Sample records for existing climate models

  1. Modeling the Environmental Impact of Air Traffic Operations

    NASA Technical Reports Server (NTRS)

    Chen, Neil

    2011-01-01

    There is increased interest to understand and mitigate the impacts of air traffic on the climate, since greenhouse gases, nitrogen oxides, and contrails generated by air traffic can have adverse impacts on the climate. The models described in this presentation are useful for quantifying these impacts and for studying alternative environmentally aware operational concepts. These models have been developed by leveraging and building upon existing simulation and optimization techniques developed for the design of efficient traffic flow management strategies. Specific enhancements to the existing simulation and optimization techniques include new models that simulate aircraft fuel flow, emissions and contrails. To ensure that these new models are beneficial to the larger climate research community, the outputs of these new models are compatible with existing global climate modeling tools like the FAA's Aviation Environmental Design Tool.

  2. A Narrowing Target for Early Mars Climate Models: Which Models Survive Confrontation with Improved Hydrology Constraints?

    NASA Astrophysics Data System (ADS)

    Kite, E. S.; Goldblatt, C.; Gao, P.; Mayer, D. P.; Sneed, J.; Wilson, S. A.

    2016-12-01

    The wettest climates in Mars' geologic history represent habitability optima, and also set the tightest constraints on climate models. For lake-forming climates on Early Mars, geologic data constrain discharge, duration, intermittency, and the number of lake-forming events. We synthesise new and existing data to suggest that post-Noachian lake-forming climates were widely separated in time, lasted >10^4 yr individually, were few in number, but cumulatively lasted <10^7 yr (to allow olivine to survive globally). We compare these data against existing models, set out a new model involving methane bursts, and conclude with future directions for Early Mars geologic analysis and modelling work.

  3. 78 FR 13874 - Watershed Modeling To Assess the Sensitivity of Streamflow, Nutrient, and Sediment Loads to...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-03-01

    ... an improved understanding of methodological challenges associated with integrating existing tools and... methodological challenges associated with integrating existing tools (e.g., climate models, downscaling... sensitivity to methodological choices such as different approaches for downscaling global climate change...

  4. How do various maize crop models vary in their responses to climate change factors?

    USDA-ARS?s Scientific Manuscript database

    Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models give similar grain yield responses to changes in climatic factors, or whether they agr...

  5. Quasi-decadal Oscillation in the CMIP5 and CMIP3 Climate Model Simulations: California Case

    NASA Astrophysics Data System (ADS)

    Wang, J.; Yin, H.; Reyes, E.; Chung, F. I.

    2014-12-01

    The ongoing three drought years in California are reminding us of two other historical long drought periods: 1987-1992 and 1928-1934. This kind of interannual variability is corresponding to the dominating 7-15 yr quasi-decadal oscillation in precipitation and streamflow in California. When using global climate model projections to assess the climate change impact on water resources planning in California, it is natural to ask if global climate models are able to reproduce the observed interannual variability like 7-15 yr quasi-decadal oscillation. Further spectral analysis to tree ring retrieved precipitation and historical precipitation record proves the existence of 7-15 yr quasi-decadal oscillation in California. But while implementing spectral analysis to all the CMIP5 and CMIP3 global climate model historical simulations using wavelet analysis approach, it was found that only two models in CMIP3 , CGCM 2.3.2a of MRI and NCAP PCM1.0, and only two models in CMIP5, MIROC5 and CESM1-WACCM, have statistically significant 7-15 yr quasi-decadal oscillations in California. More interesting, the existence of 7-15 yr quasi-decadal oscillation in the global climate model simulation is also sensitive to initial conditions. 12-13 yr quasi-decadal oscillation occurs in one ensemble run of CGCM 2.3.2a of MRI but does not exist in the other four ensemble runs.

  6. Assessing adaptation to the health risks of climate change: what guidance can existing frameworks provide?

    PubMed

    Füssel, Hans-Martin

    2008-02-01

    Climate change adaptation assessments aim at assisting policy-makers in reducing the health risks associated with climate change and variability. This paper identifies key characteristics of the climate-health relationship and of the adaptation decision problem that require consideration in climate change adaptation assessments. It then analyzes whether these characteristics are appropriately considered in existing guidelines for climate impact and adaptation assessment and in pertinent conceptual models from environmental epidemiology. The review finds three assessment guidelines based on a generalized risk management framework to be most useful for guiding adaptation assessments of human health. Since none of them adequately addresses all key challenges of the adaptation decision problem, actual adaptation assessments need to combine elements from different guidelines. Established conceptual models from environmental epidemiology are found to be of limited relevance for assessing and planning adaptation to climate change since the prevailing toxicological model of environmental health is not applicable to many climate-sensitive health risks.

  7. Updating Known Distribution Models for Forecasting Climate Change Impact on Endangered Species

    PubMed Central

    Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

    2013-01-01

    To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only. PMID:23840330

  8. Updating known distribution models for forecasting climate change impact on endangered species.

    PubMed

    Muñoz, Antonio-Román; Márquez, Ana Luz; Real, Raimundo

    2013-01-01

    To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli's Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species' distribution, instead of building new models that are based on climate change variables only.

  9. A linear regression model for predicting PNW estuarine temperatures in a changing climate

    EPA Science Inventory

    Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

  10. Climate change in grasslands, shrublands, and deserts of the interior American West: a review and needs assessment

    Treesearch

    Deborah M. Finch

    2012-01-01

    Recent research and species distribution modeling predict large changes in the distributions of species and vegetation types in the western interior of the United States in response to climate change. This volume reviews existing climate models that predict species and vegetation changes in the western United States, and it synthesizes knowledge about climate change...

  11. A model for evaluating stream temperature response to climate change scenarios in Wisconsin

    USGS Publications Warehouse

    Westenbroek, Stephen M.; Stewart, Jana S.; Buchwald, Cheryl A.; Mitro, Matthew G.; Lyons, John D.; Greb, Steven

    2010-01-01

    Global climate change is expected to alter temperature and flow regimes for streams in Wisconsin over the coming decades. Stream temperature will be influenced not only by the predicted increases in average air temperature, but also by changes in baseflow due to changes in precipitation patterns and amounts. In order to evaluate future stream temperature and flow regimes in Wisconsin, we have integrated two existing models in order to generate a water temperature time series at a regional scale for thousands of stream reaches where site-specific temperature observations do not exist. The approach uses the US Geological Survey (USGS) Soil-Water-Balance (SWB) model, along with a recalibrated version of an existing artificial neural network (ANN) stream temperature model. The ANN model simulates stream temperatures on the basis of landscape variables such as land use and soil type, and also includes climate variables such as air temperature and precipitation amounts. The existing ANN model includes a landscape variable called DARCY designed to reflect the potential for groundwater recharge in the contributing area for a stream segment. SWB tracks soil-moisture and potential recharge at a daily time step, providing a way to link changing climate patterns and precipitation amounts over time to baseflow volumes, and presumably to stream temperatures. The recalibrated ANN incorporates SWB-derived estimates of potential recharge to supplement the static estimates of groundwater flow potential derived from a topographically based model (DARCY). SWB and the recalibrated ANN will be supplied with climate drivers from a suite of general circulation models and emissions scenarios, enabling resource managers to evaluate possible changes in stream temperature regimes for Wisconsin.

  12. Statistical surrogate models for prediction of high-consequence climate change.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

    2011-09-01

    In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

  13. Common Warming Pattern Emerges Irrespective of Forcing Location

    NASA Astrophysics Data System (ADS)

    Kang, Sarah M.; Park, Kiwoong; Jin, Fei-Fei; Stuecker, Malte F.

    2017-10-01

    The Earth's climate is changing due to the existence of multiple radiative forcing agents. It is under question whether different forcing agents perturb the global climate in a distinct way. Previous studies have demonstrated the existence of similar climate response patterns in response to aerosol and greenhouse gas (GHG) forcings. In this study, the sensitivity of tropospheric temperature response patterns to surface heating distributions is assessed by forcing an atmospheric general circulation model coupled to an aquaplanet slab ocean with a wide range of possible forcing patterns. We show that a common climate pattern emerges in response to localized forcing at different locations. This pattern, characterized by enhanced warming in the tropical upper troposphere and the polar lower troposphere, resembles the historical trends from observations and models as well as the future projections. Atmospheric dynamics in combination with thermodynamic air-sea coupling are primarily responsible for shaping this pattern. Identifying this common pattern strengthens our confidence in the projected response to GHG and aerosols in complex climate models.

  14. Linking Wildfire and Climate as Drivers of Plant Species and Community-level Change

    NASA Astrophysics Data System (ADS)

    Newingham, B. A.; Hudak, A. T.; Bright, B. C.

    2015-12-01

    Plant species distributions and community shifts after fire are affected by burn severity, elevation, aspect, and climate. However, little empirical data exists on long-term (decadal) recovery after fire across these interacting factors, limiting understanding of fire regime characteristics and climate in post-fire community trajectories. We examined plant species and community responses a decade after fire across five fires in ponderosa pine, dry mixed coniferous, and moist mixed coniferous forests across the western USA. Using field data, we determined changes in plant communities one and ten years post-fire across gradients of burn severity, elevation, and aspect. Existing published work has shown that plant species distributions can be accurately predicted from physiologically relevant climate variables using non-parametric Random Forests models; such models have also been linked to projected climate profiles in 2030, 2060, and 2090 generated from three commonly used general circulation models (GCMs). We explore the possibility that fire and climate are coupled drivers affecting plant species distributions. Climate change may not manifest as a slow shift in plant species distributions, but as sudden, localized events tied to changing fire and other disturbance regimes.

  15. Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise

    USDA-ARS?s Scientific Manuscript database

    The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible un...

  16. A New Framework for Cumulus Parametrization - A CPT in action

    NASA Astrophysics Data System (ADS)

    Jakob, C.; Peters, K.; Protat, A.; Kumar, V.

    2016-12-01

    The representation of convection in climate model remains a major Achilles Heel in our pursuit of better predictions of global and regional climate. The basic principle underpinning the parametrisation of tropical convection in global weather and climate models is that there exist discernible interactions between the resolved model scale and the parametrised cumulus scale. Furthermore, there must be at least some predictive power in the larger scales for the statistical behaviour on small scales for us to be able to formally close the parametrised equations. The presentation will discuss a new framework for cumulus parametrisation based on the idea of separating the prediction of cloud area from that of velocity. This idea is put into practice by combining an existing multi-scale stochastic cloud model with observations to arrive at the prediction of the area fraction for deep precipitating convection. Using mid-tropospheric humidity and vertical motion as predictors, the model is shown to reproduce the observed behaviour of both mean and variability of deep convective area fraction well. The framework allows for the inclusion of convective organisation and can - in principle - be made resolution-aware or resolution-independent. When combined with simple assumptions about cloud-base vertical motion the model can be used as a closure assumption in any existing cumulus parametrisation. Results of applying this idea in the the ECHAM model indicate significant improvements in the simulation of tropical variability, including but not limited to the MJO. This presentation will highlight how the close collaboration of the observational, theoretical and model development community in the spirit of the climate process teams can lead to significant progress in long-standing issues in climate modelling while preserving the freedom of individual groups in pursuing their specific implementation of an agreed framework.

  17. Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems.

    PubMed

    Del Prado, A; Crosson, P; Olesen, J E; Rotz, C A

    2013-06-01

    The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

  18. An empirical perspective for understanding climate change impacts in Switzerland

    USGS Publications Warehouse

    Henne, Paul; Bigalke, Moritz; Büntgen, Ulf; Colombaroli, Daniele; Conedera, Marco; Feller, Urs; Frank, David; Fuhrer, Jürg; Grosjean, Martin; Heiri, Oliver; Luterbacher, Jürg; Mestrot, Adrien; Rigling, Andreas; Rössler, Ole; Rohr, Christian; Rutishauser, This; Schwikowski, Margit; Stampfli, Andreas; Szidat, Sönke; Theurillat, Jean-Paul; Weingartner, Rolf; Wilcke, Wolfgan; Tinner, Willy

    2018-01-01

    Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.

  19. Modeling lakes and reservoirs in the climate system

    USGS Publications Warehouse

    MacKay, M.D.; Neale, P.J.; Arp, C.D.; De Senerpont Domis, L. N.; Fang, X.; Gal, G.; Jo, K.D.; Kirillin, G.; Lenters, J.D.; Litchman, E.; MacIntyre, S.; Marsh, P.; Melack, J.; Mooij, W.M.; Peeters, F.; Quesada, A.; Schladow, S.G.; Schmid, M.; Spence, C.; Stokes, S.L.

    2009-01-01

    Modeling studies examining the effect of lakes on regional and global climate, as well as studies on the influence of climate variability and change on aquatic ecosystems, are surveyed. Fully coupled atmosphere-land surface-lake climate models that could be used for both of these types of study simultaneously do not presently exist, though there are many applications that would benefit from such models. It is argued here that current understanding of physical and biogeochemical processes in freshwater systems is sufficient to begin to construct such models, and a path forward is proposed. The largest impediment to fully representing lakes in the climate system lies in the handling of lakes that are too small to be explicitly resolved by the climate model, and that make up the majority of the lake-covered area at the resolutions currently used by global and regional climate models. Ongoing development within the hydrological sciences community and continual improvements in model resolution should help ameliorate this issue.

  20. Assessment of Vulnerability to Climate Change Effects on Urban Stormwater Infrastructure in City of Las Vegas, NV

    NASA Astrophysics Data System (ADS)

    Thakali, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

    2016-12-01

    In the spring of 2016 the City of Las Vegas and the Southern Illinois University began collaborating on a project that seeks to assess the city's current vulnerability to drought, extreme heat, and extreme precipitation patterns, as well as the response mechanisms that are already in place within its jurisdiction. The document analyzes a series of scenarios to assess to what extent the vulnerability of four Key Planning Areas will change in the long term (30-50 years), what will be the most affected city operations, and what mechanisms the City will need to put into place to adapt to such changes. As part of the vulnerability report, this study assessed the impacts of climate change in the existing stormwater system of the Gowan watershed within City of Las Vegas, NV, by assessing projected design storms. The climate change projection for the region was evaluated using the high-resolution North American Regional Climate Change Assessment Program (NARCCAP) climate model data. The design storms (6h 100y) were calculated using the best fitted probability distribution among twenty-seven distributions for the historic and future NARCCAP climate model projection. North American Regional Reanalysis (NARR) data were used to assess the performance of NARCCAP data. The projected design storms were implemented in an existing U.S. Army Corps of Engineers' Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model developed by Clark County Regional Flood Control District (CCRFCD), Las Vegas. The simulation results showed an increase in the design storms which exceeded the capacity of existing stormwater infrastructure.

  1. Exploring Climate Niches of Ponderosa Pine (Pinus ponderosa Douglas ex Lawson) Haplotypes in the Western United States: Implications for Evolutionary History and Conservation

    PubMed Central

    Shinneman, Douglas J.; Potter, Kevin M.; Hipkins, Valerie D.

    2016-01-01

    Ponderosa pine (Pinus ponderosa Douglas ex Lawson) occupies montane environments throughout western North America, where it is both an ecologically and economically important tree species. A recent study using mitochondrial DNA analysis demonstrated substantial genetic variation among ponderosa pine populations in the western U.S., identifying 10 haplotypes with unique evolutionary lineages that generally correspond spatially with distributions of the Pacific (P. p. var. ponderosa) and Rocky Mountain (P. p. var. scopulorum) varieties. To elucidate the role of climate in shaping the phylogeographic history of ponderosa pine, we used nonparametric multiplicative regression to develop predictive climate niche models for two varieties and 10 haplotypes and to hindcast potential distribution of the varieties during the last glacial maximum (LGM), ~22,000 yr BP. Our climate niche models performed well for the varieties, but haplotype models were constrained in some cases by small datasets and unmeasured microclimate influences. The models suggest strong relationships between genetic lineages and climate. Particularly evident was the role of seasonal precipitation balance in most models, with winter- and summer-dominated precipitation regimes strongly associated with P. p. vars. ponderosa and scopulorum, respectively. Indeed, where present-day climate niches overlap between the varieties, introgression of two haplotypes also occurs along a steep clinal divide in western Montana. Reconstructed climate niches for the LGM suggest potentially suitable climate existed for the Pacific variety in the California Floristic province, the Great Basin, and Arizona highlands, while suitable climate for the Rocky Mountain variety may have existed across the southwestern interior highlands. These findings underscore potentially unique phylogeographic origins of modern ponderosa pine evolutionary lineages, including potential adaptations to Pleistocene climates associated with discrete temporary glacial refugia. Our predictive climate niche models may inform strategies for further genetic research (e.g., sampling design) and conservation that promotes haplotype compatibility with projected changes in future climate. PMID:26985674

  2. Exploring Climate Niches of Ponderosa Pine (Pinus ponderosa Douglas ex Lawson) Haplotypes in the Western United States: Implications for Evolutionary History and Conservation.

    PubMed

    Shinneman, Douglas J; Means, Robert E; Potter, Kevin M; Hipkins, Valerie D

    2016-01-01

    Ponderosa pine (Pinus ponderosa Douglas ex Lawson) occupies montane environments throughout western North America, where it is both an ecologically and economically important tree species. A recent study using mitochondrial DNA analysis demonstrated substantial genetic variation among ponderosa pine populations in the western U.S., identifying 10 haplotypes with unique evolutionary lineages that generally correspond spatially with distributions of the Pacific (P. p. var. ponderosa) and Rocky Mountain (P. p. var. scopulorum) varieties. To elucidate the role of climate in shaping the phylogeographic history of ponderosa pine, we used nonparametric multiplicative regression to develop predictive climate niche models for two varieties and 10 haplotypes and to hindcast potential distribution of the varieties during the last glacial maximum (LGM), ~22,000 yr BP. Our climate niche models performed well for the varieties, but haplotype models were constrained in some cases by small datasets and unmeasured microclimate influences. The models suggest strong relationships between genetic lineages and climate. Particularly evident was the role of seasonal precipitation balance in most models, with winter- and summer-dominated precipitation regimes strongly associated with P. p. vars. ponderosa and scopulorum, respectively. Indeed, where present-day climate niches overlap between the varieties, introgression of two haplotypes also occurs along a steep clinal divide in western Montana. Reconstructed climate niches for the LGM suggest potentially suitable climate existed for the Pacific variety in the California Floristic province, the Great Basin, and Arizona highlands, while suitable climate for the Rocky Mountain variety may have existed across the southwestern interior highlands. These findings underscore potentially unique phylogeographic origins of modern ponderosa pine evolutionary lineages, including potential adaptations to Pleistocene climates associated with discrete temporary glacial refugia. Our predictive climate niche models may inform strategies for further genetic research (e.g., sampling design) and conservation that promotes haplotype compatibility with projected changes in future climate.

  3. Exploring climate niches of ponderosa pine (Pinus ponderosa Douglas ex Lawson) haplotypes in the western United States: Implications for evolutionary history and conservation

    USGS Publications Warehouse

    Shinneman, Douglas; Means, Robert E.; Potter, Kevin M.; Hipkins, Valerie D.

    2016-01-01

    Ponderosa pine (Pinus ponderosa Douglas ex Lawson) occupies montane environments throughout western North America, where it is both an ecologically and economically important tree species. A recent study using mitochondrial DNA analysis demonstrated substantial genetic variation among ponderosa pine populations in the western U.S., identifying 10 haplotypes with unique evolutionary lineages that generally correspond spatially with distributions of the Pacific (P. p. var. ponderosa) and Rocky Mountain (P. p. var. scopulorum) varieties. To elucidate the role of climate in shaping the phylogeographic history of ponderosa pine, we used nonparametric multiplicative regression to develop predictive climate niche models for two varieties and 10 haplotypes and to hindcast potential distribution of the varieties during the last glacial maximum (LGM), ~22,000 yr BP. Our climate niche models performed well for the varieties, but haplotype models were constrained in some cases by small datasets and unmeasured microclimate influences. The models suggest strong relationships between genetic lineages and climate. Particularly evident was the role of seasonal precipitation balance in most models, with winter- and summer-dominated precipitation regimes strongly associated with P. p. vars. ponderosa and scopulorum, respectively. Indeed, where present-day climate niches overlap between the varieties, introgression of two haplotypes also occurs along a steep clinal divide in western Montana. Reconstructed climate niches for the LGM suggest potentially suitable climate existed for the Pacific variety in the California Floristic province, the Great Basin, and Arizona highlands, while suitable climate for the Rocky Mountain variety may have existed across the southwestern interior highlands. These findings underscore potentially unique phylogeographic origins of modern ponderosa pine evolutionary lineages, including potential adaptations to Pleistocene climates associated with discrete temporary glacial refugia. Our predictive climate niche models may inform strategies for further genetic research (e.g., sampling design) and conservation that promotes haplotype compatibility with projected changes in future climate.

  4. An investigation of the Archean climate using the NCAR CCm

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Jenkins, G.S.

    1991-01-01

    The Archean (2.5 to 3.8 billion years ago) is of interest climatically, because of the 'Faint-Young Sun Paradox', which can be characterized by the Sun's reduced energy output. This lower energy output leads to a frozen planet if the climate existed as it does today. But, the geologic record shows that water was flowing at the earth's surface 3.8 billion years ago. Energy Balance Models (EBMs) and one-dimensional radiative-convective (1DRC) models predict a frozen planet for this time period, unless large carbon dioxide (CO2) concentrations exist in the Archean atmosphere. The goal is to explore the Archean climate with themore » National Center for Atmospheric Research (NCAR), Community Climate Model (CCM). The search for negative feedbacks to explain the 'Faint-Young Sun Paradox' is the thrust of this study. This study undertakes a series of sensitivity simulations which first explores individual factors that may be important for the Archean. They include rotation rate, lower solar luminosity, and land fraction. Then, these climatic factors along with higher CO2 concentrations are combined into a set of experiments. A faster rotation rate may have existed in the Archean. The faster rotation rate simulations show warmer globally averaged surface temperatures that are caused by a 20 percent decrease in the total cloud fraction. The smaller cloud fraction is brought about by dynamical changes. A global ocean is a possibility for the Archean. A global ocean simulation predicts 4 K increase in global mean surface temperatures compared to the present-day climate control.« less

  5. Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Liu, Lu; Hejazi, Mohamad; Li, Hongyi

    This study explores the interactions between climate and thermoelectric generation in the U.S. by coupling an Earth System Model with a thermoelectric power generation model. We validated model simulations of power production for selected power plants (~44% of existing thermoelectric capacity) against reported values. In addition, we projected future usable capacity for existing power plants under two different climate change scenarios. Results indicate that climate change alone may reduce average thermoelectric generating capacity by 2%-3% by the 2060s. Reductions up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. This study concludes that the impactmore » of climate change on the U.S. thermoelectric power system is less than previous estimates due to an inclusion of a spatially-disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. This work highlights the significance of accounting for legal constructs in which the operation of power plants are managed, and underscores the effects of provisional variances in addition to environmental requirements.« less

  6. Use of NARCCAP Model Projections to Develop a Future Typical Meteorological Year and Estimate the Impact of a Changing Climate on Building Energy Consumption

    NASA Astrophysics Data System (ADS)

    Patton, S. L.; Takle, E. S.; Passe, U.; Kalvelage, K.

    2013-12-01

    Current simulations of building energy consumption use weather input files based on the past thirty years of climate observations. These 20th century climate conditions may be inadequate when designing buildings meant to function well into the 21st century. An alternative is using model projections of climate change to estimate future risk to the built environment. In this study, model-projected changes in climate were combined with existing typical meteorological year data to create future typical meteorological year data. These data were then formatted for use in EnergyPlus simulation software to evaluate their potential impact on commercial building energy consumption. The modeled climate data were taken from the North American Regional Climate Change Assessment Program (NARCCAP). NARCCAP uses results of global climate models to drive regional climate models, also known as dynamical downscaling. This downscaling gives higher resolution results over specific locations, and the multiple global/regional climate model combinations provide a unique opportunity to quantify the uncertainty of climate change projections and their impacts. Our results show a projected decrease in heating energy consumption and a projected increase in cooling energy consumption for nine locations across the United States for all model combinations. Warmer locations may expect a decrease in heating load of around 30% to 45% and an increase in cooling load of around 25% to 35%. Colder locations may expect a decrease in heating load of around 15% to 25% and an increase in cooling load of around 40% to 70%. The change in net energy consumption is determined by the balance between the magnitudes of heating change and cooling change. Net energy consumption is projected to increase by an average of 5% for lower-latitude locations and decrease by an average of 5% for higher-latitude locations. With these projected annual and seasonal changes presenting strong evidence for the unsuitable nature of current building practices holding up under future climate change, we recommend using our methods and results to make modifications and adaptations to existing buildings and to aid in the design of future buildings.

  7. Representation of the West African Monsoon System in the aerosol-climate model ECHAM6-HAM2

    NASA Astrophysics Data System (ADS)

    Stanelle, Tanja; Lohmann, Ulrike; Bey, Isabelle

    2017-04-01

    The West African Monsoon (WAM) is a major component of the global monsoon system. The temperature contrast between the Saharan land surface in the North and the sea surface temperature in the South dominates the WAM formation. The West African region receives most of its precipitation during the monsoon season between end of June and September. Therefore the existence of the monsoon is of major social and economic importance. We discuss the ability of the climate model ECHAM6 as well as the coupled aerosol climate model ECHAM6-HAM2 to simulate the major features of the WAM system. The north-south temperature gradient is reproduced by both model versions but all model versions fail in reproducing the precipitation amount south of 10° N. A special focus is on the representation of the nocturnal low level jet (NLLJ) and the corresponding enhancement of low level clouds (LLC) at the Guinea Coast, which are a crucial factor for the regional energy budget. Most global climate models have difficulties to represent these features. The pure climate model ECHAM6 is able to simulate the existence of the NLLJ and LLC, but the model does not represent the pronounced diurnal cycle. Overall, the representation of LLC is worse in the coupled model. We discuss the model behaviors on the basis of outputted temperature and humidity tendencies and try to identify potential processes responsible for the model deficiencies.

  8. Integrating Climate and Ocean Change Vulnerability into Conservation Planning

    NASA Astrophysics Data System (ADS)

    Mcleod, E.; Green, A.; Game, E.; Anthony, K.; Cinner, J.; Heron, S. F.; Kleypas, J. A.; Lovelock, C.; Pandolfi, J.; Pressey, B.; Salm, R.; Schill, S.; Woodroffe, C. D.

    2013-05-01

    Tropical coastal and marine ecosystems are particularly vulnerable to ocean warming, ocean acidification, and sea-level rise. Yet these projected climate and ocean change impacts are rarely considered in conservation planning due to the lack of guidance on how existing climate and ocean change models, tools, and data can be applied. We address this gap by describing how conservation planning can use available tools and data for assessing the vulnerability of tropical marine ecosystems to key climate threats. Additionally, we identify limitations of existing tools and provide recommendations for future research to improve integration of climate and ocean change information and conservation planning. Such information is critical for developing a conservation response that adequately protects these ecosystems and dependent coastal communities in the face of climate and ocean change.

  9. Reassessing Pliocene temperature gradients

    NASA Astrophysics Data System (ADS)

    Tierney, J. E.

    2017-12-01

    With CO2 levels similar to present, the Pliocene Warm Period (PWP) is one of our best analogs for climate change in the near future. Temperature proxy data from the PWP describe dramatically reduced zonal and meridional temperature gradients that have proved difficult to reproduce with climate model simulations. Recently, debate has emerged regarding the interpretation of the proxies used to infer Pliocene temperature gradients; these interpretations affect the magnitude of inferred change and the degree of inconsistency with existing climate model simulations of the PWP. Here, I revisit the issue using Bayesian proxy forward modeling and prediction that propagates known uncertainties in the Mg/Ca, UK'37, and TEX86 proxy systems. These new spatiotemporal predictions are quantitatively compared to PWP simulations to assess probabilistic agreement. Results show generally good agreement between existing Pliocene simulations from the PlioMIP ensemble and SST proxy data, suggesting that exotic changes in the ocean-atmosphere are not needed to explain the Pliocene climate state. Rather, the spatial changes in SST during the Pliocene are largely consistent with elevated CO2 forcing.

  10. A transient stochastic weather generator incorporating climate model uncertainty

    NASA Astrophysics Data System (ADS)

    Glenis, Vassilis; Pinamonti, Valentina; Hall, Jim W.; Kilsby, Chris G.

    2015-11-01

    Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called 'perturbed physics ensembles' (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.

  11. Representing agriculture in Earth System Models: Approaches and priorities for development

    NASA Astrophysics Data System (ADS)

    McDermid, S. S.; Mearns, L. O.; Ruane, A. C.

    2017-09-01

    Earth System Model (ESM) advances now enable improved representations of spatially and temporally varying anthropogenic climate forcings. One critical forcing is global agriculture, which is now extensive in land-use and intensive in management, owing to 20th century development trends. Agriculture and food systems now contribute nearly 30% of global greenhouse gas emissions and require copious inputs and resources, such as fertilizer, water, and land. Much uncertainty remains in quantifying important agriculture-climate interactions, including surface moisture and energy balances and biogeochemical cycling. Despite these externalities and uncertainties, agriculture is increasingly being leveraged to function as a net sink of anthropogenic carbon, and there is much emphasis on future sustainable intensification. Given its significance as a major environmental and climate forcing, there now exist a variety of approaches to represent agriculture in ESMs. These approaches are reviewed herein, and range from idealized representations of agricultural extent to the development of coupled climate-crop models that capture dynamic feedbacks. We highlight the robust agriculture-climate interactions and responses identified by these modeling efforts, as well as existing uncertainties and model limitations. To this end, coordinated and benchmarking assessments of land-use-climate feedbacks can be leveraged for further improvements in ESM's agricultural representations. We suggest key areas for continued model development, including incorporating irrigation and biogeochemical cycling in particular. Last, we pose several critical research questions to guide future work. Our review focuses on ESM representations of climate-surface interactions over managed agricultural lands, rather than on ESMs as an estimation tool for crop yields and productivity.

  12. Hemispheric symmetry of the Earth's Energy Balance as a fundamental constraint on the Earth's climate

    NASA Astrophysics Data System (ADS)

    Stephens, G. L.; Webster, P. J.; OBrien, D. M.

    2013-12-01

    We currently lack a quantitative understanding of how the Earth's energy balance and the poleward energy transport adjust to different forcings that determine climate change. Currently, there are no constraints that guide this understanding. We will demonstrate that the Earth's energy balance exhibits a remarkable symmetry about the equator, and that this symmetry is a necessary condition of a steady state climate. Our analysis points to clouds as the principal agent that highly regulates this symmetry and sets the steady state. The existence of this thermodynamic steady-state constraint on climate and the symmetry required to sustain it leads to important inferences about the synchronous nature of climate changes between hemispheres, offering for example insights on mechanisms that can sustain global ice ages forced by asymmetric hemispheric solar radiation variations or how climate may respond to increases in greenhouse gas concentration. Further inferences regarding cloud effects on climate can also be deduced without resorting to the complex and intricate processes of cloud formation, whose representation continues to challenge the climate modeling community. The constraint suggests cloud feedbacks must be negative buffering the system against change. We will show that this constraint doesn't exist in the current CMIP5 model experiments and the lack of such a constraint suggests there is insufficient buffering in models in response to external forcings

  13. Weather Forecaster Understanding of Climate Models

    NASA Astrophysics Data System (ADS)

    Bol, A.; Kiehl, J. T.; Abshire, W. E.

    2013-12-01

    Weather forecasters, particularly those in broadcasting, are the primary conduit to the public for information on climate and climate change. However, many weather forecasters remain skeptical of model-based climate projections. To address this issue, The COMET Program developed an hour-long online lesson of how climate models work, targeting an audience of weather forecasters. The module draws on forecasters' pre-existing knowledge of weather, climate, and numerical weather prediction (NWP) models. In order to measure learning outcomes, quizzes were given before and after the lesson. Preliminary results show large learning gains. For all people that took both pre and post-tests (n=238), scores improved from 48% to 80%. Similar pre/post improvement occurred for National Weather Service employees (51% to 87%, n=22 ) and college faculty (50% to 90%, n=7). We believe these results indicate a fundamental misunderstanding among many weather forecasters of (1) the difference between weather and climate models, (2) how researchers use climate models, and (3) how they interpret model results. The quiz results indicate that efforts to educate the public about climate change need to include weather forecasters, a vital link between the research community and the general public.

  14. Application of synthetic scenarios to address water resource concerns: A management-guided case study from the Upper Colorado River Basin

    USGS Publications Warehouse

    McAfee, Stephanie A.; Pederson, Gregory T.; Woodhouse, Connie A.; McCabe, Gregory

    2017-01-01

    Water managers are increasingly interested in better understanding and planning for projected resource impacts from climate change. In this management-guided study, we use a very large suite of synthetic climate scenarios in a statistical modeling framework to simultaneously evaluate how (1) average temperature and precipitation changes, (2) initial basin conditions, and (3) temporal characteristics of the input climate data influence water-year flow in the Upper Colorado River. The results here suggest that existing studies may underestimate the degree of uncertainty in future streamflow, particularly under moderate temperature and precipitation changes. However, we also find that the relative severity of future flow projections within a given climate scenario can be estimated with simple metrics that characterize the input climate data and basin conditions. These results suggest that simple testing, like the analyses presented in this paper, may be helpful in understanding differences between existing studies or in identifying specific conditions for physically based mechanistic modeling. Both options could reduce overall cost and improve the efficiency of conducting climate change impacts studies.

  15. Global precipitation measurements for validating climate models

    NASA Astrophysics Data System (ADS)

    Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

    2017-11-01

    The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

  16. Using Scenario Development to Encourage Tourism Business Resilience in the Great Lakes

    NASA Astrophysics Data System (ADS)

    Chin, N.; Day, J.; Sydnor, S.; Cherkauer, K. A.

    2015-12-01

    Tourism is an economic sector anticipated to be greatly affected by climate change, but the potential impacts of climate change on tourism have rarely been examined in detail in existing research. Past research has shown, however, that the small and medium businesses that dominate the tourism sector could be greatly impacted by climate change. We have presented global climate and hydrologic model research results to pre-selected coastal tourism business owners in the Great Lakes region to determine the best methods for delivering user-friendly future climate scenarios, given that existing research suggests that climate change adaptive behaviors and resilience increase with information (message) clarity. Model output analyses completed for this work have focused on temperature, precipitation, and extreme weather events due to their economic impact on tourism activities. We have also experimented with the development and use of infographics because of their ability to present information quickly and clearly. Initial findings of this work will be presented as well as lessons learned from stakeholder interactions. Two main results include that (1) extreme weather events may have more meaning to tourism business owners than general trends in climate and (2) long-term planning for climate is extremely difficult for tourism business owners because they operate on a much shorter planning timeline than those generally used for climate change analyses.

  17. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate.

    PubMed

    Beer, Christian; Reichstein, Markus; Tomelleri, Enrico; Ciais, Philippe; Jung, Martin; Carvalhais, Nuno; Rödenbeck, Christian; Arain, M Altaf; Baldocchi, Dennis; Bonan, Gordon B; Bondeau, Alberte; Cescatti, Alessandro; Lasslop, Gitta; Lindroth, Anders; Lomas, Mark; Luyssaert, Sebastiaan; Margolis, Hank; Oleson, Keith W; Roupsard, Olivier; Veenendaal, Elmar; Viovy, Nicolas; Williams, Christopher; Woodward, F Ian; Papale, Dario

    2010-08-13

    Terrestrial gross primary production (GPP) is the largest global CO(2) flux driving several ecosystem functions. We provide an observation-based estimate of this flux at 123 +/- 8 petagrams of carbon per year (Pg C year(-1)) using eddy covariance flux data and various diagnostic models. Tropical forests and savannahs account for 60%. GPP over 40% of the vegetated land is associated with precipitation. State-of-the-art process-oriented biosphere models used for climate predictions exhibit a large between-model variation of GPP's latitudinal patterns and show higher spatial correlations between GPP and precipitation, suggesting the existence of missing processes or feedback mechanisms which attenuate the vegetation response to climate. Our estimates of spatially distributed GPP and its covariation with climate can help improve coupled climate-carbon cycle process models.

  18. Effect of climate change on marine ecosystems

    NASA Astrophysics Data System (ADS)

    Vikebo, F. B.; Sundby, S.; Aadlandsvik, B.; Fiksen, O.

    2003-04-01

    As a part of the INTEGRATION project, headed by Potsdam Institute for Climate Impact Research, funded by the German Research Council, the impact of climate change scenarios on marine fish populations will be addressed on a spesific population basis and will focus on fish populations in the northern North Atlantic with special emphasis on cod. The approach taken will mainly be a modelling study supported by analysis of existing data on fish stocks and climate. Through down-scaling and nesting techniques, various climate change scenarios with reduced THC in the North Atlantic will be investigated with higher spatial resolution for selected shelf areas. The hydrodynamical model used for the regional ocean modeling is ROMS (http://marine.rutgers.edu/po/models/roms/). An individual based model will be implemented into the larval drift module to simulate growth of the larvae along the drift paths.

  19. Testing the sensitivity of past climates to the indirect effects of dust

    NASA Astrophysics Data System (ADS)

    Sagoo, Navjit; Storelvmo, Trude

    2017-06-01

    Mineral dust particles are important ice nuclei (IN) and as such indirectly impact Earth's radiative balance via the properties of cold clouds. Using the Community Earth System Model version 1.0.6, and Community Atmosphere Model version 5.1, and a new empirical parameterization for ice nucleation on dust particles, we investigate the radiative forcing induced by dust IN for different dust loadings. Dust emissions are representative of global conditions for the Last Glacial Maximum and the mid-Pliocene Warm Period. Increased dust leads to smaller and more numerous ice crystals in mixed phase clouds, impacting cloud opacity, lifetime, and precipitation. This increases the shortwave cloud radiative forcing, resulting in significant surface temperature cooling and polar amplification—which is underestimated in existing studies relative to paleoclimate archives. Large hydrological changes occur and are linked to an enhanced dynamical response. We conclude that dust indirect effects could potentially have a significant impact on the model-data mismatch that exists for paleoclimates.Plain Language SummaryMineral dust and climate are closely linked, with large fluctuations in dust deposition recorded in geological archives. Dusty conditions are generally associated with cold, glacial periods and low dust with warmer climates. The direct effects of dust on the climate (absorbing and reflecting radiation) are well understood; however, the indirect effects of dust on climate have been overlooked. Dust indirectly impacts the climate through its role as ice nuclei; the presence of dust makes it easier for ice to form in a cloud. We explore the indirect effects of dust in climates with different dust loading from the present by conducting a climate modeling study in which dust are able to act as ice nuclei. Including dust indirect effects increases the sensitivity of our model to changes in dust emission. Increasing dust impacts ice crystal numbers (increased) and size (reduced) in a cloud. This increases cloud reflectivity and lifetime, which increases the sunlight reflected by the cloud and cools the climate. Including the indirect effects of dust has a large impact on the climate, and our results indicate that this is an important but overlooked aspect of paleoclimates that could remedy some of the existing shortcomings of paleoclimate simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150014242','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150014242"><span>Uncertainty in Model Predictions of Vibrio Vulnificus Response to Climate Variability and Change: A Chesapeake Bay Case Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Urquhart, Erin A.; Zaitchik, Benjamin F.; Waugh, Darryn W.; Guikema, Seth D.; Del Castillo, Carlos E.</p> <p>2014-01-01</p> <p>The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4 C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li class="active"><span>2</span></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_2 --> <div id="page_3" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="41"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC13A1049D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC13A1049D"><span>Contradictory cooling in a warmer world? the climate of the Mediterranean region during the ';Holocene Thermal Maximum'</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Davis, B.</p> <p>2013-12-01</p> <p>Extensive evidence from high latitudes of the Northern Hemisphere indicates that temperatures were warmer than present during the early-mid Holocene, a period known as the Holocene thermal maximum (HTM). The existence of the HTM over lower mid-latitudes and the sub-tropics however is less clear, with pollen-based reconstructions in particular actually indicating a contrary cooling at this time in these regions. This apparent cooling is controversial because it is not shown in climate model simulations, which indicate that the HTM occurred across all extra-tropical latitudes of the Northern Hemisphere. This is also supported by alkenone based SST reconstructions, which also show a much more widespread HTM than indicated by the pollen data. Here this problem is investigated by reviewing the evidence both for, and against, the HTM in the Mediterranean region, which represents one of the most intensively studied regions of sub-tropical climate in the Northern Hemisphere. This evidence includes a large number of both marine and terrestrial records that can be directly compared due to their close proximity around the Mediterranean Sea. The results highlight the potential for bias in both marine and terrestrial climate proxies, but despite many criticisms of the pollen-based record, it is shown that the existence of more extensive temperate vegetation in the early-mid Holocene in the Mediterranean is difficult to explain by anything other than a cooler climate. For instance, vegetation models driven by climate model output show that the warmer climate suggested by the models produces a HTM vegetation even more arid than today. The results have important implications in the interpretation of proxy records, but perhaps most importantly, the potential for climate models to underestimate cooling processes in a warmer world needs further investigation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120014238','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120014238"><span>Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve</p> <p>2012-01-01</p> <p>Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1068717','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1068717"><span>The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Potter, Gerald L; Bader, David C; Riches, Michael</p> <p></p> <p>Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized the scientific ideas that are the basis of PCMDI's success, summarizing their evolution and impact. Four speakers followed the various PCMDI-supported climate model intercomparison projects, beginning with early work on cloud representations in models, presented by Robert D. Cess (Distinguished Professor Emeritus, Stony Brook University), and then the latest Cloud Feedback Model Intercomparison Projects (CFMIPs) led by Sandrine Bony (Laboratoire de M'©t'©orologie Dynamique). Benjamin Santer (LLNL) presented a review of the climate change detection and attribution (D & A) work pioneered at PCMDI, and Gerald A. Meehl (NCAR) ended the day with a look toward the future of climate change research.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMNH51A1861N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMNH51A1861N"><span>Understanding scale dependency of climatic processes with diarrheal disease</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nasr Azadani, F.; Jutla, A.; Akanda, A. S. S.; Colwell, R. R.</p> <p>2015-12-01</p> <p>The issue of scales in linking climatic processes with diarrheal diseases is perhaps one of the most challenging aspect to develop any predictive algorithm for outbreaks and to understand impacts of changing climate. Majority of diarrheal diseases have shown to be strongly associated with climate modulated environmental processes where pathogens survive. Using cholera as an example of characteristic diarrheal diseases, this study will provide methodological insights on dominant scale variability in climatic processes that are linked with trigger and transmission of disease. Cholera based epidemiological models use human to human interaction as a main transmission mechanism, however, environmental conditions for creating seasonality in outbreaks is not explicitly modeled. For example, existing models cannot create seasonality, unless some of the model parameters are a-priori chosen to vary seasonally. A systems based feedback approach will be presented to understand role of climatic processes on trigger and transmission disease. In order to investigate effect of changing climate on cholera, a downscaling approach using support vector machine will be used. Our preliminary results using three climate models, ECHAM5, GFDL, and HADCM show that varying modalities in future cholera outbreaks.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.H53B..03M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.H53B..03M"><span>Performance of the Hydrological Portion of a Simple Water Quality Model in Different Climatic Regions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moore, K.; Pierson, D.; Pettersson, K.; Naden, P.; Allott, N.; Jennings, E.; Tamm, T.; Järvet, A.; Nickus, U.; Thies, H.; Arvola, L.; Järvinen, M.; Schneiderman, E.; Zion, M.; Lounsbury, D.</p> <p>2004-05-01</p> <p>We are applying an existing watershed model in the EU CLIME (Climate and Lake Impacts in Europe) project to evaluate the effects of weather on seasonal and annual delivery of N, P, and DOC to lakes. Model calibration is based on long-term records of weather and water quality data collected from sites in different climatic regions spread across Europe and in New York State. The overall aim of the CLIME project is to develop methods and models to support lake and catchment management under current climate conditions and make predictions under future climate scenarios. Scientists from 10 partner countries are collaborating on developing a consistent approach to defining model parameters for the Generalized Watershed Loading Functions (GWLF) model, one of a larger suite of models used in the project. An example of the approach for the hydrological portion of the GWLF model will be presented, with consideration of the balance between model simplicity, ease of use, data requirements, and realistic predictions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29569799','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29569799"><span>How will climate novelty influence ecological forecasts? Using the Quaternary to assess future reliability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fitzpatrick, Matthew C; Blois, Jessica L; Williams, John W; Nieto-Lugilde, Diego; Maguire, Kaitlin C; Lorenz, David J</p> <p>2018-03-23</p> <p>Future climates are projected to be highly novel relative to recent climates. Climate novelty challenges models that correlate ecological patterns to climate variables and then use these relationships to forecast ecological responses to future climate change. Here, we quantify the magnitude and ecological significance of future climate novelty by comparing it to novel climates over the past 21,000 years in North America. We then use relationships between model performance and climate novelty derived from the fossil pollen record from eastern North America to estimate the expected decrease in predictive skill of ecological forecasting models as future climate novelty increases. We show that, in the high emissions scenario (RCP 8.5) and by late 21st century, future climate novelty is similar to or higher than peak levels of climate novelty over the last 21,000 years. The accuracy of ecological forecasting models is projected to decline steadily over the coming decades in response to increasing climate novelty, although models that incorporate co-occurrences among species may retain somewhat higher predictive skill. In addition to quantifying future climate novelty in the context of late Quaternary climate change, this work underscores the challenges of making reliable forecasts to an increasingly novel future, while highlighting the need to assess potential avenues for improvement, such as increased reliance on geological analogs for future novel climates and improving existing models by pooling data through time and incorporating assemblage-level information. © 2018 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26750759','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26750759"><span>Future Warming Patterns Linked to Today's Climate Variability.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dai, Aiguo</p> <p>2016-01-11</p> <p>The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1130216-agriculture-climate-change-global-scenarios-why-don-models-agree','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1130216-agriculture-climate-change-global-scenarios-why-don-models-agree"><span>Agriculture and Climate Change in Global Scenarios: Why Don't the Models Agree</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Nelson, Gerald; van der Mensbrugghe, Dominique; Ahammad, Helal</p> <p></p> <p>Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs makes direct use of weather inputs. Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes of key variables such as prices, production, and trade. These divergent outcomes arise from differences in model inputs and model specification. The goal of this paper is to review climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. Bymore » providing common productivity drivers that include climate change effects, differences in model outcomes are reduced. All models show higher prices in 2050 because of negative productivity shocks from climate change. The magnitude of the price increases, and the adaptation responses, differ significantly across the various models. Substantial differences exist in the structural parameters affecting demand, area, and yield, and should be a topic for future research.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H23M..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H23M..06T"><span>Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taner, M. U.; Wi, S.; Brown, C.</p> <p>2017-12-01</p> <p>The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/40383','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/40383"><span>Height-growth response to climatic changes differs among populations of Douglas-fir: A novel analysis of historic data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Laura P. Leites; Andrew P. Robinson; Gerald E. Rehfeldt; John D. Marshall; Nicholas L. Crookston</p> <p>2012-01-01</p> <p>Projected climate change will affect existing forests, as substantial changes are predicted to occur during their life spans. Species that have ample intraspecific genetic differentiation, such as Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), are expected to display population-specific growth responses to climate change. Using a mixed-effects modeling approach,...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSED34A1682S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSED34A1682S"><span>Climate Adaptation Training for Natural Resource Professionals</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sorensen, H. L.; Meyer, N.</p> <p>2016-02-01</p> <p>The University of Minnesota Sea Grant Program and University of Minensota Extension are coordinating the development of a cohort-based training for natural resource professionals that prepares them with essential aptitude, resources and tools to lead climate adaptation activities in their organizations and municipalities. This course is geared toward the growing cadre of natural resources, water, municipal infrastructure, and human resources professionals who are called upon to lead climate adaptation initiatives but lack core training in climate change science, vulnerability assessment, and adaptation planning. Modeled on pre-existing UMN certificate programs, the online course encompasses approximately 40 contact hours of training. Content builds from basic climate mechanics to change science, vulnerability assessment, downscaled climate modeling, ecosystem response to climate change and strategies communicating climate change to diverse audiences. Minnesota as well as national case studies and expertise will anchor core climate adaptation concepts in a relevant context.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3492365','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3492365"><span>The Impact of Climate Change on Indigenous Arabica Coffee (Coffea arabica): Predicting Future Trends and Identifying Priorities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Gole, Tadesse Woldemariam; Baena, Susana</p> <p>2012-01-01</p> <p>Precise modelling of the influence of climate change on Arabica coffee is limited; there are no data available for indigenous populations of this species. In this study we model the present and future predicted distribution of indigenous Arabica, and identify priorities in order to facilitate appropriate decision making for conservation, monitoring and future research. Using distribution data we perform bioclimatic modelling and examine future distribution with the HadCM3 climate model for three emission scenarios (A1B, A2A, B2A) over three time intervals (2020, 2050, 2080). The models show a profoundly negative influence on indigenous Arabica. In a locality analysis the most favourable outcome is a c. 65% reduction in the number of pre-existing bioclimatically suitable localities, and at worst an almost 100% reduction, by 2080. In an area analysis the most favourable outcome is a 38% reduction in suitable bioclimatic space, and the least favourable a c. 90% reduction, by 2080. Based on known occurrences and ecological tolerances of Arabica, bioclimatic unsuitability would place populations in peril, leading to severe stress and a high risk of extinction. This study establishes a fundamental baseline for assessing the consequences of climate change on wild populations of Arabica coffee. Specifically, it: (1) identifies and categorizes localities and areas that are predicted to be under threat from climate change now and in the short- to medium-term (2020–2050), representing assessment priorities for ex situ conservation; (2) identifies ‘core localities’ that could have the potential to withstand climate change until at least 2080, and therefore serve as long-term in situ storehouses for coffee genetic resources; (3) provides the location and characterization of target locations (populations) for on-the-ground monitoring of climate change influence. Arabica coffee is confimed as a climate sensitivite species, supporting data and inference that existing plantations will be neagtively impacted by climate change. PMID:23144840</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC13G0832N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC13G0832N"><span>Modeling Malaria Vector Distribution under Climate Change Scenarios in Kenya</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ngaina, J. N.</p> <p>2017-12-01</p> <p>Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control strategies for sustaining elimination and preventing reintroduction of malaria. However, in Kenya, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of future climate change on locally dominant Anopheles vectors including Anopheles gambiae, Anopheles arabiensis, Anopheles merus, Anopheles funestus, Anopheles pharoensis and Anopheles nili. Environmental data (Climate, Land cover and elevation) and primary empirical geo-located species-presence data were identified. The principle of maximum entropy (Maxent) was used to model the species' potential distribution area under paleoclimate, current and future climates. The Maxent model was highly accurate with a statistically significant AUC value. Simulation-based estimates suggest that the environmentally suitable area (ESA) for Anopheles gambiae, An. arabiensis, An. funestus and An. pharoensis would increase under all two scenarios for mid-century (2016-2045), but decrease for end century (2071-2100). An increase in ESA of An. Funestus was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios for mid-century. Our findings can be applied in various ways such as the identification of additional localities where Anopheles malaria vectors may already exist, but has not yet been detected and the recognition of localities where it is likely to spread to. Moreover, it will help guide future sampling location decisions, help with the planning of vector control suites nationally and encourage broader research inquiry into vector species niche modeling</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040074253&hterms=Physical+Research+Study&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DPhysical%2BResearch%2BStudy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040074253&hterms=Physical+Research+Study&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3DPhysical%2BResearch%2BStudy"><span>The CEOP Inter-Monsoon Studies (CIMS)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lau, William K. M.</p> <p>2003-01-01</p> <p>Prediction of climate relies on models, and better model prediction depends on good model physics. Improving model physics requires the maximal utilization of climate data of the past, present and future. CEOP provides the first example of a comprehensive, integrated global and regional data set, consisting of globally gridded data, reference site in-situ observations, model location time series (MOLTS), and integrated satellite data for a two-year period covering two complete annual cycles of 2003-2004. The monsoon regions are the most important socio-economically in terms of devastation by floods and droughts, and potential impacts from climate change md fluctuatinns nf the hydrologic cyc!e. Scientifically, it is most challenging, because of complex interactions of atmosphere, land and oceans, local vs. remote forcings in contributing to climate variability and change in the region. Given that many common features, and physical teleconnection exist among different monsoon regions, an international research focus on monsoon must be coordinated and sustained. Current models of the monsoon are grossly inadequate for regional predictions. For improvement, models must be confronted with relevant observations, and model physic developers must be made to be aware of the wealth of information from existing climate data, field measurements, and satellite data that can be used to improve models. Model transferability studles must be conducted. CIMS is a major initiative under CEOP to engage the modeling and the observational communities to join in a coordinated effort to study the monsoons. The objectives of CIMS are (a) To provide a better understanding of fundamental physical processes (diurnal cycle, annual cycle, and intraseasonal oscillations) in monsoon regions around the world and (b) To demonstrate the synergy and utility of CEOP data in providing a pathway for model physics evaluation and improvement. In this talk, I will present the basic concepts of CIMS and the key scientific problems facing monsoon climates and provide examples of common monsoon features, and possible monsoon induced teleconnections linking different parts of the world.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150019930&hterms=biome&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dbiome','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150019930&hterms=biome&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dbiome"><span>Challenges in Quantifying Pliocene Terrestrial Warming Revealed by Data-Model Discord</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Salzmann, Ulrich; Dolan, Aisling M.; Haywood, Alan M.; Chan, Wing-Le; Voss, Jochen; Hill, Daniel J.; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Bragg, Frances J.; Chandler, Mark A.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20150019930'); toggleEditAbsImage('author_20150019930_show'); toggleEditAbsImage('author_20150019930_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20150019930_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20150019930_hide"></p> <p>2013-01-01</p> <p>Comparing simulations of key warm periods in Earth history with contemporaneous geological proxy data is a useful approach for evaluating the ability of climate models to simulate warm, high-CO2 climates that are unprecedented in the more recent past. Here we use a global data set of confidence-assessed, proxy-based temperature estimates and biome reconstructions to assess the ability of eight models to simulate warm terrestrial climates of the Pliocene epoch. The Late Pliocene, 3.6-2.6 million years ago, is an accessible geological interval to understand climate processes of a warmer world4. We show that model-predicted surface air temperatures reveal a substantial cold bias in the Northern Hemisphere. Particularly strong data-model mismatches in mean annual temperatures (up to 18 C) exist in northern Russia. Our model sensitivity tests identify insufficient temporal constraints hampering the accurate configuration of model boundary conditions as an important factor impacting on data- model discrepancies. We conclude that to allow a more robust evaluation of the ability of present climate models to predict warm climates, future Pliocene data-model comparison studies should focus on orbitally defined time slices.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=337351','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=337351"><span>Conceptualizing Holistic Community Resilience to Climate ...</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a></p> <p></p> <p></p> <p>The concept of resilience has been evolving over the past decade as a way to address the current and future challenges nations, states, and cities face from a changing climate. Understanding how the environment (natural and built), climate event risk, societal interactions, and governance reflect community resilience for adaptive management is critical for envisioning urban and natural environments that can persist through extreme weather events and longer-term shifts in climate. To be successful, this interaction of these five domains must result in maintaining quality of life and ensuring equal access to the benefits or the protection from harm for all segments of the population. An exhaustive literature review of climate resilience approaches was conducted examining the two primary elements of resilience—vulnerability and recoverability. The results of this review were examined to determine if any existing frameworks addressed the above five major areas in an integrated manner. While some aspects of a resilience model were available for existing sources, no comprehensive approach was available. A new conceptual model for resilience to climate events is proposed that incorporates some available structures and addresses these five domains at a national, regional, state, and county spatial scale for a variety of climate-induced events ranging from superstorms to droughts and their concomitant events such as wildfires, floods, and pest invasions. This conceptua</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1238786-future-warming-patterns-linked-todays-climate-variability','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1238786-future-warming-patterns-linked-todays-climate-variability"><span>Future warming patterns linked to today’s climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Dai, Aiguo</p> <p>2016-01-11</p> <p>The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1238786','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1238786"><span>Future warming patterns linked to today’s climate variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Dai, Aiguo</p> <p></p> <p>The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/132693','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/132693"><span>Clouds and ocean-atmosphere interactions. Final report, September 15, 1992--September 14, 1995</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Randall, D.A.; Jensen, T.G.</p> <p>1995-10-01</p> <p>Predictions of global change based on climate models are influencing both national and international policies on energy and the environment. Existing climate models show some skill in simulating the present climate, but suffer from many widely acknowledged deficiencies. Among the most serious problems is the need to apply ``flux corrections`` to prevent the models from drifting away from the observed climate in control runs that do not include external perturbing influences such as increased carbon dioxide (CO{sub 2}) concentrations. The flux corrections required to prevent climate drift are typically comparable in magnitude to the observed fluxes themselves. Although there canmore » be many contributing reasons for the climate drift problem, clouds and their effects on the surface energy budget are among the prime suspects. The authors have conducted a research program designed to investigate global air-sea interaction as it relates to the global warming problem, with special emphasis on the role of clouds. Their research includes model development efforts; application of models to simulation of present and future climates, with comparison to observations wherever possible; and vigorous participation in ongoing efforts to intercompare the present generation of atmospheric general circulation models.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70034923','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70034923"><span>Near term climate projections for invasive species distributions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Jarnevich, C.S.; Stohlgren, T.J.</p> <p>2009-01-01</p> <p>Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_1");'>1</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li class="active"><span>3</span></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_3 --> <div id="page_4" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="61"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AtmEn..75..321K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AtmEn..75..321K"><span>Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.</p> <p>2013-08-01</p> <p>This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22..287M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22..287M"><span>Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul</p> <p>2018-01-01</p> <p>Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8533E..0RH','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8533E..0RH"><span>Invitation to a forum: architecting operational `next generation' earth monitoring satellites based on best modeling, existing sensor capabilities, with constellation efficiencies to secure trusted datasets for the next 20 years</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Helmuth, Douglas B.; Bell, Raymond M.; Grant, David A.; Lentz, Christopher A.</p> <p>2012-09-01</p> <p>Architecting the operational Next Generation of earth monitoring satellites based on matured climate modeling, reuse of existing sensor & satellite capabilities, attention to affordability and evolutionary improvements integrated with constellation efficiencies - becomes our collective goal for an open architectural design forum. Understanding the earth's climate and collecting requisite signatures over the next 30 years is a shared mandate by many of the world's governments. But there remains a daunting challenge to bridge scientific missions to 'operational' systems that truly support the demands of decision makers, scientific investigators and global users' requirements for trusted data. In this paper we will suggest an architectural structure that takes advantage of current earth modeling examples including cross-model verification and a first order set of critical climate parameters and metrics; that in turn, are matched up with existing space borne collection capabilities and sensors. The tools used and the frameworks offered are designed to allow collaborative overlays by other stakeholders nominating different critical parameters and their own treaded connections to existing international collection experience. These aggregate design suggestions will be held up to group review and prioritized as potential constellation solutions including incremental and spiral developments - including cost benefits and organizational opportunities. This Part IV effort is focused on being an inclusive 'Next Gen Constellation' design discussion and is the natural extension to earlier papers.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002JHyd..264..230H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002JHyd..264..230H"><span>Susceptibility of the Batoka Gorge hydroelectric scheme to climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Harrison, Gareth P.; Whittington, H.(Bert) W.</p> <p>2002-07-01</p> <p>The continuing and increased use of renewable energy sources, including hydropower, is a key strategy to limit the extent of future climate change. Paradoxically, climate change itself may alter the availability of this natural resource, adversely affecting the financial viability of both existing and potential schemes. Here, a model is described that enables the assessment of the relationship between changes in climate and the viability, technical and financial, of hydro development. The planned Batoka Gorge scheme on the Zambezi River is used as a case study to validate the model and to predict the impact of climate change on river flows, electricity production and scheme financial performance. The model was found to perform well, given the inherent difficulties in the task, although there is concern regarding the ability of the hydrological model to reproduce the historic flow conditions of the upper Zambezi Basin. Simulations with climate change scenarios illustrate the sensitivity of the Batoka Gorge scheme to changes in climate. They suggest significant reductions in river flows, declining power production, reductions in electricity sales revenue and consequently an adverse impact on a range of investment measures.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70035536','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70035536"><span>Adaptation of farming practices could buffer effects of climate change on northern prairie wetlands</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Voldseth, R.A.; Johnson, W.C.; Guntenspergen, G.R.; Gilmanov, T.; Millett, B.V.</p> <p>2009-01-01</p> <p>Wetlands of the Prairie Pothole Region of North America are vulnerable to climate change. Adaptation of farming practices to mitigate adverse impacts of climate change on wetland water levels is a potential watershed management option. We chose a modeling approach (WETSIM 3.2) to examine the effects of changes in climate and watershed cover on the water levels of a semi-permanent wetland in eastern South Dakota. Land-use practices simulated were unmanaged grassland, grassland managed with moderately heavy grazing, and cultivated crops. Climate scenarios were developed by adjusting the historical climate in combinations of 2??C and 4??C air temperature and ??10% precipitation. For these climate change scenarios, simulations of land use that produced water levels equal to or greater than unmanaged grassland under historical climate were judged to have mitigative potential against a drier climate. Water levels in wetlands surrounded by managed grasslands were significantly greater than those surrounded by unmanaged grassland. Management reduced both the proportion of years the wetland went dry and the frequency of dry periods, producing the most dynamic vegetation cycle for this modeled wetland. Both cultivated crops and managed grassland achieved water levels that were equal or greater than unmanaged grassland under historical climate for the 2??C rise in air temperature, and the 2??C rise plus 10% increase in precipitation scenarios. Managed grassland also produced water levels that were equal or greater than unmanaged grassland under historical climate for the 4??C rise plus 10% increase in precipitation scenario. Although these modeling results stand as hypotheses, they indicate that amelioration potential exists for a change in climate up to an increase of 2??C or 4??C with a concomitant 10% increase in precipitation. Few empirical data exist to verify the results of such land-use simulations; however, adaptation of farming practices is one possible mitigation avenue available for prairie wetlands. ?? 2009, The Society of Wetland Scientists.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/46576','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/46576"><span>Evidence-based planning for forest adaptation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Lee Hannah; Thomas E. Lovejoy</p> <p>2014-01-01</p> <p>Forest conservation under climate change requires conserving species both in their present ranges and where they may exist in the future as climate changes. Several debates in the literature are pioneering this relatively novel ground. For instance, conservation planning using species distribution models is advocated because it uses information on both exposure to...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150021875','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150021875"><span>ISMIP6: Ice Sheet Model Intercomparison Project for CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nowicki, S.</p> <p>2015-01-01</p> <p>ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6) targets the Cryosphere in a Changing Climate and the Future Sea Level Grand Challenges of the WCRP (World Climate Research Program). Primary goal is to provide future sea level contribution from the Greenland and Antarctic ice sheets, along with associated uncertainty. Secondary goal is to investigate feedback due to dynamic ice sheet models. Experiment design uses and augment the existing CMIP6 (Coupled Model Intercomparison Project Phase 6) DECK (Diagnosis, Evaluation, and Characterization of Klima) experiments. Additonal MIP (Model Intercomparison Project)- specific experiments will be designed for ISM (Ice Sheet Model). Effort builds on the Ice2sea, SeaRISE (Sea-level Response to Ice Sheet Evolution) and COMBINE (Comprehensive Modelling of the Earth System for Better Climate Prediction and Projection) efforts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.1719L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.1719L"><span>The epistemological status of general circulation models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Loehle, Craig</p> <p>2018-03-01</p> <p>Forecasts of both likely anthropogenic effects on climate and consequent effects on nature and society are based on large, complex software tools called general circulation models (GCMs). Forecasts generated by GCMs have been used extensively in policy decisions related to climate change. However, the relation between underlying physical theories and results produced by GCMs is unclear. In the case of GCMs, many discretizations and approximations are made, and simulating Earth system processes is far from simple and currently leads to some results with unknown energy balance implications. Statistical testing of GCM forecasts for degree of agreement with data would facilitate assessment of fitness for use. If model results need to be put on an anomaly basis due to model bias, then both visual and quantitative measures of model fit depend strongly on the reference period used for normalization, making testing problematic. Epistemology is here applied to problems of statistical inference during testing, the relationship between the underlying physics and the models, the epistemic meaning of ensemble statistics, problems of spatial and temporal scale, the existence or not of an unforced null for climate fluctuations, the meaning of existing uncertainty estimates, and other issues. Rigorous reasoning entails carefully quantifying levels of uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23D2377A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23D2377A"><span>Impact of Climate Change on Irrigation and Hydropower Potential: A Case of Upper Blue Nile Basin</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Abdella, E. J.; Gosain, A. K.; Khosa, R.</p> <p>2017-12-01</p> <p>Due to the growing pressure in water resource and climate change there is great uncertainty in the availability of water for existing as well as proposed irrigation and hydropower projects in the Upper Blue Nile basin (longitude 34oE and 39oE and latitude 7oN and 12oN). This study quantitatively assessed the impact of climate change on the hydrological regime of the basin which intern affect water availability for different use including hydropower and irrigation. Ensemble of four bias corrected regional climate models (RCM) of CORDEX Africa domain and two scenarios (RCP 4.5 and RCP 8.5) were used to determine climate projections for future (2021-2050) period. The outputs from the climate models used to drive the calibrated Soil and Water Assessment Tool (SWAT) hydrologic model to simulate future runoff. The simulated discharge were used as input to a Water Evaluation and Planning (WEAP) water allocation model to determine the implication in hydropower and irrigation potential of the basin. The WEAP model was setup to simulate three scenarios which includes Current, Medium-term (by 2025) and Long-term (by 2050) Development scenario. The projected mean annual temperature of the basin are warmer than the baseline (1982 - 2005) average in the range of 1 to 1.4oC. Projected mean annual precipitation varies across the basin in the range of - 3% to 7%, much of the expected increase is in the highland region of the basin. The water use simulation indicate that the current annual average irrigation water demand in the basin is 1.29Bm3y-1 with 100% coverage. By 2025 and 2050, with the development of new schemes and changing climate, water demand for irrigation is estimated to increase by 2.5 Bm3y-1 and 3.4 Bm3y-1 with 99 % and 96% coverage respectively. Simulation for domestic water demand coverage for all scenarios shows that there will be 100% coverage for the two major cities in the basin. The hydropower generation simulation indicate that 98% of hydroelectricity potential could be produced if all planed dams are constructed. The results in this study demonstrate the general idea of future water availability for different purpose in the basin, but uncertainties still exist in the projected future climate and simulated runoff. Optimal operation of existing and proposed reservoirs is also crucial in the context of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.2771B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.2771B"><span>Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boé, Julien</p> <p>2018-03-01</p> <p>Multimodel ensembles are the main way to deal with model uncertainties in climate projections. However, the interdependencies between models that often share entire components make it difficult to combine their results in a satisfactory way. In this study, how the replication of components (atmosphere, ocean, land, and sea ice) between climate models impacts the proximity of their results is quantified precisely, in terms of climatological means and future changes. A clear relationship exists between the number of components shared by climate models and the proximity of their results. Even the impact of a single shared component is generally visible. These conclusions are true at both the global and regional scales. Given available data, it cannot be robustly concluded that some components are more important than others. Those results provide ways to estimate model interdependencies a priori rather than a posteriori based on their results, in order to define independence weights.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GPC...158...72N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GPC...158...72N"><span>Significance of direct and indirect impacts of climate change on groundwater resources in the Olifants River basin: A review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nkhonjera, German K.; Dinka, Megersa O.</p> <p>2017-11-01</p> <p>This paper considers the extent and usefulness of reviewing existing literature on the significance of direct and indirect impacts of climate change on groundwater resources with emphasis on examples from the Olifants River basin. Here, the existing literature were extensively reviewed, with discussions centred mainly on the impacts of climate change on groundwater resources and challenges in modelling climate change impacts on groundwater resources. Since in the hydrological cycle, the hydrological components such as evaporation, temperature, precipitation, and groundwater, are the major drivers of the present and future climate, a detailed discussion is done on the impact of climate change on these hydrological components to determine to what extent the hydrological cycle has already been affected as a result of climate change. The uncertainties, constraints and limitations in climate change research have also been reviewed. In addition to the research gaps discussed here, the emphasis on the need of extensive climate change research on the continent, especially as climate change impacts on groundwater, is discussed. Overall, the importance of conducting further research in climate change, understanding the significance of the impact of climate change on water resources such as groundwater, and taking actions to effectively meet the adaptation needs of the people, emerge as an important theme in this review.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017FrEaS...5..105M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017FrEaS...5..105M"><span>Permafrost Favourability Index: Spatial modelling in the French Alps using a Rock Glacier Inventory</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marcer, Marco; Bodin, Xavier; Brenning, Alexander; Schoeneich, Philippe; Charvet, Raphaële; Gottardi, Frédéric</p> <p>2017-12-01</p> <p>In the present study we used the first rock glacier inventory for the entire French Alps to model spatial permafrost distribution in the region. The inventory, which does not originally belong to this study, was revised by the authors in order to obtain a database suitable for statistical modelling. Climatic and topographic data evaluated at the rock glacier locations were used as predictor variables in a Generalized Linear Model. Model performances are strong, suggesting that, in agreement with several previous studies, this methodology is able to model accurately rock glacier distribution. A methodology to estimate model uncertainties is proposed, revealing that the subjectivity in the interpretation of rock glacier activity and contours may substantially bias the model. The model highlights a North-South trend in the regional pattern of permafrost distribution which is attributed to the climatic influences of the Atlantic and Mediterranean climates. Further analysis suggest that lower amounts of precipitation in the early winter and a thinner snow cover, as typically found in the Mediterranean area, could contribute to the existence of permafrost at higher temperatures compared to the Northern Alps. A comparison with the Alpine Permafrost Index Map (APIM) shows no major differences with our model, highlighting the very good predictive power of the APIM despite its tendency to slightly overestimate permafrost extension with respect to our database. The use of rock glaciers as indicators of permafrost existence despite their time response to climate change is discussed and an interpretation key is proposed in order to ensure the proper use of the model for research as well as for operational purposes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1711175B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1711175B"><span>Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier</p> <p>2015-04-01</p> <p>At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H13C1223R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H13C1223R"><span>Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ranatunga, T.; Tong, S.; Yang, J.</p> <p>2011-12-01</p> <p>Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24979763','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24979763"><span>Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi</p> <p>2014-07-01</p> <p>Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA12A..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA12A..04S"><span>Translating climate data for business decisions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Steinberg, N.</p> <p>2015-12-01</p> <p>Businesses are bound to play an integral role in global and local climate change adaptation efforts, and integrating climate science into business decision-making can help protect companies' bottom-line and the communities which they depend upon. Yet many companies do not have good means to measure and manage climate risks. There are inherent limiting factors to incorporating climate data into existing operations and sourcing strategies. Spatial and temporal incongruities between climate and business models can make integration cumbersome. Even when such incongruities are resolved, raw climate data must undergo multiple transformations until the data is deemed actionable or otherwise translatable in dollar terms. However, the predictability of future impacts is advancing along with the use of second-order variables such as Cooling Degree Days and Water-Limited Crop productivity, helping business managers make better decisions about future energy and water demand requirements under the prospect of rising temperatures and more variable rainfall. This presentation will discuss the methods and opportunities for transforming raw climate data into business metrics. Results for the 2015 Corporate Adaptation Survey, led by Four Twenty Seven and in partnership with Notre Dame Global Adaptation Index, will also be presented to illustrate existing gaps between climate science and its application in the business context.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRE..121..965O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRE..121..965O"><span>Radiative transfer in CO2-rich atmospheres: 1. Collisional line mixing implies a colder early Mars</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ozak, N.; Aharonson, O.; Halevy, I.</p> <p>2016-06-01</p> <p>Fast and accurate radiative transfer methods are essential for modeling CO2-rich atmospheres, relevant to the climate of early Earth and Mars, present-day Venus, and some exoplanets. Although such models already exist, their accuracy may be improved as better theoretical and experimental constraints become available. Here we develop a unidimensional radiative transfer code for CO2-rich atmospheres, using the correlated k approach and with a focus on modeling early Mars. Our model differs from existing models in that it includes the effects of CO2 collisional line mixing in the calculation of the line-by-line absorption coefficients. Inclusion of these effects results in model atmospheres that are more transparent to infrared radiation and, therefore, in colder surface temperatures at radiative-convective equilibrium, compared with results of previous studies. Inclusion of water vapor in the model atmosphere results in negligible warming due to the low atmospheric temperatures under a weaker early Sun, which translate into climatically unimportant concentrations of water vapor. Overall, the results imply that sustained warmth on early Mars would not have been possible with an atmosphere containing only CO2 and water vapor, suggesting that other components of the early Martian climate system are missing from current models or that warm conditions were not long lived.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/889817','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/889817"><span>Predicting Coupled Ocean-Atmosphere Modes with a Climate Modeling Hierarchy -- Final Report</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Michael Ghil, UCLA; Andrew W. Robertson, IRI, Columbia Univ.; Sergey Kravtsov, U. of Wisconsin, Milwaukee</p> <p></p> <p>The goal of the project was to determine midlatitude climate predictability associated with tropical-extratropical interactions on interannual-to-interdecadal time scales. Our strategy was to develop and test a hierarchy of climate models, bringing together large GCM-based climate models with simple fluid-dynamical coupled ocean-ice-atmosphere models, through the use of advanced probabilistic network (PN) models. PN models were used to develop a new diagnostic methodology for analyzing coupled ocean-atmosphere interactions in large climate simulations made with the NCAR Parallel Climate Model (PCM), and to make these tools user-friendly and available to other researchers. We focused on interactions between the tropics and extratropics throughmore » atmospheric teleconnections (the Hadley cell, Rossby waves and nonlinear circulation regimes) over both the North Atlantic and North Pacific, and the ocean’s thermohaline circulation (THC) in the Atlantic. We tested the hypothesis that variations in the strength of the THC alter sea surface temperatures in the tropical Atlantic, and that the latter influence the atmosphere in high latitudes through an atmospheric teleconnection, feeding back onto the THC. The PN model framework was used to mediate between the understanding gained with simplified primitive equations models and multi-century simulations made with the PCM. The project team is interdisciplinary and built on an existing synergy between atmospheric and ocean scientists at UCLA, computer scientists at UCI, and climate researchers at the IRI.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27048926','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27048926"><span>A Circular Bioeconomy with Biobased Products from CO2 Sequestration.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Venkata Mohan, S; Modestra, J Annie; Amulya, K; Butti, Sai Kishore; Velvizhi, G</p> <p>2016-06-01</p> <p>The unprecedented climate change influenced by elevated concentrations of CO2 has compelled the research world to focus on CO2 sequestration. Although existing natural and anthropogenic CO2 sinks have proven valuable, their ability to further assimilate CO2 is now questioned. Thus, we highlight here the importance of biological sequestration methods as alternate and viable routes for mitigating climate change while simultaneously synthesizing value-added products that could sustainably fuel the circular bioeconomy. Four conceptual models for CO2 biosequestration and the synthesis of biobased products, as well as an integrated CO2 biorefinery model, are proposed. Optimizing and implementing this biorefinery model might overcome the limitations of existing sequestration methods and could help realign the carbon balance. Copyright © 2016 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27835976','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27835976"><span>An integrated risk and vulnerability assessment framework for climate change and malaria transmission in East Africa.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Onyango, Esther Achieng; Sahin, Oz; Awiti, Alex; Chu, Cordia; Mackey, Brendan</p> <p>2016-11-11</p> <p>Malaria is one of the key research concerns in climate change-health relationships. Numerous risk assessments and modelling studies provide evidence that the transmission range of malaria will expand with rising temperatures, adversely impacting on vulnerable communities in the East African highlands. While there exist multiple lines of evidence for the influence of climate change on malaria transmission, there is insufficient understanding of the complex and interdependent factors that determine the risk and vulnerability of human populations at the community level. Moreover, existing studies have had limited focus on the nature of the impacts on vulnerable communities or how well they are prepared to cope. In order to address these gaps, a systems approach was used to present an integrated risk and vulnerability assessment framework for studies of community level risk and vulnerability to malaria due to climate change. Drawing upon published literature on existing frameworks, a systems approach was applied to characterize the factors influencing the interactions between climate change and malaria transmission. This involved structural analysis to determine influential, relay, dependent and autonomous variables in order to construct a detailed causal loop conceptual model that illustrates the relationships among key variables. An integrated assessment framework that considers indicators of both biophysical and social vulnerability was proposed based on the conceptual model. A major conclusion was that this integrated assessment framework can be implemented using Bayesian Belief Networks, and applied at a community level using both quantitative and qualitative methods with stakeholder engagement. The approach enables a robust assessment of community level risk and vulnerability to malaria, along with contextually relevant and targeted adaptation strategies for dealing with malaria transmission that incorporate both scientific and community perspectives.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_2");'>2</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li class="active"><span>4</span></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_4 --> <div id="page_5" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="81"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70019631','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70019631"><span>Climatic controls of western U.S. glaciers at the last glacial maximum</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hostetler, S.W.; Clark, P.U.</p> <p>1997-01-01</p> <p>We use a nested atmospheric modeling strategy to simulate precipitation and temperature of the western United States 18,000 years ago (18 ka). The high resolution of the nested model allows us to isolate the regional structure of summer temperature and winter precipitation that is crucial to determination of the net mass balance of late-Pleistocene mountain glaciers in this region of diverse topography and climate. Modeling results suggest that climatic controls of these glaciers varied significantly over the western U.S. Glaciers in the northern Rocky Mountains existed under relatively cold July temperatures and low winter accumulation, reflecting anticyclonic, easterly wind flow off the Laurentide Ice Sheet. In contrast, glaciers that existed under relatively warmer and wetter conditions are located along the Pacific coast south of Oregon, where enhanced westerlies delivered higher precipitation than at present. Between these two groupings lie glaciers that were controlled by a mix of cold and wet conditions attributed to the convergence of cold air from the ice sheet and moisture derived from the westerlies. Sensitivity tests suggest that, for our simulated 18 ka climate, many of the glaciers exhibit a variable response to climate but were generally more sensitive to changes in temperature than to changes in precipitation, particularly those glaciers in central Idaho and the Yellowstone Plateau. Our results support arguments that temperature depression generally played a larger role in lowering equilibrium line altitudes in the western U.S. during the last glacial maximum than did increased precipitation, although the magnitude of temperature depression required for steady-state mass balance varied from 8-18??C. Only the Sierra Nevada glaciers required a substantial increase in precipitation to achieve steady-state mass balance, while glaciers in the Cascade Range existed with decreased precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1266397-new-test-statistic-climate-models-includes-field-spatial-dependencies-using-gaussian-markov-random-fields','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1266397-new-test-statistic-climate-models-includes-field-spatial-dependencies-using-gaussian-markov-random-fields"><span>A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel</p> <p>2016-07-20</p> <p>A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005GPC....47..273W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005GPC....47..273W"><span>Mitigation of climate change impacts on raptors by behavioural adaptation: ecological buffering mechanisms</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wichmann, Matthias C.; Groeneveld, Jürgen; Jeltsch, Florian; Grimm, Volker</p> <p>2005-07-01</p> <p>The predicted climate change causes deep concerns on the effects of increasing temperatures and changing precipitation patterns on species viability and, in turn, on biodiversity. Models of Population Viability Analysis (PVA) provide a powerful tool to assess the risk of species extinction. However, most PVA models do not take into account the potential effects of behavioural adaptations. Organisms might adapt to new environmental situations and thereby mitigate negative effects of climate change. To demonstrate such mitigation effects, we use an existing PVA model describing a population of the tawny eagle ( Aquila rapax) in the southern Kalahari. This model does not include behavioural adaptations. We develop a new model by assuming that the birds enlarge their average territory size to compensate for lower amounts of precipitation. Here, we found the predicted increase in risk of extinction due to climate change to be much lower than in the original model. However, this "buffering" of climate change by behavioural adaptation is not very effective in coping with increasing interannual variances. We refer to further examples of ecological "buffering mechanisms" from the literature and argue that possible buffering mechanisms should be given due consideration when the effects of climate change on biodiversity are to be predicted.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1266397-new-test-statistic-climate-models-includes-field-spatial-dependencies-using-gaussian-markov-random-fields','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1266397-new-test-statistic-climate-models-includes-field-spatial-dependencies-using-gaussian-markov-random-fields"><span>A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel</p> <p></p> <p>A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23708470','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23708470"><span>Cross-validation of an employee safety climate model in Malaysia.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bahari, Siti Fatimah; Clarke, Sharon</p> <p>2013-06-01</p> <p>Whilst substantial research has investigated the nature of safety climate, and its importance as a leading indicator of organisational safety, much of this research has been conducted with Western industrial samples. The current study focuses on the cross-validation of a safety climate model in the non-Western industrial context of Malaysian manufacturing. The first-order factorial validity of Cheyne et al.'s (1998) [Cheyne, A., Cox, S., Oliver, A., Tomas, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work and Stress, 12(3), 255-271] model was tested, using confirmatory factor analysis, in a Malaysian sample. Results showed that the model fit indices were below accepted levels, indicating that the original Cheyne et al. (1998) safety climate model was not supported. An alternative three-factor model was developed using exploratory factor analysis. Although these findings are not consistent with previously reported cross-validation studies, we argue that previous studies have focused on validation across Western samples, and that the current study demonstrates the need to take account of cultural factors in the development of safety climate models intended for use in non-Western contexts. The results have important implications for the transferability of existing safety climate models across cultures (for example, in global organisations) and highlight the need for future research to examine cross-cultural issues in relation to safety climate. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC33F..02Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC33F..02Y"><span>Integrated modeling for assessment of energy-water system resilience under changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yan, E.; Veselka, T.; Zhou, Z.; Koritarov, V.; Mahalik, M.; Qiu, F.; Mahat, V.; Betrie, G.; Clark, C.</p> <p>2016-12-01</p> <p>Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. The IWESAF currently includes an extreme climate event generator to predict future extreme weather events, hydrologic and reservoir models, riverine temperature model, power plant water use simulator, and power grid operation and cost optimization model. The IWESAF can facilitate the interaction among the modeling systems and provide insights of the sustainability and resilience of the energy-water system under extreme climate events and economic consequence. The regional case demonstration in the Midwest region will be presented. The detailed information on some of individual modeling components will also be presented in several other abstracts submitted to AGU this year.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMNH31C..07Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMNH31C..07Y"><span>Simulating malaria transmission in the current and future climate of West Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yamana, T. K.; Bomblies, A.; Eltahir, E. A. B.</p> <p>2015-12-01</p> <p>Malaria transmission in West Africa is closely tied to climate, as rain fed water pools provide breeding habitat for the anopheles mosquito vector, and temperature affects the mosquito's ability to spread disease. We present results of a highly detailed, spatially explicit mechanistic modelling study exploring the relationships between the environment and malaria in the current and future climate of West Africa. A mechanistic model of human immunity was incorporated into an existing agent-based model of malaria transmission, allowing us to move beyond entomological measures such as mosquito density and vectorial capacity to analyzing the prevalence of the malaria parasite within human populations. The result is a novel modelling tool that mechanistically simulates all of the key processes linking environment to malaria transmission. Simulations were conducted across climate zones in West Africa, linking temperature and rainfall to entomological and epidemiological variables with a focus on nonlinearities due to threshold effects and interannual variability. Comparisons to observations from the region confirmed that the model provides a reasonable representation of the entomological and epidemiological conditions in this region. We used the predictions of future climate from the most credible CMIP5 climate models to predict the change in frequency and severity of malaria epidemics in West Africa as a result of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29800841','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29800841"><span>Potential land use adjustment for future climate change adaptation in revegetated regions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Peng, Shouzhang; Li, Zhi</p> <p>2018-05-22</p> <p>To adapt to future climate change, appropriate land use patterns are desired. Potential natural vegetation (PNV) emphasizing the dominant role of climate can provide a useful baseline to guide the potential land use adjustment. This work is particularly important for the revegetated regions with intensive human perturbation. However, it has received little attention. This study chose China's Loess Plateau, a typical revegetated region, as an example study area to generate the PNV patterns with high spatial resolution over 2071-2100 with a process-based dynamic vegetation model (LPJ-GUESS), and further investigated the potential land use adjustment through comparing the simulated and observed land use patterns. Compared with 1981-2010, the projected PNV over 2071-2100 would have less forest and more steppe because of drier climate. Subsequently, 25.3-55.0% of the observed forests and 79.3-91.9% of the observed grasslands in 2010 can be kept over 2071-2100, and the rest of the existing forested area and grassland were expected to be more suitable for steppes and forests, respectively. To meet the request of China's Grain for Green Project, 60.9-84.8% of the existing steep farmland could be converted to grassland and the other for forest. Our results highlight the importance in adjusting the existing vegetation pattern to adapt to climate change. The research approach is extendable and provides a framework to evaluate the sustainability of the existing land use pattern under future climate. Copyright © 2018 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=307754','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=307754"><span>Validation of non-stationary precipitation series for site-specific impact assessment: Comparison of two statistical downscaling techniques</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The generation of realistic future precipitation scenarios is crucial for assessing their impacts on a range of environmental and socio-economic impact sectors. A scale mismatch exists, however, between the coarse spatial resolution at which global climate models (GCMs) output future climate scenari...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26438283','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26438283"><span>Weighting climate model projections using observational constraints.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gillett, Nathan P</p> <p>2015-11-13</p> <p>Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050175952','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050175952"><span>Outflow Channels Influencing Martian Climate: Global Circulation Model Simulations with Emplaced Water</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Santiago, D. L.; Colaprete, A.; Haberle, R. M.; Sloan, L. C.; Asphaug, E. I.</p> <p>2005-01-01</p> <p>The existence of surface water on Mars in past geologic epochs is inferred on the basis of geomorphologic interpretation of spaceflight images, and is supported by the recent Mars Odyssey identification of ice-rich soils [1]. The Mars Exploration Rovers have provided further chemical evidence for past surface hydrologic activity [2]. One issue is whether this water-rich climate ever existed in a steady state, or whether it was triggered by catastrophic events such as large impacts [3], and/ or catastrophic outburst floods, the topic of consideration here.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMIN23C1095W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMIN23C1095W"><span>A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wehner, M. F.; Oliker, L.; Shalf, J.</p> <p>2008-12-01</p> <p>Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1997Natur.385..804O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1997Natur.385..804O"><span>Vegetation-induced warming of high-latitude regions during the Late Cretaceous period</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Otto-Bliesner, Bette L.; Upchurch, Garland R.</p> <p>1997-02-01</p> <p>Modelling studies of pre-Quaternary (>2 million years ago) climate implicate atmospheric carbon dioxide concentrations1, land elevation2 and land-sea distribution3-5 as important factors influencing global climate change over geological timescales. But during times of global warmth, such as the Cretaceous period and Eocene epoch, there are large discrepancies between model simulations of high-latitude and continental-interior temperatures and those indicated by palaeotemperature records6,7. Here we use a global climate model for the latest Cretaceous (66 million years ago) to examine the role played by high- and middle-latitude forests in surface temperature regulation. In our simulations, this forest vegetation warms the global climate by 2.2 °C. The low-albedo deciduous forests cause high-latitude land areas to warm, which then transfer more heat to adjacent oceans, thus delaying sea-ice formation and increasing winter temperatures over coastal land. Overall, the inclusion of some of the physical and physiological climate feedback effects of high-latitude forest vegetation in our simulations reduces the existing discrepancies between observed and modelled climates of the latest Cretaceous, suggesting that these forests may have made an important contribution to climate regulation during periods of global warmth.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4810853','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4810853"><span>Controlled comparison of species- and community-level models across novel climates and communities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Maguire, Kaitlin C.; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.; Ferrier, Simon; Lorenz, David J.</p> <p>2016-01-01</p> <p>Species distribution models (SDMs) assume species exist in isolation and do not influence one another's distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa. PMID:26962143</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED21A0266R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED21A0266R"><span>A computational approach to climate science education with CLIMLAB</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rose, B. E. J.</p> <p>2017-12-01</p> <p>CLIMLAB is a Python-based software toolkit for interactive, process-oriented climate modeling for use in education and research. It is motivated by the need for simpler tools and more reproducible workflows with which to "fill in the gaps" between blackboard-level theory and the results of comprehensive climate models. With CLIMLAB you can interactively mix and match physical model components, or combine simpler process models together into a more comprehensive model. I use CLIMLAB in the classroom to put models in the hands of students (undergraduate and graduate), and emphasize a hierarchical, process-oriented approach to understanding the key emergent properties of the climate system. CLIMLAB is equally a tool for climate research, where the same needs exist for more robust, process-based understanding and reproducible computational results. I will give an overview of CLIMLAB and an update on recent developments, including: a full-featured, well-documented, interactive implementation of a widely-used radiation model (RRTM) packaging with conda-forge for compiler-free (and hassle-free!) installation on Mac, Windows and Linux interfacing with xarray for i/o and graphics with gridded model data a rich and growing collection of examples and self-computing lecture notes in Jupyter notebook format</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC11A0884F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC11A0884F"><span>Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Field, R.; Constantine, P.; Boslough, M.</p> <p>2011-12-01</p> <p>We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We applied the calibrated surrogate model to study the probability that the precipitation rate falls below certain thresholds and utilized the Bayesian approach to quantify our confidence in these predictions. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1376180-arm-cloud-radar-simulator-global-climate-models-new-tool-bridging-field-data-climate-models','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1376180-arm-cloud-radar-simulator-global-climate-models-new-tool-bridging-field-data-climate-models"><span>The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.; ...</p> <p>2017-08-11</p> <p>Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1376180','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1376180"><span>The ARM Cloud Radar Simulator for Global Climate Models: A New Tool for Bridging Field Data and Climate Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.</p> <p></p> <p>Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept ofmore » instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to facilitate and to improve the comparison of modeled clouds with observations. Many simulators have been (and continue to be) developed for a variety of instruments and purposes. Finally, a community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Kay et al. 2012; Klein et al. 2013; Suzuki et al. 2013; Zhang et al. 2010).« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JAMES...8.1358X','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JAMES...8.1358X"><span>Calibration-induced uncertainty of the EPIC model to estimate climate change impact on global maize yield</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Xiong, Wei; Skalský, Rastislav; Porter, Cheryl H.; Balkovič, Juraj; Jones, James W.; Yang, Di</p> <p>2016-09-01</p> <p>Understanding the interactions between agricultural production and climate is necessary for sound decision-making in climate policy. Gridded and high-resolution crop simulation has emerged as a useful tool for building this understanding. Large uncertainty exists in this utilization, obstructing its capacity as a tool to devise adaptation strategies. Increasing focus has been given to sources of uncertainties for climate scenarios, input-data, and model, but uncertainties due to model parameter or calibration are still unknown. Here, we use publicly available geographical data sets as input to the Environmental Policy Integrated Climate model (EPIC) for simulating global-gridded maize yield. Impacts of climate change are assessed up to the year 2099 under a climate scenario generated by HadEM2-ES under RCP 8.5. We apply five strategies by shifting one specific parameter in each simulation to calibrate the model and understand the effects of calibration. Regionalizing crop phenology or harvest index appears effective to calibrate the model for the globe, but using various values of phenology generates pronounced difference in estimated climate impact. However, projected impacts of climate change on global maize production are consistently negative regardless of the parameter being adjusted. Different values of model parameter result in a modest uncertainty at global level, with difference of the global yield change less than 30% by the 2080s. The uncertainty subjects to decrease if applying model calibration or input data quality control. Calibration has a larger effect at local scales, implying the possible types and locations for adaptation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1327127-uncertainty-quantification-climate-modeling-projection','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1327127-uncertainty-quantification-climate-modeling-projection"><span>Uncertainty Quantification in Climate Modeling and Projection</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Qian, Yun; Jackson, Charles; Giorgi, Filippo</p> <p></p> <p>The projection of future climate is one of the most complex problems undertaken by the scientific community. Although scientists have been striving to better understand the physical basis of the climate system and to improve climate models, the overall uncertainty in projections of future climate has not been significantly reduced (e.g., from the IPCC AR4 to AR5). With the rapid increase of complexity in Earth system models, reducing uncertainties in climate projections becomes extremely challenging. Since uncertainties always exist in climate models, interpreting the strengths and limitations of future climate projections is key to evaluating risks, and climate change informationmore » for use in Vulnerability, Impact, and Adaptation (VIA) studies should be provided with both well-characterized and well-quantified uncertainty. The workshop aimed at providing participants, many of them from developing countries, information on strategies to quantify the uncertainty in climate model projections and assess the reliability of climate change information for decision-making. The program included a mixture of lectures on fundamental concepts in Bayesian inference and sampling, applications, and hands-on computer laboratory exercises employing software packages for Bayesian inference, Markov Chain Monte Carlo methods, and global sensitivity analyses. The lectures covered a range of scientific issues underlying the evaluation of uncertainties in climate projections, such as the effects of uncertain initial and boundary conditions, uncertain physics, and limitations of observational records. Progress in quantitatively estimating uncertainties in hydrologic, land surface, and atmospheric models at both regional and global scales was also reviewed. The application of Uncertainty Quantification (UQ) concepts to coupled climate system models is still in its infancy. The Coupled Model Intercomparison Project (CMIP) multi-model ensemble currently represents the primary data for assessing reliability and uncertainties of climate change information. An alternative approach is to generate similar ensembles by perturbing parameters within a single-model framework. One of workshop’s objectives was to give participants a deeper understanding of these approaches within a Bayesian statistical framework. However, there remain significant challenges still to be resolved before UQ can be applied in a convincing way to climate models and their projections.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_3");'>3</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li class="active"><span>5</span></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_5 --> <div id="page_6" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="101"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC14C..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC14C..06A"><span>Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.</p> <p>2012-12-01</p> <p>Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H42D..08J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H42D..08J"><span>Investigating the Sensitivity of Streamflow and Water Quality to Climate Change and Urbanization in 20 U.S. Watersheds</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Johnson, T. E.; Weaver, C. P.; Butcher, J.; Parker, A.</p> <p>2011-12-01</p> <p>Watershed modeling was conducted in 20 large (15,000-60,000 km2), U.S. watersheds to address gaps in our knowledge of the sensitivity of U.S. streamflow, nutrient (N and P) and sediment loading to potential future climate change, and methodological challenges associated with integrating existing tools (e.g., climate models, watershed models) and datasets to address these questions. Climate change scenarios are based on dynamically downscaled (50x50 km2) output from four of the GCMs used in the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report for the period 2041-2070 archived by the North American Regional Climate Change Assessment Program (NARCCAP). To explore the potential interaction of climate change and urbanization, model simulations also include urban and residential development scenarios for each of the 20 study watersheds. Urban and residential development scenarios were acquired from EPA's national-scale Integrated Climate and Land Use Scenarios (ICLUS) project. Watershed modeling was conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil and Water Assessment Tool (SWAT) models. Here we present a summary of results for 5 of the study watersheds; the Minnesota River, the Susquehanna River, the Apalachicola-Chattahoochee-Flint, the Salt/Verde/San Pedro, and the Willamette River Basins. This set of results provide an overview of the response to climate change in different regions of the U.S., the different sensitivities of different streamflow and water quality endpoints, and illustrate a number of methodological issues including the sensitivities and uncertainties associated with use of different watershed models, approaches for downscaling climate change projections, and interaction between climate change and other forcing factors, specifically urbanization and changes in atmospheric CO2 concentration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21556186','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21556186"><span>Climate change and vector-borne diseases: an economic impact analysis of malaria in Africa.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Egbendewe-Mondzozo, Aklesso; Musumba, Mark; McCarl, Bruce A; Wu, Ximing</p> <p>2011-03-01</p> <p>A semi-parametric econometric model is used to study the relationship between malaria cases and climatic factors in 25 African countries. Results show that a marginal change in temperature and precipitation levels would lead to a significant change in the number of malaria cases for most countries by the end of the century. Consistent with the existing biophysical malaria model results, the projected effects of climate change are mixed. Our model projects that some countries will see an increase in malaria cases but others will see a decrease. We estimate projected malaria inpatient and outpatient treatment costs as a proportion of annual 2000 health expenditures per 1,000 people. We found that even under minimal climate change scenario, some countries may see their inpatient treatment cost of malaria increase more than 20%.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/tm/6b7/pdf/tm6-b7.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/tm/6b7/pdf/tm6-b7.pdf"><span>PRMS-IV, the precipitation-runoff modeling system, version 4</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.</p> <p>2015-01-01</p> <p>Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23690959','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23690959"><span>Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu</p> <p>2013-01-01</p> <p>Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19625300','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19625300"><span>Integrating bioclimate with population models to improve forecasts of species extinctions under climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brook, Barry W; Akçakaya, H Resit; Keith, David A; Mace, Georgina M; Pearson, Richard G; Araújo, Miguel B</p> <p>2009-12-23</p> <p>Climate change is already affecting species worldwide, yet existing methods of risk assessment have not considered interactions between demography and climate and their simultaneous effect on habitat distribution and population viability. To address this issue, an international workshop was held at the University of Adelaide in Australia, 25-29 May 2009, bringing leading species distribution and population modellers together with plant ecologists. Building on two previous workshops in the UK and Spain, the participants aimed to develop methodological standards and case studies for integrating bioclimatic and metapopulation models, to provide more realistic forecasts of population change, habitat fragmentation and extinction risk under climate change. The discussions and case studies focused on several challenges, including spatial and temporal scale contingencies, choice of predictive climate, land use, soil type and topographic variables, procedures for ensemble forecasting of both global climate and bioclimate models and developing demographic structures that are realistic and species-specific and yet allow generalizations of traits that make species vulnerable to climate change. The goal is to provide general guidelines for assessing the Red-List status of large numbers of species potentially at risk, owing to the interactions of climate change with other threats such as habitat destruction, overexploitation and invasive species.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/875736','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/875736"><span>A model to estimate the cost effectiveness of the indoorenvironment improvements in office work</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Seppanen, Olli; Fisk, William J.</p> <p>2004-06-01</p> <p>Deteriorated indoor climate is commonly related to increases in sick building syndrome symptoms, respiratory illnesses, sick leave, reduced comfort and losses in productivity. The cost of deteriorated indoor climate for the society is high. Some calculations show that the cost is higher than the heating energy costs of the same buildings. Also building-level calculations have shown that many measures taken to improve indoor air quality and climate are cost-effective when the potential monetary savings resulting from an improved indoor climate are included as benefits gained. As an initial step towards systemizing these building level calculations we have developed a conceptualmore » model to estimate the cost-effectiveness of various measures. The model shows the links between the improvements in the indoor environment and the following potential financial benefits: reduced medical care cost, reduced sick leave, better performance of work, lower turn over of employees, and lower cost of building maintenance due to fewer complaints about indoor air quality and climate. The pathways to these potential benefits from changes in building technology and practices go via several human responses to the indoor environment such as infectious diseases, allergies and asthma, sick building syndrome symptoms, perceived air quality, and thermal environment. The model also includes the annual cost of investments, operation costs, and cost savings of improved indoor climate. The conceptual model illustrates how various factors are linked to each other. SBS symptoms are probably the most commonly assessed health responses in IEQ studies and have been linked to several characteristics of buildings and IEQ. While the available evidence indicates that SBS symptoms can affect these outcomes and suspects that such a linkage exists, at present we can not quantify the relationships sufficiently for cost-benefit modeling. New research and analyses of existing data to quantify the financial importance of SBS symptoms would enable more widespread consideration of the effects of IEQ in cost benefit calculations.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11E1927K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11E1927K"><span>A New Integrated Threshold Selection Methodology for Spatial Forecast Verification of Extreme Events</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kholodovsky, V.</p> <p>2017-12-01</p> <p>Extreme weather and climate events such as heavy precipitation, heat waves and strong winds can cause extensive damage to the society in terms of human lives and financial losses. As climate changes, it is important to understand how extreme weather events may change as a result. Climate and statistical models are often independently used to model those phenomena. To better assess performance of the climate models, a variety of spatial forecast verification methods have been developed. However, spatial verification metrics that are widely used in comparing mean states, in most cases, do not have an adequate theoretical justification to benchmark extreme weather events. We proposed a new integrated threshold selection methodology for spatial forecast verification of extreme events that couples existing pattern recognition indices with high threshold choices. This integrated approach has three main steps: 1) dimension reduction; 2) geometric domain mapping; and 3) thresholds clustering. We apply this approach to an observed precipitation dataset over CONUS. The results are evaluated by displaying threshold distribution seasonally, monthly and annually. The method offers user the flexibility of selecting a high threshold that is linked to desired geometrical properties. The proposed high threshold methodology could either complement existing spatial verification methods, where threshold selection is arbitrary, or be directly applicable in extreme value theory.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/43898','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/43898"><span>Assessing the vulnerability of watersheds to climate change: results of national forest watershed vulnerability pilot assessments</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Michael J. Furniss; Ken B. Roby; Dan Cenderelli; John Chatel; Caty F. Clifton; Alan Clingenpeel; Polly E. Hays; Dale Higgins; Ken Hodges; Carol Howe; Laura Jungst; Joan Louie; Christine Mai; Ralph Martinez; Kerry Overton; Brian P. Staab; Rory Steinke; Mark Weinhold</p> <p>2013-01-01</p> <p>Existing models and predictions project serious changes to worldwide hydrologic processes as a result of global climate change. Projections indicate that significant change may threaten National Forest System watersheds that are an important source of water used to support people, economies, and ecosystems.Wildland managers are expected to anticipate and...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/EJ1111541.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/EJ1111541.pdf"><span>The Teaching of Anthropogenic Climate Change and Earth Science via Technology-Enabled Inquiry Education</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Bush, Drew; Sieber, Renee; Seiler, Gale; Chandler, Mark</p> <p>2016-01-01</p> <p>A gap has existed between the tools and processes of scientists working on anthropogenic global climate change (AGCC) and the technologies and curricula available to educators teaching the subject through student inquiry. Designing realistic scientific inquiry into AGCC poses a challenge because research on it relies on complex computer models,…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.1965B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.1965B"><span>Forward modeling of tree-ring data: a case study with a global network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Breitenmoser, P. D.; Frank, D.; Brönnimann, S.</p> <p>2012-04-01</p> <p>Information derived from tree-rings is one of the most powerful tools presently available for studying past climatic variability as well as identifying fundamental relationships between tree-growth and climate. Climate reconstructions are typically performed by extending linear relationships, established during the overlapping period of instrumental and climate proxy archives into the past. Such analyses, however, are limited by methodological assumptions, including stationarity and linearity of the climate-proxy relationship. We investigate climate and tree-ring data using the Vaganov-Shashkin-Lite (VS-Lite) forward model of tree-ring width formation to examine the relations among actual tree growth and climate (as inferred from the simulated chronologies) to reconstruct past climate variability. The VS-lite model has been shown to produce skill comparable to that achieved using classical dendrochronological statistical modeling techniques when applied on simulations of a network of North American tree-ring chronologies. Although the detailed mechanistic processes such as photosynthesis, storage, or cell processes are not modeled directly, the net effect of the dominating nonlinear climatic controls on tree-growth are implemented into the model by the principle of limiting factors and threshold growth response functions. The VS-lite model requires as inputs only latitude, monthly mean temperature and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree-rings to monthly climate conditions obtained from the 20th century reanalysis project back to 1871. These simulated tree-ring chronologies are compared to the climate-driven variability in worldwide observed tree-ring chronologies from the International Tree Ring Database. Results point toward the suitability of the relationship among actual tree growth and climate (as inferred from the simulated chronologies) for use in global palaeoclimate reconstructions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011WRR....4712516G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011WRR....4712516G"><span>Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goderniaux, Pascal; BrouyèRe, Serge; Blenkinsop, Stephen; Burton, Aidan; Fowler, Hayley J.; Orban, Philippe; Dassargues, Alain</p> <p>2011-12-01</p> <p>Several studies have highlighted the potential negative impact of climate change on groundwater reserves, but additional work is required to help water managers plan for future changes. In particular, existing studies provide projections for a stationary climate representative of the end of the century, although information is demanded for the near future. Such time-slice experiments fail to account for the transient nature of climatic changes over the century. Moreover, uncertainty linked to natural climate variability is not explicitly considered in previous studies. In this study we substantially improve upon the state-of-the-art by using a sophisticated transient weather generator in combination with an integrated surface-subsurface hydrological model (Geer basin, Belgium) developed with the finite element modeling software "HydroGeoSphere." This version of the weather generator enables the stochastic generation of large numbers of equiprobable climatic time series, representing transient climate change, and used to assess impacts in a probabilistic way. For the Geer basin, 30 equiprobable climate change scenarios from 2010 to 2085 have been generated for each of six different regional climate models (RCMs). Results show that although the 95% confidence intervals calculated around projected groundwater levels remain large, the climate change signal becomes stronger than that of natural climate variability by 2085. Additionally, the weather generator's ability to simulate transient climate change enabled the assessment of the likely time scale and associated uncertainty of a specific impact, providing managers with additional information when planning further investment. This methodology constitutes a real improvement in the field of groundwater projections under climate change conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.B33D1054R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.B33D1054R"><span>Climate Change Impacts on Hydrology and Water Management of the San Juan Basin</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.</p> <p>2005-12-01</p> <p>Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1995EOSTr..76..265C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1995EOSTr..76..265C"><span>Ice sheets play important role in climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clark, Peter U.; MacAyeal, Douglas R.; Andrews, John T.; Bartlein, Patrick J.</p> <p></p> <p>Ice sheets once were viewed as passive elements in the climate system enslaved to orbitally generated variations in solar radiation. Today, modeling results and new geologic records suggest that ice sheets actively participated in late-Pleistocene climate change, amplifying or driving significant variability at millennial as well as orbital timescales. Although large changes in global ice volume were ultimately caused by orbital variations (the Milankovitch hypothesis), once in existence, the former ice sheets behaved dynamically and strongly influenced regional and perhaps even global climate by altering atmospheric and oceanic circulation and temperature.Experiments with General Circulation Models (GCMs) yielded the first inklings of ice sheets' climatic significance. Manabe and Broccoli [1985], for example, found that the topographic and albedo effects of ice sheets alone explain much of the Northern Hemisphere cooling identified in paleoclimatic records of the last glacial maximum (˜21 ka).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25657652','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25657652"><span>Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Iglesias, Virginia; Yospin, Gabriel I; Whitlock, Cathy</p> <p>2014-01-01</p> <p>Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4302794','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4302794"><span>Reconstruction of fire regimes through integrated paleoecological proxy data and ecological modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Iglesias, Virginia; Yospin, Gabriel I.; Whitlock, Cathy</p> <p>2015-01-01</p> <p>Fire is a key ecological process affecting vegetation dynamics and land cover. The characteristic frequency, size, and intensity of fire are driven by interactions between top-down climate-driven and bottom-up fuel-related processes. Disentangling climatic from non-climatic drivers of past fire regimes is a grand challenge in Earth systems science, and a topic where both paleoecology and ecological modeling have made substantial contributions. In this manuscript, we (1) review the use of sedimentary charcoal as a fire proxy and the methods used in charcoal-based fire history reconstructions; (2) identify existing techniques for paleoecological modeling; and (3) evaluate opportunities for coupling of paleoecological and ecological modeling approaches to better understand the causes and consequences of past, present, and future fire activity. PMID:25657652</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1228428-multi-model-analysis-atlantic-influence-southern-amazon-rainfall','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1228428-multi-model-analysis-atlantic-influence-southern-amazon-rainfall"><span>Multi-model analysis of the Atlantic influence on Southern Amazon rainfall</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Yoon, Jin -Ho</p> <p>2015-12-07</p> <p>Amazon rainfall is subject to year-to-year fluctuation resulting in drought and flood in various intensities. A major climatic driver of the interannual variation of the Amazon rainfall is El Niño/Southern Oscillation. Also, the Sea Surface Temperature over the Atlantic Ocean is identified as an important climatic driver on the Amazon water cycle. Previously, observational datasets were used to support the Atlantic influence on Amazon rainfall. Furthermore, it is found that multiple global climate models do reproduce the Atlantic-Amazon link robustly. However, there exist differences in rainfall response, which primarily depends on the climatological rainfall amount.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19..453L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19..453L"><span>Feedbacks between climate change and biosphere integrity</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lade, Steven; Anderies, J. Marty; Donges, Jonathan; Steffen, Will; Rockström, Johan; Richardson, Katherine; Cornell, Sarah; Norberg, Jon; Fetzer, Ingo</p> <p>2017-04-01</p> <p>The terrestrial and marine biospheres sink substantial fractions of human fossil fuel emissions. How the biosphere's capacity to sink carbon depends on biodiversity and other measures of biosphere integrity is however poorly understood. Here, we (1): review assumptions from literature regarding the relationships between the carbon cycle and the terrestrial and marine biospheres; and (2) explore the consequences of these different assumptions for climate feedbacks using the stylised carbon cycle model PB-INT. We find that: terrestrial biodiversity loss could significantly dampen climate-carbon cycle feedbacks; direct biodiversity effects, if they exist, could rival temperature increases from low-emission trajectories; and the response of the marine biosphere is critical for longer term climate change. Simple, low-dimensional climate models such as PB-INT can help assess the importance of still unknown or controversial earth system processes such as biodiversity loss for climate feedbacks. This study constitutes the first detailed study of the interactions between climate change and biosphere integrity, two of the 'planetary boundaries'.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25898351','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25898351"><span>Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Brown, Patrick T; Li, Wenhong; Cordero, Eugene C; Mauget, Steven A</p> <p>2015-04-21</p> <p>The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20(th) century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4404682','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4404682"><span>Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Brown, Patrick T.; Li, Wenhong; Cordero, Eugene C.; Mauget, Steven A.</p> <p>2015-01-01</p> <p>The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenario's forced signal, but is likely inconsistent with the steepest emission scenario's forced signal. PMID:25898351</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_4");'>4</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li class="active"><span>6</span></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_6 --> <div id="page_7" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="121"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPa...8.1339S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPa...8.1339S"><span>Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sundberg, R.; Moberg, A.; Hind, A.</p> <p>2012-08-01</p> <p>A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25680630','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25680630"><span>Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Junk, J; Ulber, B; Vidal, S; Eickermann, M</p> <p>2015-11-01</p> <p>Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015IJBm...59.1597J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015IJBm...59.1597J"><span>Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.</p> <p>2015-11-01</p> <p>Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/14654317','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/14654317"><span>Potential effect of climate change on malaria transmission in Africa.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tanser, Frank C; Sharp, Brian; le Sueur, David</p> <p>2003-11-29</p> <p>Climate change is likely to affect transmission of vector-borne diseases such as malaria. We quantitatively estimated current malaria exposure and assessed the potential effect of projected climate scenarios on malaria transmission. We produced a spatiotemporally validated (against 3791 parasite surveys) model of Plasmodium falciparum malaria transmission in Africa. Using different climate scenarios from the Hadley Centre global climate model (HAD CM3) climate experiments, we projected the potential effect of climate change on transmission patterns. Our model showed sensitivity and specificity of 63% and 96%, respectively (within 1 month temporal accuracy), when compared with the parasite surveys. We estimate that on average there are 3.1 billion person-months of exposure (445 million people exposed) in Africa per year. The projected scenarios would estimate a 5-7% potential increase (mainly altitudinal) in malaria distribution with surprisingly little increase in the latitudinal extents of the disease by 2100. Of the overall potential increase (although transmission will decrease in some countries) of 16-28% in person-months of exposure (assuming a constant population), a large proportion will be seen in areas of existing transmission. The effect of projected climate change indicates that a prolonged transmission season is as important as geographical expansion in correct assessment of the effect of changes in transmission patterns. Our model constitutes a valid baseline against which climate scenarios can be assessed and interventions planned.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28080984','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28080984"><span>Modelling coffee leaf rust risk in Colombia with climate reanalysis data.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J</p> <p>2016-12-05</p> <p>Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ThApC.124.1033M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ThApC.124.1033M"><span>Integration of climatic indices in an objective probabilistic model for establishing and mapping viticultural climatic zones in a region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moral, Francisco J.; Rebollo, Francisco J.; Paniagua, Luis L.; García, Abelardo; Honorio, Fulgencio</p> <p>2016-05-01</p> <p>Different climatic indices have been proposed to determine the wine suitability in a region. Some of them are related to the air temperature, but the hydric component of climate should also be considered which, in turn, is influenced by the precipitation during the different stages of the grapevine growing and ripening periods. In this study, we propose using the information obtained from ten climatic indices [heliothermal index (HI), cool night index (CI), dryness index (DI), growing season temperature (GST), the Winkler index (WI), September mean thermal amplitude (MTA), annual precipitation (AP), precipitation during flowering (PDF), precipitation before flowering (PBF), and summer precipitation (SP)] as inputs in an objective and probabilistic model, the Rasch model, with the aim of integrating the individual effects of them, obtaining the climate data that summarize all main climatic indices, which could influence on wine suitability from a climate viewpoint, and utilizing the Rasch measures to generate homogeneous climatic zones. The use of the Rasch model to estimate viticultural climatic suitability constitutes a new application of great practical importance, enabling to rationally determine locations in a region where high viticultural potential exists and establishing a ranking of the climatic indices which exerts an important influence on wine suitability in a region. Furthermore, from the measures of viticultural climatic suitability at some locations, estimates can be computed using a geostatistical algorithm, and these estimates can be utilized to map viticultural climatic zones in a region. To illustrate the process, an application to Extremadura, southwestern Spain, is shown.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27889676','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27889676"><span>Towards a threshold climate for emergency lower respiratory hospital admissions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Islam, Muhammad Saiful; Chaussalet, Thierry J; Koizumi, Naoru</p> <p>2017-02-01</p> <p>Identification of 'cut-points' or thresholds of climate factors would play a crucial role in alerting risks of climate change and providing guidance to policymakers. This study investigated a 'Climate Threshold' for emergency hospital admissions of chronic lower respiratory diseases by using a distributed lag non-linear model (DLNM). We analysed a unique longitudinal dataset (10 years, 2000-2009) on emergency hospital admissions, climate, and pollution factors for the Greater London. Our study extends existing work on this topic by considering non-linearity, lag effects between climate factors and disease exposure within the DLNM model considering B-spline as smoothing technique. The final model also considered natural cubic splines of time since exposure and 'day of the week' as confounding factors. The results of DLNM indicated a significant improvement in model fitting compared to a typical GLM model. The final model identified the thresholds of several climate factors including: high temperature (≥27°C), low relative humidity (≤ 40%), high Pm10 level (≥70-µg/m 3 ), low wind speed (≤ 2 knots) and high rainfall (≥30mm). Beyond the threshold values, a significantly higher number of emergency admissions due to lower respiratory problems would be expected within the following 2-3 days after the climate shift in the Greater London. The approach will be useful to initiate 'region and disease specific' climate mitigation plans. It will help identify spatial hot spots and the most sensitive areas and population due to climate change, and will eventually lead towards a diversified health warning system tailored to specific climate zones and populations. Copyright © 2016 Elsevier Inc. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.B31D0348W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.B31D0348W"><span>Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.</p> <p>2011-12-01</p> <p>Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29023503','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29023503"><span>Model uncertainties do not affect observed patterns of species richness in the Amazon.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo; Loyola, Rafael</p> <p>2017-01-01</p> <p>Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale-patterns of species richness and species vulnerability to climate change-are affected by the inputs used to model and project species distribution. We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5638225','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5638225"><span>Model uncertainties do not affect observed patterns of species richness in the Amazon</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Sales, Lilian Patrícia; Neves, Olívia Viana; De Marco, Paulo</p> <p>2017-01-01</p> <p>Background Climate change is arguably a major threat to biodiversity conservation and there are several methods to assess its impacts on species potential distribution. Yet the extent to which different approaches on species distribution modeling affect species richness patterns at biogeographical scale is however unaddressed in literature. In this paper, we verified if the expected responses to climate change in biogeographical scale—patterns of species richness and species vulnerability to climate change—are affected by the inputs used to model and project species distribution. Methods We modeled the distribution of 288 vertebrate species (amphibians, birds and mammals), all endemic to the Amazon basin, using different combinations of the following inputs known to affect the outcome of species distribution models (SDMs): 1) biological data type, 2) modeling methods, 3) greenhouse gas emission scenarios and 4) climate forecasts. We calculated uncertainty with a hierarchical ANOVA in which those different inputs were considered factors. Results The greatest source of variation was the modeling method. Model performance interacted with data type and modeling method. Absolute values of variation on suitable climate area were not equal among predictions, but some biological patterns were still consistent. All models predicted losses on the area that is climatically suitable for species, especially for amphibians and primates. All models also indicated a current East-western gradient on endemic species richness, from the Andes foot downstream the Amazon river. Again, all models predicted future movements of species upwards the Andes mountains and overall species richness losses. Conclusions From a methodological perspective, our work highlights that SDMs are a useful tool for assessing impacts of climate change on biodiversity. Uncertainty exists but biological patterns are still evident at large spatial scales. As modeling methods are the greatest source of variation, choosing the appropriate statistics according to the study objective is also essential for estimating the impacts of climate change on species distribution. Yet from a conservation perspective, we show that Amazon endemic fauna is potentially vulnerable to climate change, due to expected reductions on suitable climate area. Climate-driven faunal movements are predicted towards the Andes mountains, which might work as climate refugia for migrating species. PMID:29023503</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810054382&hterms=plastic+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dplastic%2Bocean','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810054382&hterms=plastic+ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dplastic%2Bocean"><span>A climate model with cryodynamics and geodynamics</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ghil, M.; Le Treut, H.</p> <p>1981-01-01</p> <p>A simplified, zero-dimensional model of the climatic system is presented which attempts to incorporate mechanisms important on the time scale of glaciation cycles: 10,000 to 100,000 years. The ocean-atmosphere radiation balance, continental ice sheet plastic flow, and upper mantle viscous flow are taken into account, with stress on the interaction between the ice sheets and the upper mantle. The model exhibits free, self-sustained oscillations of an amplitude and period comparable to those found in the paleoclimatic record of glaciations, offering mild support for the idea that unforced oscillations can actually exist in the real climatic system itself. The careful study of the interplay between internal mechanisms and external forcing is held to represent an interesting challenge to the theory of ice ages.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC23F..06A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC23F..06A"><span>Modeling Urban Energy Savings Scenarios Using Earth System Microclimate and Urban Morphology</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Allen, M. R.; Rose, A.; New, J. R.; Yuan, J.; Omitaomu, O.; Sylvester, L.; Branstetter, M. L.; Carvalhaes, T. M.; Seals, M.; Berres, A.</p> <p>2017-12-01</p> <p>We analyze and quantify the relationships among climatic conditions, urban morphology, population, land cover, and energy use so that these relationships can be used to inform energy-efficient urban development and planning. We integrate different approaches across three research areas: earth system modeling; impacts, adaptation and vulnerability; and urban planning in order to address three major gaps in the existing capability in these areas: i) neighborhood resolution modeling and simulation of urban micrometeorological processes and their effect on and from regional climate; ii) projections for future energy use under urbanization and climate change scenarios identifying best strategies for urban morphological development and energy savings; iii) analysis and visualization tools to help planners optimally use these projections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70157068','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70157068"><span>Modelling the enigmatic Late Pliocene Glacial Event - Marine Isotope Stage M2</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Dolan, Aisling M.; Haywood, Alan M.; Hunter, Stephen J.; Tindall, Julia C.; Dowsett, Harry J.; Hill, Daniel J.; Pickering, Steven J.</p> <p>2015-01-01</p> <p>The Pliocene Epoch (5.2 to 2.58 Ma) has often been targeted to investigate the nature of warm climates. However, climate records for the Pliocene exhibit significant variability and show intervals that apparently experienced a cooler than modern climate. Marine Isotope Stage (MIS) M2 (~ 3.3 Ma) is a globally recognisable cooling event that disturbs an otherwise relatively (compared to present-day) warm background climate state. It remains unclear whether this event corresponds to significant ice sheet build-up in the Northern and Southern Hemisphere. Estimates of sea level for this interval vary, and range from modern values to estimates of 65 m sea level fall with respect to present day. Here we implement plausible M2 ice sheet configurations into a coupled atmosphere–ocean climate model to test the hypothesis that larger-than-modern ice sheet configurations may have existed at M2. Climate model results are compared with proxy climate data available for M2 to assess the plausibility of each ice sheet configuration. Whilst the outcomes of our data/model comparisons are not in all cases straight forward to interpret, there is little indication that results from model simulations in which significant ice masses have been prescribed in the Northern Hemisphere are incompatible with proxy data from the North Atlantic, Northeast Arctic Russia, North Africa and the Southern Ocean. Therefore, our model results do not preclude the possibility of the existence of larger ice masses during M2 in the Northern or Southern Hemisphere. Specifically they are not able to discount the possibility of significant ice masses in the Northern Hemisphere during the M2 event, consistent with a global sea-level fall of between 40 m and 60 m. This study highlights the general need for more focused and coordinated data generation in the future to improve the coverage and consistency in proxy records for M2, which will allow these and future M2 sensitivity tests to be interrogated further.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN53C..08Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN53C..08Y"><span>Integrated assessment of water-power grid systems under changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yan, E.; Zhou, Z.; Betrie, G.</p> <p>2017-12-01</p> <p>Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. In this presentation, we are focusing on recent improvement in model development of thermoelectric power plant water use simulator, power grid operation and cost optimization model, and model integration that facilitate interaction among water and electricity generation under extreme climate events. A process based thermoelectric power water use simulator includes heat-balance, climate, and cooling system modules that account for power plant characteristics, fuel types, and cooling technology. The model is validated with more than 800 power plants of fossil-fired, nuclear and gas-turbine power plants with different cooling systems. The power grid operation and cost optimization model was implemented for a selected regional in the Midwest. The case study will be demonstrated to evaluate the sensitivity and resilience of thermoelectricity generation and power grid under various climate and hydrologic extremes and potential economic consequences.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1321P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1321P"><span>The regional climate model REMO (v2015) coupled with the 1-D freshwater lake model FLake (v1): Fenno-Scandinavian climate and lakes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pietikäinen, Joni-Pekka; Markkanen, Tiina; Sieck, Kevin; Jacob, Daniela; Korhonen, Johanna; Räisänen, Petri; Gao, Yao; Ahola, Jaakko; Korhonen, Hannele; Laaksonen, Ari; Kaurola, Jussi</p> <p>2018-04-01</p> <p>The regional climate model REMO was coupled with the FLake lake model to include an interactive treatment of lakes. Using this new version, the Fenno-Scandinavian climate and lake characteristics were studied in a set of 35-year hindcast simulations. Additionally, sensitivity tests related to the parameterization of snow albedo were conducted. Our results show that overall the new model version improves the representation of the Fenno-Scandinavian climate in terms of 2 m temperature and precipitation, but the downside is that an existing wintertime cold bias in the model is enhanced. The lake surface water temperature, ice depth and ice season length were analyzed in detail for 10 Finnish, 4 Swedish and 2 Russian lakes and 1 Estonian lake. The results show that the model can reproduce these characteristics with reasonably high accuracy. The cold bias during winter causes overestimation of ice layer thickness, for example, at several of the studied lakes, but overall the values from the model are realistic and represent the lake physics well in a long-term simulation. We also analyzed the snow depth on ice from 10 Finnish lakes and vertical temperature profiles from 5 Finnish lakes and the model results are realistic.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24456900','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24456900"><span>Geo-environmental model for the prediction of potential transmission risk of Dirofilaria in an area with dry climate and extensive irrigated crops. The case of Spain.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando</p> <p>2014-03-01</p> <p>Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AIPC.1782d0002A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AIPC.1782d0002A"><span>Dynamics of climate-based malaria transmission model with age-structured human population</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Addawe, Joel; Pajimola, Aprimelle Kris</p> <p>2016-10-01</p> <p>In this paper, we proposed to study the dynamics of malaria transmission with periodic birth rate of the vector and an age-structure for the human population. The human population is divided into two compartments: pre-school (0-5 years) and the rest of the human population. We showed the existence of a disease-free equilibrium point. Using published epidemiological parameters, we use numerical simulations to show potential effect of climate change in the dynamics of age-structured malaria transmission. Numerical simulations suggest that there exists an asymptotically attractive solution that is positive and periodic.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310621&keyword=Global+AND+warming&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50','EPA-EIMS'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310621&keyword=Global+AND+warming&actType=&TIMSType=+&TIMSSubTypeID=&DEID=&epaNumber=&ntisID=&archiveStatus=Both&ombCat=Any&dateBeginCreated=&dateEndCreated=&dateBeginPublishedPresented=&dateEndPublishedPresented=&dateBeginUpdated=&dateEndUpdated=&dateBeginCompleted=&dateEndCompleted=&personID=&role=Any&journalID=&publisherID=&sortBy=revisionDate&count=50"><span>Towards a climate-dependent paradigm of ammonia emission and deposition</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://oaspub.epa.gov/eims/query.page">EPA Science Inventory</a></p> <p></p> <p></p> <p>Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4645171','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4645171"><span>Heat Transport Compensation in Atmosphere and Ocean over the Past 22,000 Years</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yang, Haijun; Zhao, Yingying; Liu, Zhengyu; Li, Qing; He, Feng; Zhang, Qiong</p> <p>2015-01-01</p> <p>The Earth’s climate has experienced dramatic changes over the past 22,000 years; however, the total meridional heat transport (MHT) of the climate system remains stable. A 22,000-year-long simulation using an ocean-atmosphere coupled model shows that the changes in atmosphere and ocean MHT are significant but tend to be out of phase in most regions, mitigating the total MHT change, which helps to maintain the stability of the Earth’s overall climate. A simple conceptual model is used to understand the compensation mechanism. The simple model can reproduce qualitatively the evolution and compensation features of the MHT over the past 22,000 years. We find that the global energy conservation requires the compensation changes in the atmosphere and ocean heat transports. The degree of compensation is mainly determined by the local climate feedback between surface temperature and net radiation flux at the top of the atmosphere. This study suggests that an internal mechanism may exist in the climate system, which might have played a role in constraining the global climate change over the past 22,000 years. PMID:26567710</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC31E..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC31E..04S"><span>Defining climate modeling user needs: which data are actually required to support impact analysis and adaptation policy development?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Swart, R. J.; Pagé, C.</p> <p>2010-12-01</p> <p>Until recently, the policy applications of Earth System Models in general and climate models in particular were focusing mainly on the potential future changes in the global and regional climate and attribution of observed changes to anthropogenic activities. Is climate change real? And if so, why do we have to worry about it? Following the broad acceptance of the reality of the risks by the majority of governments, particularly after the publication of IPCC’s 4th Assessment Report and the increasing number of observations of changes in ecological and socio-economic systems that are consistent with the observed climatic changes, governments, companies and other societal groups have started to evaluate their own vulnerability in more detail and to develop adaptation and mitigation strategies. After an early focus on the most vulnerable developing countries, recently, an increasing number of industrialized countries have embarked on the design of adaptation and mitigation plans, or on studies to evaluate the level of climate resilience of their development plans and projects. Which climate data are actually required to effectively support these activities? This paper reports on the efforts of the IS-ENES project, the infrastructure project of the European Network for Earth System Modeling, to address this question. How do we define user needs and can the existing gap between the climate modeling and impact research communities be bridged in support of the ENES long-term strategy? In contrast from the climate modeling community, which has a relatively long history of collaboration facilitated by a relatively uniform subject matter, commonly agreed definitions of key terminology and some level of harmonization of methods, the climate change impacts research community is very diverse and fragmented, using a wide variety of data sources, methods and tools. An additional complicating factor is that researchers working on adaptation usually closely collaborate with non-scientific stakeholders in government, civil society and the private sector, in a context which is different in many European countries. In the IS-ENES effort, a dialogue is set up between the communities in Europe, building on various existing research networks in the area of climate change impacts, vulnerability and adaptation. Generally, the data needs have not been well articulated. If asked, people working on impacts and adaptation routinely seem to ask for data with the highest possible resolution. However, in reality for many impact and adaptation applications this is not needed, and the large resulting data sets may exceed the analytical capacity of the impact researchers. For impact analysis often various types of climate indices, derived from primary climate model output variables, are required, including indices for extremes and in probabilistic format. Rather than making output from climate modeling generically available, e.g. through a climate service e-portal, context-specific tailoring of information for specific applications is important for effective use. This may require some level of interaction between the users and the data providers, dependent on the specific questions to be addressed.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24670422','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24670422"><span>Refining climate change projections for organisms with low dispersal abilities: a case study of the Caspian whip snake.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sahlean, Tiberiu C; Gherghel, Iulian; Papeş, Monica; Strugariu, Alexandru; Zamfirescu, Ştefan R</p> <p>2014-01-01</p> <p>Climate warming is one of the most important threats to biodiversity. Ectothermic organisms such as amphibians and reptiles are especially vulnerable as climatic conditions affect them directly. Ecological niche models (ENMs) are increasingly popular in ecological studies, but several drawbacks exist, including the limited ability to account for the dispersal potential of the species. In this study, we use ENMs to explore the impact of global climate change on the Caspian whip snake (Dolichophis caspius) as model for organisms with low dispersal abilities and to quantify dispersal to novel areas using GIS techniques. Models generated using Maxent 3.3.3 k and GARP for current distribution were projected on future climatic scenarios. A cost-distance analysis was run in ArcGIS 10 using geomorphological features, ecological conditions, and human footprint as "costs" to dispersal of the species to obtain a Maximum Dispersal Range (MDR) estimate. All models developed were statistically significant (P<0.05) and recovered the currently known distribution of D. caspius. Models projected on future climatic conditions using Maxent predicted a doubling of suitable climatic area, while GARP predicted a more conservative expansion. Both models agreed on an expansion of suitable area northwards, with minor decreases at the southern distribution limit. The MDR area calculated using the Maxent model represented a third of the total area of the projected model. The MDR based on GARP models recovered only about 20% of the total area of the projected model. Thus, incorporating measures of species' dispersal abilities greatly reduced estimated area of potential future distributions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/4637','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/4637"><span>Is carbon storage enough? Can plants adapt? New questions in climate change research.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Sally Duncan</p> <p>2002-01-01</p> <p>As it becomes increasingly apparent that human activities are partly responsible for global warming, the focus of climate change research is shifting from the churning out of assessments to the pursuit of science that can test the robustness of existing models. The questions now being addressed are becoming more challenging: Can water-use efficiency of plants keep up...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/14437','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/14437"><span>Developing the next generation of forest ecosystem models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Christopher R. Schwalm; Alan R. Ek</p> <p>2002-01-01</p> <p>Forest ecology and management are model-rich areas for research. Models are often cast as either empirical or mechanistic. With evolving climate change, hybrid models gain new relevance because of their ability to integrate existing mechanistic knowledge with empiricism based on causal thinking. The utility of hybrid platforms results in the combination of...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/8985005','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/8985005"><span>Predictability of North Atlantic Multidecadal Climate Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Griffies; Bryan</p> <p>1997-01-10</p> <p>Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the dominant multidecadal sea surface temperature patterns in the North Atlantic, which have been associated with changes in climate over Eurasia, can be predicted if an adequate and sustainable system for monitoring the Atlantic Ocean exists.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27113317','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27113317"><span>US forest response to projected climate-related stress: a tolerance perspective.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liénard, Jean; Harrison, John; Strigul, Nikolay</p> <p>2016-08-01</p> <p>Although it is widely recognized that climate change will require a major spatial reorganization of forests, our ability to predict exactly how and where forest characteristics and distributions will change has been rather limited. Current efforts to predict future distribution of forested ecosystems as a function of climate include species distribution models (for fine-scale predictions) and potential vegetation climate envelope models (for coarse-grained, large-scale predictions). Here, we develop and apply an intermediate approach wherein we use stand-level tolerances of environmental stressors to understand forest distributions and vulnerabilities to anticipated climate change. In contrast to other existing models, this approach can be applied at a continental scale while maintaining a direct link to ecologically relevant, climate-related stressors. We first demonstrate that shade, drought, and waterlogging tolerances of forest stands are strongly correlated with climate and edaphic conditions in the conterminous United States. This discovery allows the development of a tolerance distribution model (TDM), a novel quantitative tool to assess landscape level impacts of climate change. We then focus on evaluating the implications of the drought TDM. Using an ensemble of 17 climate change models to drive this TDM, we estimate that 18% of US ecosystems are vulnerable to drought-related stress over the coming century. Vulnerable areas include mostly the Midwest United States and Northeast United States, as well as high-elevation areas of the Rocky Mountains. We also infer stress incurred by shifting climate should create an opening for the establishment of forest types not currently seen in the conterminous United States. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B31C0428G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B31C0428G"><span>How will climate change affect watershed mercury export in a representative Coastal Plain watershed?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.</p> <p>2012-12-01</p> <p>Future climate change is expected to drive variations in watershed hydrological processes and water quality across a wide range of physiographic provinces, ecosystems, and spatial scales. How such shifts in climatic conditions will impact watershed mercury (Hg) dynamics and hydrologically-driven Hg transport is a significant concern. We simulate the responses of watershed hydrological and total Hg (HgT) fluxes and concentrations to a unified set of past and future climate change projections in a Coastal Plain basin using multiple watershed models. We use two statistically downscaled global precipitation and temperature models, ECHO, a hybrid of the ECHAM4 and HOPE-G models, and the Community Climate System Model (CCSM3) across two thirty-year simulations (1980 to 2010 and 2040 to 2070). We apply three watershed models to quantify and bracket potential changes in hydrologic and HgT fluxes, including the Visualizing Ecosystems for Land Management Assessment Model for Hg (VELMA-Hg), the Grid Based Mercury Model (GBMM), and TOPLOAD, a water quality constituent model linked to TOPMODEL hydrological simulations. We estimate a decrease in average annual HgT fluxes in response to climate change using the ECHO projections and an increase with the CCSM3 projections in the study watershed. Average monthly HgT fluxes increase using both climate change projections between in the late spring (March through May), when HgT concentrations and flow are high. Results suggest that hydrological transport associated with changes in precipitation and temperature is the primary mechanism driving HgT flux response to climate change. Our multiple model/multiple projection approach allows us to bracket the relative response of HgT fluxes to climate change, thereby illustrating the uncertainty associated with the projections. In addition, our approach allows us to examine potential variations in climate change-driven water and HgT export based on different conceptualizations of watershed HgT dynamics and the representative mathematical structures underpinning existing watershed Hg models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.6374M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.6374M"><span>A field and glacier modelling based approach to determine the timing and extent of glaciation in southern Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mills, Stephanie C.; Rowan, Ann V.; Barrow, Timothy T.; Plummer, Mitchell A.; Smith, Michael; Grab, Stefan W.; Carr, Simon J.; Fifield, L. Keith</p> <p>2014-05-01</p> <p>Moraines identified at high-altitude sites in southern Africa and dated to the last glacial maximum (LGM) indicate that the climate in this region was cold enough to support glaciers. Small glaciers are very sensitive to changes in temperature and precipitation and the identification of LGM moraines in southern Africa has important palaeoclimatic implications concerning the magnitude of temperature change and the seasonality of precipitation during the last glacial cycle. This paper presents a refined time-frame for likely glaciations based on surface exposure dating using Cl-36 at sites in Lesotho and reports results of a 2D glacier energy balance and ice flow modelling approach (Plummer and Phillips, 2003) to evaluate the most likely climatic scenarios associated with mapped moraine limits. Samples for surface exposure dating were collected from glacially eroded bedrock at several locations and yield ages within the timescale of the LGM. Scatter in the ages may be due to insufficient erosion of the bedrock surface due to the small and relatively thin nature of the glaciers. To determine the most likely climatic conditions that may have caused the glaciers to reach their mapped extent, we use a glacier-climate model, driven by data from local weather stations and a 30m (ASTER) DEM (sub-sampled to 10m) representation of the topographic surface. The model is forced using modern climate data for primary climatic controls (temperature and precipitation) and for secondary climatic parameters (relative humidity, cloudiness, wind speed). Various sensitivity tests were run by dropping temperature by small increments and by varying the amount of precipitation and its seasonality relative to present-day values. Results suggest that glaciers could have existed in the Lesotho highlands with a temperature depression of ~5-6 ºC and that the glaciers were highly sensitive to small changes in temperature. The additional accumulation of mass through wind redistribution appears to have been important at all but a few sites, suggesting that this must be taken into account when trying to determine a regional climate signal from small glaciers. Our dating and glacier-climate model simulations reinforce the idea that small glaciers existed in the Lesotho Highlands during the LGM, under climatic scenarios that are consistent with other proxy records. Plummer, M.A. and Phillips, F.M. (2003) 2-D numerical model of snow/ice energy balance and ice flow for paleoclimatic interpretation of glacial geomorphic features. Quaternary Science Reviews, 22, 1389-1406.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3140741','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3140741"><span>The future of terrestrial mammals in the Mediterranean basin under climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Maiorano, Luigi; Falcucci, Alessandra; Zimmermann, Niklaus E.; Psomas, Achilleas; Pottier, Julien; Baisero, Daniele; Rondinini, Carlo; Guisan, Antoine; Boitani, Luigi</p> <p>2011-01-01</p> <p>The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition. PMID:21844047</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917052V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917052V"><span>Investigating the Capacity of Hydrological Models to Project Impacts of Climate Change in the Context of Water Allocation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando</p> <p>2017-04-01</p> <p>To analyse the impacts of climate changes, hydrological models are used to project the hydrology responds under future conditions that normally differ from those for which they were calibrated. The challenge is to assess the validity of the projected effects when there is not data to validate it. A framework for testing the ability of models to project climate change was proposed by Refsgaard et al., (2014). The authors recommend the use of the differential-split sample test (DSST) in order to build confidence in the model projections. The method follow three steps: 1. A small number of sub-periods are selected according to one climate characteristics, 2. The calibration - validation test is applied on these periods, 3. The validation performances are compered to evaluate whether they vary significantly when climatic characteristics differ between calibration and validation. DSST rely on the existing records of climate and hydrological variables; and performances are estimated based on indicators of error between observed and simulated variables. Other authors suggest that, since climate models are not able to reproduce single events but rather statistical properties describing the climate, this should be reflected when testing hydrological models. Thus, performance criteria such as RMSE should be replaced by for instance flow duration curves or other distribution functions. Using this type of performance criteria, Van Steenbergen and Willems, (2012) proposed a method to test the validity of hydrological models in a climate changing context. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. In contrast to DSST, this method use the projected climate variability and it is especially useful to compare different modelling tools. In the framework of a water allocation project for the region of Flanders (Belgium) we calibrated three hydrological models: NAM, PDM and VHM; for 67 gauged sub-catchments with approx. 40 years of records. This paper investigates the capacity of the three hydrological models to project the impacts of climate change scenarios. It is proposed a general testing framework which combine the use of the existing information through an adapted form of DSST with the approach proposed by Van Steenbergen and Willems, (2012) adapted to assess statistical properties of flows useful in the context of water allocation. To assess the model we use robustness criteria based on a Log Nash-Sutcliffe, BIAS on cummulative volumes and relative changes based on Q50/Q90 estimated from the duration curve. The three conceptual rainfall-runoff models yielded different results per sub-catchments. A relation was found between robustness criteria and changes in mean rainfall and changes in mean potential evapotranspiration. Biases are greatly affected by changes in precipitation, especially when the climate scenarios involve changes in precipitation volume beyond the range used for calibration. Using the combine approach we were able to classify the modelling tools per sub-catchments and create an ensemble of best models to project the impacts of climate variability for the catchments of 10 main rivers in Flanders. Thus, managers could understand better the usability of the modelling tools and the credibility of its outputs for water allocation applications. References Refsgaard, J.C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T.A., Drews, M., Hamilton, D.P., Jeppesen, E., Kjellström, E., Olesen, J.E., Sonnenborg, T.O., Trolle, D., Willems, P., Christensen, J.H., 2014. A framework for testing the ability of models to project climate change and its impacts. Clim. Change. Van Steenbergen, N., Willems, P., 2012. Method for testing the accuracy of rainfall - runoff models in predicting peak flow changes due to rainfall changes , in a climate changing context. J. Hydrol. 415, 425-434.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1513593W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1513593W"><span>Decision- rather than scenario-centred downscaling: Towards smarter use of climate model outputs</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilby, Robert L.</p> <p>2013-04-01</p> <p>Climate model output has been used for hydrological impact assessments for at least 25 years. Scenario-led methods raise awareness about risks posed by climate variability and change to the security of supplies, performance of water infrastructure, and health of freshwater ecosystems. However, it is less clear how these analyses translate into actionable information for adaptation. One reason is that scenario-led methods typically yield very large uncertainty bounds in projected impacts at regional and river catchment scales. Consequently, there is growing interest in vulnerability-based frameworks and strategies for employing climate model output in decision-making contexts. This talk begins by summarising contrasting perspectives on climate models and principles for testing their utility for water sector applications. Using selected examples it is then shown how water resource systems may be adapted with varying levels of reliance on climate model information. These approaches include the conventional scenario-led risk assessment, scenario-neutral strategies, safety margins and sensitivity testing, and adaptive management of water systems. The strengths and weaknesses of each approach are outlined and linked to selected water management activities. These cases show that much progress can be made in managing water systems without dependence on climate models. Low-regret measures such as improved forecasting, better inter-agency co-operation, and contingency planning, yield benefits regardless of the climate outlook. Nonetheless, climate model scenarios are useful for evaluating adaptation portfolios, identifying system thresholds and fixing weak links, exploring the timing of investments, improving operating rules, or developing smarter licensing regimes. The most problematic application remains the climate change safety margin because of the very low confidence in extreme precipitation and river flows generated by climate models. In such cases, it is necessary to understand the trade-offs that exist between the additional costs of a scheme and the level of risk that is accommodated.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140011827','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140011827"><span>Assessing the Impact of Laurentide Ice-sheet Topography on Glacial Climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ullman, D. J.; LeGrande, A. N.; Carlson, A. E.; Anslow, F. S.; Licciardi, J. M.</p> <p>2014-01-01</p> <p>Simulations of past climates require altered boundary conditions to account for known shifts in the Earth system. For the Last Glacial Maximum (LGM) and subsequent deglaciation, the existence of large Northern Hemisphere ice sheets caused profound changes in surface topography and albedo. While ice-sheet extent is fairly well known, numerous conflicting reconstructions of ice-sheet topography suggest that precision in this boundary condition is lacking. Here we use a high-resolution and oxygen-isotopeenabled fully coupled global circulation model (GCM) (GISS ModelE2-R), along with two different reconstructions of the Laurentide Ice Sheet (LIS) that provide maximum and minimum estimates of LIS elevation, to assess the range of climate variability in response to uncertainty in this boundary condition.We present this comparison at two equilibrium time slices: the LGM, when differences in ice-sheet topography are maximized, and 14 ka, when differences in maximum ice-sheet height are smaller but still exist. Overall, we find significant differences in the climate response to LIS topography, with the larger LIS resulting in enhanced Atlantic Meridional Overturning Circulation and warmer surface air temperatures, particularly over northeastern Asia and the North Pacific. These up- and downstream effects are associated with differences in the development of planetary waves in the upper atmosphere, with the larger LIS resulting in a weaker trough over northeastern Asia that leads to the warmer temperatures and decreased albedo from snow and sea-ice cover. Differences between the 14 ka simulations are similar in spatial extent but smaller in magnitude, suggesting that climate is responding primarily to the larger difference in maximum LIS elevation in the LGM simulations. These results suggest that such uncertainty in ice-sheet boundary conditions alone may significantly impact the results of paleoclimate simulations and their ability to successfully simulate past climates, with implications for estimating climate sensitivity to greenhouse gas forcing utilizing past climate states.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014WRR....50.6370F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014WRR....50.6370F"><span>Modeling irrigation behavior in groundwater systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Foster, Timothy; Brozović, Nicholas; Butler, Adrian P.</p> <p>2014-08-01</p> <p>Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160010643&hterms=Experimental+design&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DExperimental%2Bdesign','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160010643&hterms=Experimental+design&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DExperimental%2Bdesign"><span>The Model Intercomparison Project on the Climatic Response to Volcanic Forcing (VolMIP): Experimental Design and Forcing Input Data for CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zanchettin, Davide; Khodri, Myriam; Timmreck, Claudia; Toohey, Matthew; Schmidt, Anja; Gerber, Edwin P.; Hegerl, Gabriele; Robock, Alan; Pausata, Francesco; Ball, William T.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160010643'); toggleEditAbsImage('author_20160010643_show'); toggleEditAbsImage('author_20160010643_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160010643_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160010643_hide"></p> <p>2016-01-01</p> <p>The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150005676&hterms=geophysic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dgeophysic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150005676&hterms=geophysic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dgeophysic"><span>Software Analysis of New Space Gravity Data for Geophysics and Climate Research</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Deese, Rupert; Ivins, Erik R.; Fielding, Eric J.</p> <p>2012-01-01</p> <p>Both the Gravity Recovery and Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellites are returning rich data for the study of the solid earth, the oceans, and the climate. Current software analysis tools do not provide researchers with the ease and flexibility required to make full use of this data. We evaluate the capabilities and shortcomings of existing software tools including Mathematica, the GOCE User Toolbox, the ICGEM's (International Center for Global Earth Models) web server, and Tesseroids. Using existing tools as necessary, we design and implement software with the capability to produce gridded data and publication quality renderings from raw gravity data. The straight forward software interface marks an improvement over previously existing tools and makes new space gravity data more useful to researchers. Using the software we calculate Bouguer anomalies of the gravity tensor's vertical component in the Gulf of Mexico, Antarctica, and the 2010 Maule earthquake region. These maps identify promising areas of future research.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GeoRL..44.2810G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GeoRL..44.2810G"><span>The projected demise of Barnes Ice Cap: Evidence of an unusually warm 21st century Arctic</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gilbert, A.; Flowers, G. E.; Miller, G. H.; Refsnider, K. A.; Young, N. E.; Radić, V.</p> <p>2017-03-01</p> <p>As a remnant of the Laurentide Ice Sheet, Barnes Ice Cap owes its existence and present form in part to the climate of the last glacial period. The ice cap has been sustained in the present interglacial climate by its own topography through the mass balance-elevation feedback. A coupled mass balance and ice-flow model, forced by Coupled Model Intercomparison Project Phase 5 climate model output, projects that the current ice cap will likely disappear in the next 300 years. For greenhouse gas Representative Concentration Pathways of +2.6 to +8.5 Wm-2, the projected ice-cap survival times range from 150 to 530 years. Measured concentrations of cosmogenic radionuclides 10Be, 26Al, and 14C at sites exposed near the ice-cap margin suggest the pending disappearance of Barnes Ice Cap is very unusual in the last million years. The data and models together point to an exceptionally warm 21st century Arctic climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018RvGeo..56..108H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018RvGeo..56..108H"><span>Seasonal Drought Prediction: Advances, Challenges, and Future Prospects</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hao, Zengchao; Singh, Vijay P.; Xia, Youlong</p> <p>2018-03-01</p> <p>Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3655130','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3655130"><span>Forecasting the Future Risk of Barmah Forest Virus Disease under Climate Change Scenarios in Queensland, Australia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu</p> <p>2013-01-01</p> <p>Background Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. Methods/Principal Findings We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. Conclusions/Significance We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland. PMID:23690959</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC43A0685Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC43A0685Z"><span>Global Potential for Hydro-generated Electricity and Climate Change Impact</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhou, Y.; Hejazi, M. I.; Leon, C.; Calvin, K. V.; Thomson, A. M.; Li, H. Y.</p> <p>2014-12-01</p> <p>Hydropower is a dominant renewable energy source at the global level, accounting for more than 15% of the world's total power supply. It is also very vulnerable to climate change. Improved understanding of climate change impact on hydropower can help develop adaptation measures to increase the resilience of energy system. In this study, we developed a comprehensive estimate of global hydropower potential using runoff and stream flow data derived from a global hydrologic model with a river routing sub-model, along with turbine technology performance, cost assumptions, and environmental consideration (Figure 1). We find that hydropower has the potential to supply a significant portion of the world energy needs, although this potential varies substantially by regions. Resources in a number of countries exceed by multiple folds the total current demand for electricity, e.g., Russia and Indonesia. A sensitivity analysis indicates that hydropower potential can be highly sensitive to a number of parameters including designed flow for capacity, cost and financing, turbine efficiency, and stream flow. The climate change impact on hydropower potential was evaluated by using runoff outputs from 4 climate models (HadCM3, PCM, CGCM2, and CSIRO2). It was found that the climate change on hydropower shows large variation not only by regions, but also climate models, and this demonstrates the importance of incorporating climate change into infrastructure-planning at the regional level though the existing uncertainties.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010047842','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010047842"><span>Northern Hemisphere Winter Climate Response to Greenhouse Gas, Ozone, Solar and Volcanic Forcing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shindell, Drew T.; Schmidt, Gavin A.; Miller, Ron L.; Rind, David; Hansen, James E. (Technical Monitor)</p> <p>2001-01-01</p> <p>The Goddard Institute for Space Studies (GISS) climate/middle atmosphere model has been used to study the impacts of increasing greenhouse gases, polar ozone depletion, volcanic eruptions, and solar cycle variability. We focus on the projection of the induced responses onto Northern Hemisphere winter surface climate. Changes in the model's surface climate take place largely through enhancement of existing variability patterns, with greenhouse gases, polar ozone depletion and volcanic eruptions primarily affecting the Arctic Oscillation (AO) pattern. Perturbations descend from the stratosphere to the surface in the model by altering the propagation of planetary waves coming up from the surface, in accord with observational evidence. Models lacking realistic stratospheric dynamics fail to capture these wave flux changes. The results support the conclusion that the stratosphere plays a crucial role in recent AO trends. We show that in our climate model, while ozone depletion has a significant effect, greenhouse gas forcing is the only one capable of causing the large, sustained increase in the AO observed over recent decades. This suggests that the AO trend, and a concurrent strengthening of the stratospheric vortex over the Arctic, are very likely anthropogenic in origin.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28246631','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28246631"><span>State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu</p> <p>2017-02-01</p> <p>Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5298857','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5298857"><span>State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu</p> <p>2017-01-01</p> <p>Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29155862','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29155862"><span>A multi-paradigm framework to assess the impacts of climate change on end-use energy demand.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nateghi, Roshanak; Mukherjee, Sayanti</p> <p>2017-01-01</p> <p>Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5695769','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5695769"><span>A multi-paradigm framework to assess the impacts of climate change on end-use energy demand</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nateghi, Roshanak</p> <p>2017-01-01</p> <p>Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months. PMID:29155862</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27594725','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27594725"><span>Climate Shocks and Migration: An Agent-Based Modeling Approach.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree</p> <p>2016-09-01</p> <p>This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19897722','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19897722"><span>On the stability of the Atlantic meridional overturning circulation.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hofmann, Matthias; Rahmstorf, Stefan</p> <p>2009-12-08</p> <p>One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5004973"><span>Climate Shocks and Migration: An Agent-Based Modeling Approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Entwisle, Barbara; Williams, Nathalie E.; Verdery, Ashton M.; Rindfuss, Ronald R.; Walsh, Stephen J.; Malanson, George P.; Mucha, Peter J.; Frizzelle, Brian G.; McDaniel, Philip M.; Yao, Xiaozheng; Heumann, Benjamin W.; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree</p> <p>2016-01-01</p> <p>This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, ‘normal’ scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response. PMID:27594725</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21456825','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21456825"><span>Regular network model for the sea ice-albedo feedback in the Arctic.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Müller-Stoffels, Marc; Wackerbauer, Renate</p> <p>2011-03-01</p> <p>The Arctic Ocean and sea ice form a feedback system that plays an important role in the global climate. The complexity of highly parameterized global circulation (climate) models makes it very difficult to assess feedback processes in climate without the concurrent use of simple models where the physics is understood. We introduce a two-dimensional energy-based regular network model to investigate feedback processes in an Arctic ice-ocean layer. The model includes the nonlinear aspect of the ice-water phase transition, a nonlinear diffusive energy transport within a heterogeneous ice-ocean lattice, and spatiotemporal atmospheric and oceanic forcing at the surfaces. First results for a horizontally homogeneous ice-ocean layer show bistability and related hysteresis between perennial ice and perennial open water for varying atmospheric heat influx. Seasonal ice cover exists as a transient phenomenon. We also find that ocean heat fluxes are more efficient than atmospheric heat fluxes to melt Arctic sea ice.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015NPGeo..22..433S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015NPGeo..22..433S"><span>Global terrestrial water storage connectivity revealed using complex climate network analyses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun, A. Y.; Chen, J.; Donges, J.</p> <p>2015-07-01</p> <p>Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27474896','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27474896"><span>Assessing uncertainties in land cover projections.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A</p> <p>2017-02-01</p> <p>Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791570','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791570"><span>El Niño/Southern Oscillation response to global warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Latif, M.; Keenlyside, N. S.</p> <p>2009-01-01</p> <p>The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO2, accelerating global warming. PMID:19060210</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013NatCC...3..559M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013NatCC...3..559M"><span>A coupled physical and economic model of the response of coastal real estate to climate risk</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McNamara, Dylan E.; Keeler, Andrew</p> <p>2013-06-01</p> <p>Barring an unprecedented large-scale effort to raise island elevation, barrier-island communities common along the US East Coast are likely to eventually face inundation of the existing built environment on a timescale that depends on uncertain climatic forcing. Between the present and when a combination of sea-level rise and erosion renders these areas uninhabitable, communities must choose levels of defensive expenditures to reduce risks and individual residents must assess whether and when risk levels are unacceptably high to justify investment in housing. We model the dynamics of coastal adaptation as the interplay of underlying climatic risks, collective actions to mitigate those risks, and individual risk assessments based on beliefs in model predictions and processing of past climate events. Efforts linking physical and behavioural models to explore shoreline dynamics have not yet brought together this set of essential factors. We couple a barrier-island model with an agent-based model of real-estate markets to show that, relative to people with low belief in model predictions about climate change, informed property owners invest heavily in defensive expenditures in the near term and then abandon coastal real estate at some critical risk threshold that presages a period of significant price volatility.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19060210','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19060210"><span>El Nino/Southern Oscillation response to global warming.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Latif, M; Keenlyside, N S</p> <p>2009-12-08</p> <p>The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO(2), accelerating global warming.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/10149481','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/10149481"><span>Modernization of the graphics post-processors of the Hamburg German Climate Computer Center Carbon Cycle Codes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Stevens, E.J.; McNeilly, G.S.</p> <p></p> <p>The existing National Center for Atmospheric Research (NCAR) code in the Hamburg Oceanic Carbon Cycle Circulation Model and the Hamburg Large-Scale Geostrophic Ocean General Circulation Model was modernized and reduced in size while still producing an equivalent end result. A reduction in the size of the existing code from more than 50,000 lines to approximately 7,500 lines in the new code has made the new code much easier to maintain. The existing code in Hamburg model uses legacy NCAR (including even emulated CALCOMP subrountines) graphics to display graphical output. The new code uses only current (version 3.1) NCAR subrountines.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AtmEn.118....7S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AtmEn.118....7S"><span>Development of a national anthropogenic heating database with an extrapolation for international cities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sailor, David J.; Georgescu, Matei; Milne, Jeffrey M.; Hart, Melissa A.</p> <p>2015-10-01</p> <p>Given increasing utility of numerical models to examine urban impacts on meteorology and climate, there exists an urgent need for accurate representation of seasonally and diurnally varying anthropogenic heating data, an important component of the urban energy budget for cities across the world. Incorporation of anthropogenic heating data as inputs to existing climate modeling systems has direct societal implications ranging from improved prediction of energy demand to health assessment, but such data are lacking for most cities. To address this deficiency we have applied a standardized procedure to develop a national database of seasonally and diurnally varying anthropogenic heating profiles for 61 of the largest cities in the United Stated (U.S.). Recognizing the importance of spatial scale, the anthropogenic heating database developed includes the city scale and the accompanying greater metropolitan area. Our analysis reveals that a single profile function can adequately represent anthropogenic heating during summer but two profile functions are required in winter, one for warm climate cities and another for cold climate cities. On average, although anthropogenic heating is 40% larger in winter than summer, the electricity sector contribution peaks during summer and is smallest in winter. Because such data are similarly required for international cities where urban climate assessments are also ongoing, we have made a simple adjustment accounting for different international energy consumption rates relative to the U.S. to generate seasonally and diurnally varying anthropogenic heating profiles for a range of global cities. The methodological approach presented here is flexible and straightforwardly applicable to cities not modeled because of presently unavailable data. Because of the anticipated increase in global urban populations for many decades to come, characterizing this fundamental aspect of the urban environment - anthropogenic heating - is an essential element toward continued progress in urban climate assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.9810M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.9810M"><span>Climate Projection Data base for Roads - CliPDaR: Design a guideline for a transnational database of downscaled climate projection data for road impact models - within the Conference's of European Directors of Roads (CEDR) TRANSNATIONAL ROAD RESEARCH PROG</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Matulla, Christoph; Namyslo, Joachim; Fuchs, Tobias; Türk, Konrad</p> <p>2013-04-01</p> <p>The European road sector is vulnerable to extreme weather phenomena, which can cause large socio-economic losses. Almost every year there occur several weather triggered events (like heavy precipitation, floods, landslides, high winds, snow and ice, heat or cold waves, etc.), that disrupt transportation, knock out power lines, cut off populated regions from the outside and so on. So, in order to avoid imbalances in the supply of vital goods to people as well as to prevent negative impacts on health and life of people travelling by car it is essential to know present and future threats to roads. Climate change might increase future threats to roads. CliPDaR focuses on parts of the European road network and contributes, based on the current body of knowledge, to the establishment of guidelines helping to decide which methods and scenarios to apply for the estimation of future climate change based challenges in the field of road maintenance. Based on regional scale climate change projections specific road-impact models are applied in order to support protection measures. In recent years, it has been recognised that it is essential to assess the uncertainty and reliability of given climate projections by using ensemble approaches and downscaling methods. A huge amount of scientific work has been done to evaluate these approaches with regard to reliability and usefulness for investigations on possible impacts of climate changes. CliPDaR is going to collect the existing approaches and methodologies in European countries, discuss their differences and - in close cooperation with the road owners - develops a common line on future applications of climate projection data to road impact models. As such, the project will focus on reviewing and assessing existing regional climate change projections regarding transnational highway transport needs. The final project report will include recommendations how the findings of CliPDaR may support the decision processes of European national road administrations regarding possible future climate change impacts. First project results are presented at the conference.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatEn...116073J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatEn...116073J"><span>Comparison and interactions between the long-term pursuit of energy independence and climate policies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jewell, Jessica; Vinichenko, Vadim; McCollum, David; Bauer, Nico; Riahi, Keywan; Aboumahboub, Tino; Fricko, Oliver; Harmsen, Mathijs; Kober, Tom; Krey, Volker; Marangoni, Giacomo; Tavoni, Massimo; van Vuuren, Detlef P.; van der Zwaan, Bob; Cherp, Aleh</p> <p>2016-06-01</p> <p>Ensuring energy security and mitigating climate change are key energy policy priorities. The recent Intergovernmental Panel on Climate Change Working Group III report emphasized that climate policies can deliver energy security as a co-benefit, in large part through reducing energy imports. Using five state-of-the-art global energy-economy models and eight long-term scenarios, we show that although deep cuts in greenhouse gas emissions would reduce energy imports, the reverse is not true: ambitious policies constraining energy imports would have an insignificant impact on climate change. Restricting imports of all fuels would lower twenty-first-century emissions by only 2-15% against the Baseline scenario as compared with a 70% reduction in a 450 stabilization scenario. Restricting only oil imports would have virtually no impact on emissions. The modelled energy independence targets could be achieved at policy costs comparable to those of existing climate pledges but a fraction of the cost of limiting global warming to 2 ∘C.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70048449','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70048449"><span>Forecasting conditional climate-change using a hybrid approach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Esfahani, Akbar Akbari; Friedel, Michael J.</p> <p>2014-01-01</p> <p>A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28750284','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28750284"><span>Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio</p> <p>2017-11-01</p> <p>The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1069F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1069F"><span>New insights into the use of stable water isotopes at the northern Antarctic Peninsula as a tool for regional climate studies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fernandoy, Francisco; Tetzner, Dieter; Meyer, Hanno; Gacitúa, Guisella; Hoffmann, Kirstin; Falk, Ulrike; Lambert, Fabrice; MacDonell, Shelley</p> <p>2018-03-01</p> <p>Due to recent atmospheric and oceanic warming, the Antarctic Peninsula is one of the most challenging regions of Antarctica to understand in terms of both local- and regional-scale climate signals. Steep topography and a lack of long-term and in situ meteorological observations complicate the extrapolation of existing climate models to the sub-regional scale. Therefore, new techniques must be developed to better understand processes operating in the region. Isotope signals are traditionally related mainly to atmospheric conditions, but a detailed analysis of individual components can give new insight into oceanic and atmospheric processes. This paper aims to use new isotopic records collected from snow and firn cores in conjunction with existing meteorological and oceanic datasets to determine changes at the climatic scale in the northern extent of the Antarctic Peninsula. In particular, a discernible effect of sea ice cover on local temperatures and the expression of climatic modes, especially the Southern Annular Mode (SAM), is demonstrated. In years with a large sea ice extension in winter (negative SAM anomaly), an inversion layer in the lower troposphere develops at the coastal zone. Therefore, an isotope-temperature relationship (δ-T) valid for all periods cannot be obtained, and instead the δ-T depends on the seasonal variability of oceanic conditions. Comparatively, transitional seasons (autumn and spring) have a consistent isotope-temperature gradient of +0.69 ‰ °C-1. As shown by firn core analysis, the near-surface temperature in the northern-most portion of the Antarctic Peninsula shows a decreasing trend (-0.33 °C year-1) between 2008 and 2014. In addition, the deuterium excess (dexcess) is demonstrated to be a reliable indicator of seasonal oceanic conditions, and therefore suitable to improve a firn age model based on seasonal dexcess variability. The annual accumulation rate in this region is highly variable, ranging between 1060 and 2470 kg m-2 year-1 from 2008 to 2014. The combination of isotopic and meteorological data in areas where data exist is key to reconstruct climatic conditions with a high temporal resolution in polar regions where no direct observations exist.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1375423-status-challenge-global-fire-modelling','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1375423-status-challenge-global-fire-modelling"><span>The status and challenge of global fire modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...</p> <p>2016-06-09</p> <p>Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016BGeo...13.3359H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016BGeo...13.3359H"><span>The status and challenge of global fire modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao</p> <p>2016-06-01</p> <p>Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1375423','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1375423"><span>The status and challenge of global fire modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.</p> <p></p> <p>Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2675786','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2675786"><span>Work–family climate, organizational commitment, and turnover: Multilevel contagion effects of leaders ⋆</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>O’Neill, John W.; Harrison, Michelle M.; Cleveland, Jeannette; Almeida, David; Stawski, Robert; Crouter, Anne C.</p> <p>2009-01-01</p> <p>This paper presents empirical research analyzing the relationship between work–family climate (operationalized in terms of three work–family climate sub-scales), organizational leadership (i.e., senior manager) characteristics, organizational commitment and turnover intent among 526 employees from 37 different hotels across the US. Using multilevel modeling, we found significant associations between work–family climate, and both organizational commitment and turnover intent, both within and between hotels. Findings underscored the importance of managerial support for employee work–family balance, the relevance of senior managers’ own work–family circumstances in relation to employees’ work outcomes, and the existence of possible contagion effects of leaders in relation to work–family climate. PMID:19412351</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.H52B..06O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.H52B..06O"><span>Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.</p> <p>2005-12-01</p> <p>Central America covers a relatively small area, but is topographically very complex, has long coast-lines, large inland bodies of water, and very diverse land cover which is both natural and human-induced. As a result, Central America is plagued by hydrologic extremes, especially major flooding and drought events, in a region where many people still barely manage to eke out a living through subsistence. Therefore, considerable concern exists about whether these extreme events will change, either in magnitude or in number, as climate changes in the future. To address this concern, we have used global climate model simulations of future climate change to drive a regional climate model centered on Central America. We use the IPCC `business as usual' scenario 21st century run made with the NCAR CCSM3 global model to drive the regional model MM5 at 12 km resolution. We chose the `business as usual' scenario to focus on the largest possible changes that are likely to occur. Because we are most interested in near-term changes, our simulations are for the years 2010, 2015, and 2025. A long `present-day run (for 2005) allows us to distinguish between climate variability and any signal due to climate change. Furthermore, a multi-year run with MM5 forced by NCEP reanalyses allows an assessment of how well the coupled global-regional model performs over Central America. Our analyses suggest that the coupled model does a credible job simulating the current climate and hydrologic regime, though lack of sufficient observations strongly complicates this comparison. The suite of model runs for the future years is currently nearing completion, and key results will be presented at the meeting.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1053998','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1053998"><span>Collaborative Research: Robust Climate Projections and Stochastic Stability of Dynamical Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ilya Zaliapin</p> <p></p> <p>This project focused on conceptual exploration of El Nino/Southern Oscillation (ENSO) variability and sensitivity using a Delay Differential Equation developed in the project. We have (i) established the existence and continuous dependence of solutions of the model (ii) explored multiple models solutions, and the distribution of solutions extrema, and (iii) established and explored the phase locking phenomenon and the existence of multiple solutions for the same values of model parameters. In addition, we have applied to our model the concept of pullback attractor, which greatly facilitated predictive understanding of the nonlinear model's behavior.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC23C0955K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC23C0955K"><span>Adapting the Biome-BGC Model to New Zealand Pastoral Agriculture: Climate Change and Land-Use Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Keller, E. D.; Baisden, W. T.; Timar, L.</p> <p>2011-12-01</p> <p>We have adapted the Biome-BGC model to make climate change and land-use scenario estimates of New Zealand's pasture production in 2020 and 2050, with comparison to a 2005 baseline. We take an integrated modelling approach with the aim of enabling the model's use for policy assessments across broadly related issues such as climate change mitigation and adaptation, land-use change, and greenhouse gas projections. The Biome-BGC model is a biogeochemical model that simulates carbon, water, and nitrogen cycles in terrestrial ecosystems. We introduce two new 'ecosystems', sheep/beef and dairy pasture, within the existing structure of the Biome-BGC model and calibrate its ecophysiological parameters against pasture clipping data from diverse sites around New Zealand to form a baseline estimate of total New Zealand pasture production. Using downscaled AR4 climate projections, we construct mid- and upper-range climate change scenarios in 2020 and 2050. We produce land-use change scenarios in the same years by combining the Biome-BGC model with the Land Use in Rural New Zealand (LURNZ) model. The LURNZ model uses econometric approaches to predict future land-use change driven by changes in net profits driven by expected pricing, including the introduction of an emission trading system. We estimate the relative change in national pasture production from our 2005 baseline levels for both sheep/beef and dairy systems under each scenario.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018TCry...12.1479M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018TCry...12.1479M"><span>Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 2: Antarctica (1979-2016)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Melchior van Wessem, Jan; van de Berg, Willem Jan; Noël, Brice P. Y.; van Meijgaard, Erik; Amory, Charles; Birnbaum, Gerit; Jakobs, Constantijn L.; Krüger, Konstantin; Lenaerts, Jan T. M.; Lhermitte, Stef; Ligtenberg, Stefan R. M.; Medley, Brooke; Reijmer, Carleen H.; van Tricht, Kristof; Trusel, Luke D.; van Ulft, Lambertus H.; Wouters, Bert; Wuite, Jan; van den Broeke, Michiel R.</p> <p>2018-04-01</p> <p>We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface mass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016). The updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation, a revised topography, tuned parameters in the cloud scheme to generate more precipitation towards the AIS interior and modified snow properties reducing drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational data show that the existing biases in AIS temperature, radiative fluxes and SMB components are further reduced with respect to the previous model version. The model-integrated annual average SMB for the ice sheet including ice shelves (minus the Antarctic Peninsula, AP) now amounts to 2229 Gt y-1, with an interannual variability of 109 Gt y-1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution ( ˜ 5.5 km) AP simulation, results remain comparable to earlier studies. The updated model provides a new, high-resolution data set of the contemporary near-surface climate and SMB of the AIS; this model version will be used for future climate scenario projections in a forthcoming study.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H11F0918K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H11F0918K"><span>An improved Multimodel Approach for Global Sea Surface Temperature Forecasts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khan, M. Z. K.; Mehrotra, R.; Sharma, A.</p> <p>2014-12-01</p> <p>The concept of ensemble combinations for formulating improved climate forecasts has gained popularity in recent years. However, many climate models share similar physics or modeling processes, which may lead to similar (or strongly correlated) forecasts. Recent approaches for combining forecasts that take into consideration differences in model accuracy over space and time have either ignored the similarity of forecast among the models or followed a pairwise dynamic combination approach. Here we present a basis for combining model predictions, illustrating the improvements that can be achieved if procedures for factoring in inter-model dependence are utilised. The utility of the approach is demonstrated by combining sea surface temperature (SST) forecasts from five climate models over a period of 1960-2005. The variable of interest, the monthly global sea surface temperature anomalies (SSTA) at a 50´50 latitude-longitude grid, is predicted three months in advance to demonstrate the utility of the proposed algorithm. Results indicate that the proposed approach offers consistent and significant improvements for majority of grid points compared to the case where the dependence among the models is ignored. Therefore, the proposed approach of combining multiple models by taking into account the existing interdependence, provides an attractive alternative to obtain improved climate forecast. In addition, an approach to combine seasonal forecasts from multiple climate models with varying periods of availability is also demonstrated.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Geomo.270..102M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Geomo.270..102M"><span>Modelling the effectiveness of grass buffer strips in managing muddy floods under a changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mullan, Donal; Vandaele, Karel; Boardman, John; Meneely, John; Crossley, Laura H.</p> <p>2016-10-01</p> <p>Muddy floods occur when rainfall generates runoff on agricultural land, detaching and transporting sediment into the surrounding natural and built environment. In the Belgian Loess Belt, muddy floods occur regularly and lead to considerable economic costs associated with damage to property and infrastructure. Mitigation measures designed to manage the problem have been tested in a pilot area within Flanders and were found to be cost-effective within three years. This study assesses whether these mitigation measures will remain effective under a changing climate. To test this, the Water Erosion Prediction Project (WEPP) model was used to examine muddy flooding diagnostics (precipitation, runoff, soil loss and sediment yield) for a case study hillslope in Flanders where grass buffer strips are currently used as a mitigation measure. The model was run for present day conditions and then under 33 future site-specific climate scenarios. These future scenarios were generated from three earth system models driven by four representative concentration pathways and downscaled using quantile mapping and the weather generator CLIGEN. Results reveal that under the majority of future scenarios, muddy flooding diagnostics are projected to increase, mostly as a consequence of large scale precipitation events rather than mean changes. The magnitude of muddy flood events for a given return period is also generally projected to increase. These findings indicate that present day mitigation measures may have a reduced capacity to manage muddy flooding given the changes imposed by a warming climate with an enhanced hydrological cycle. Revisions to the design of existing mitigation measures within existing policy frameworks are considered the most effective way to account for the impacts of climate change in future mitigation planning.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2435P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2435P"><span>Elevation-dependent warming in global climate model simulations at high spatial resolution</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Palazzi, Elisa; Mortarini, Luca; Terzago, Silvia; von Hardenberg, Jost</p> <p>2018-06-01</p> <p>The enhancement of warming rates with elevation, so-called elevation-dependent warming (EDW), is one of the regional, still not completely understood, expressions of global warming. Sentinels of climate and environmental changes, mountains have experienced more rapid and intense warming trends in the recent decades, leading to serious impacts on mountain ecosystems and downstream. In this paper we use a state-of-the-art Global Climate Model (EC-Earth) to investigate the impact of model spatial resolution on the representation of this phenomenon and to highlight possible differences in EDW and its causes in different mountain regions of the Northern Hemisphere. To this end we use EC-Earth climate simulations at five different spatial resolutions, from ˜ 125 to ˜ 16 km, to explore the existence and the driving mechanisms of EDW in the Colorado Rocky Mountains, the Greater Alpine Region and the Tibetan Plateau-Himalayas. Our results show that the more frequent EDW drivers in all regions and seasons are the changes in albedo and in downward thermal radiation and this is reflected in both daytime and nighttime warming. In the Tibetan Plateau-Himalayas and in the Greater Alpine Region, an additional driver is the change in specific humidity. We also find that, while generally the model shows no clear resolution dependence in its ability to simulate the existence of EDW in the different regions, specific EDW characteristics such as its intensity and the relative role of different driving mechanisms may be different in simulations performed at different spatial resolutions. Moreover, we find that the role of internal climate variability can be significant in modulating the EDW signal, as suggested by the spread found in the multi-member ensemble of the EC-Earth experiments which we use.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26626704','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26626704"><span>A mixed model for the relationship between climate and human cranial form.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Katz, David C; Grote, Mark N; Weaver, Timothy D</p> <p>2016-08-01</p> <p>We expand upon a multivariate mixed model from quantitative genetics in order to estimate the magnitude of climate effects in a global sample of recent human crania. In humans, genetic distances are correlated with distances based on cranial form, suggesting that population structure influences both genetic and quantitative trait variation. Studies controlling for this structure have demonstrated significant underlying associations of cranial distances with ecological distances derived from climate variables. However, to assess the biological importance of an ecological predictor, estimates of effect size and uncertainty in the original units of measurement are clearly preferable to significance claims based on units of distance. Unfortunately, the magnitudes of ecological effects are difficult to obtain with distance-based methods, while models that produce estimates of effect size generally do not scale to high-dimensional data like cranial shape and form. Using recent innovations that extend quantitative genetics mixed models to highly multivariate observations, we estimate morphological effects associated with a climate predictor for a subset of the Howells craniometric dataset. Several measurements, particularly those associated with cranial vault breadth, show a substantial linear association with climate, and the multivariate model incorporating a climate predictor is preferred in model comparison. Previous studies demonstrated the existence of a relationship between climate and cranial form. The mixed model quantifies this relationship concretely. Evolutionary questions that require population structure and phylogeny to be disentangled from potential drivers of selection may be particularly well addressed by mixed models. Am J Phys Anthropol 160:593-603, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1810336','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1810336"><span>Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ammann, Caspar M.; Joos, Fortunat; Schimel, David S.; Otto-Bliesner, Bette L.; Tomas, Robert A.</p> <p>2007-01-01</p> <p>The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century. PMID:17360418</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED31B0285B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED31B0285B"><span>Promoting Climate Literacy and Conceptual Understanding among In-service Secondary Science Teachers requires an Epistemological Perspective</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bhattacharya, D.; Forbes, C.; Roehrig, G.; Chandler, M. A.</p> <p>2017-12-01</p> <p>Promoting climate literacy among in-service science teachers necessitates an understanding of fundamental concepts about the Earth's climate System (USGCRP, 2009). Very few teachers report having any formal instruction in climate science (Plutzer et al., 2016), therefore, rather simple conceptions of climate systems and their variability exist, which has implications for students' science learning (Francies et al., 1993; Libarkin, 2005; Rebich, 2005). This study uses the inferences from a NASA Innovations in Climate Education (NICE) teacher professional development program (CYCLES) to establish the necessity for developing an epistemological perspective among teachers. In CYCLES, 19 middle and high school (male=8, female=11) teachers were assessed for their understanding of global climate change (GCC). A qualitative analysis of their concept maps and an alignment of their conceptions with the Essential Principles of Climate Literacy (NOAA, 2009) demonstrated that participants emphasized on EPCL 1, 3, 6, 7 focusing on the Earth system, atmospheric, social and ecological impacts of GCC. However, EPCL 4 (variability in climate) and 5 (data-based observations and modeling) were least represented and emphasized upon. Thus, participants' descriptions about global climatic patterns were often factual rather than incorporating causation (why the temperatures are increasing) and/or correlation (describing what other factors might influence global temperatures). Therefore, engaging with epistemic dimensions of climate science to understand the processes, tools, and norms through which climate scientists study the Earth's climate system (Huxter et al., 2013) is critical for developing an in-depth conceptual understanding of climate. CLiMES (Climate Modeling and Epistemology of Science), a NSF initiative proposes to use EzGCM (EzGlobal Climate Model) to engage students and teachers in designing and running simulations, performing data processing activities, and analyzing computational models to develop their own evidence-based claims about the Earth's climate system. We describe how epistemological investigations can be conducted using EzGCM to bring the scientific process and authentic climate science practice to middle and high school classrooms.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916050A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916050A"><span>Changing precipitation in western Europe, climate change or natural variability?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart</p> <p>2017-04-01</p> <p>Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28516031','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28516031"><span>Identifying appropriate protected areas for endangered fern species under climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wang, Chun-Jing; Wan, Ji-Zhong; Zhang, Zhi-Xiang; Zhang, Gang-Min</p> <p>2016-01-01</p> <p>The management of protected areas (PAs) is widely used in the conservation of endangered plant species under climate change. However, studies that have identified appropriate PAs for endangered fern species are rare. To address this gap, we must develop a workflow to plan appropriate PAs for endangered fern species that will be further impacted by climate change. Here, we used endangered fern species in China as a case study, and we applied conservation planning software coupled with endangered fern species distribution data and distribution modeling to plan conservation areas with high priority protection needs under climate change. We identified appropriate PAs for endangered fern species under climate change based on the IUCN protected area categories (from Ia to VI) and planned additional PAs for endangered fern species. The high priority regions for protecting the endangered fern species were distributed throughout southern China. With decreasing temperature seasonality, the priority ranking of all endangered fern species is projected to increase in existing PAs. Accordingly, we need to establish conservation areas with low climate vulnerability in existing PAs and expand the conservation areas for endangered fern species in the high priority conservation regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC21G1024V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC21G1024V"><span>Advance strategy for climate change adaptation and mitigation in cities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Varquez, A. C. G.; Kanda, M.; Darmanto, N. S.; Sueishi, T.; Kawano, N.</p> <p>2017-12-01</p> <p>An on-going 5-yr project financially supported by the Ministry of Environment, Japan, has been carried out to specifically address the issue of prescribing appropriate adaptation and mitigation measures to climate change in cities. Entitled "Case Study on Mitigation and Local Adaptation to Climate Change in an Asian Megacity, Jakarta", the project's relevant objectives is to develop a research framework that can consider both urbanization and climate change with the main advantage of being readily implementable for all cities around the world. The test location is the benchmark city, Jakarta, Indonesia, with the end focus of evaluating the benefits of various mitigation and adaptation strategies in Jakarta and other megacities. The framework was designed to improve representation of urban areas when conducting climate change investigations in cities; and to be able to quantify separately the impacts of urbanization and climate change to all cities globally. It is comprised of a sophisticated, top-down, multi-downscaling approach utilizing a regional model (numerical weather model) and a microscale model (energy balance model and CFD model), with global circulation models (GCM) as input. The models, except the GCM, were configured to reasonably consider land cover, urban morphology, and anthropogenic heating (AH). Equally as important, methodologies that can collect and estimate global distribution of urban parametric and AH datasets are continually being developed. Urban growth models, climate scenario matrices that match representative concentration pathways with shared socio-economic pathways, present distribution of socio-demographic indicators such as population and GDP, existing GIS datasets of urban parameters, are utilized. From these tools, future urbanization (urban morphological parameters and AH) can be introduced into the models. Sensitivity using various combinations of GCM and urbanization can be conducted. Furthermore, since the models utilize parameters that can be readily modified to suit certain countermeasures, adaptation and mitigation strategies can be evaluated using thermal comfort and other social indicators. With the approaches introduced through this project, a deeper understanding of urban-climate interactions in the changing global climate can be achieved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A23E0374T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A23E0374T"><span>CORDEX.be: COmbining Regional climate Downscaling EXpertise in Belgium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Termonia, P.</p> <p>2015-12-01</p> <p>The main objective of the ongoing project CORDEX.be, "COmbining Regional Downscaling EXpertise in Belgium: CORDEX and Beyond", is to gather existing and ongoing Belgian research activities in the domain of climate modelling to create a coherent scientific basis for future climate services in Belgium. The project regroups 8 Belgian Institutes under a single research program of the Belgian Science Policy (BELSPO). The project involves three regional climate models: the ALARO model, the COSMO-CLM model and the MAR model running according to the guidelines of the CORDEX project and at convection permitting resolution on small domains over Belgium. The project creates a framework to address four objectives/challenges. First, this projects aims to contribute to the EURO-CORDEX project. Secondly, RCP simulations are executed at convection-permitting resolutions (3 to 5 km) on small domains. Thirdly, the output of the atmospheric models is used to drive land surface models (the SURFEX model and the Urbclim model) with urban modules, a crop model (REGCROP), a tides and storm model (COHERENS) and the MEGAN-MOHYCAN model that simulates the fluxes emitted by vegetation. Finally, one work package will translate the uncertainty present in the CORDEX database to the high-resolution output of the CORDEX.be project. The organization of the project will be presented and first results will be shown, demonstrating that convection-permitting models can add extra skill to the mesoscale version of the regional climate models, in particular regarding the extreme value statistics and the diurnal cycle.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812252T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812252T"><span>CORDEX.be: COmbining Regional climate Downscaling EXpertise in Belgium</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Termonia, Piet; Van Schaeybroeck, Bert; De Ridder, Koen; Fettweis, Xavier; Gobin, Anne; Luyten, Patrick; Marbaix, Philippe; Pottiaux, Eric; Stavrakou, Trissevgeni; Van Lipzig, Nicole; van Ypersele, Jean-Pascal; Willems, Patrick</p> <p>2016-04-01</p> <p>The main objective of the ongoing project CORDEX.be, "COmbining Regional Downscaling EXpertise in Belgium: CORDEX and Beyond" is to gather existing and ongoing Belgian research activities in the domain of climate modelling to create a coherent scientific basis for future climate services in Belgium. The project regroups eight Belgian Institutes under a single research program of the Belgian Science Policy (BELSPO). The project involves three regional climate models: the ALARO model, the COSMO-CLM model and the MAR model running according to the guidelines of the CORDEX project and at convection permitting resolution on small domains over Belgium. The project creates a framework to address four objectives/challenges. First, this projects aims to contribute to the EURO-CORDEX project. Secondly, RCP simulations are executed at convection-permitting resolutions (3 to 5 km) on small domains. Thirdly, the output of the atmospheric models is used to drive land surface models (the SURFEX model and the Urbclim model) with urban modules, a crop model (REGCROP), a tides and storm model (COHERENS) and the MEGAN-MOHYCAN model that simulates the fluxes emitted by vegetation. Finally, one work package will translate the uncertainty present in the CORDEX database to the high-resolution output of the CORDEX.be project. The organization of the project will be presented and first results will be shown, demonstrating that convection-permitting models can add extra skill to the mesoscale version of the regional climate models, in particular regarding the extreme value statistics and the diurnal cycle.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1416921','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1416921"><span>Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia</p> <p></p> <p>The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1416921-community-climate-simulations-assess-avoided-impacts-futures','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1416921-community-climate-simulations-assess-avoided-impacts-futures"><span>Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Sanderson, Benjamin M.; Xu, Yangyang; Tebaldi, Claudia; ...</p> <p>2017-09-19</p> <p>The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 andmore » 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.« less</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC53E1346B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC53E1346B"><span>Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.</p> <p>2016-12-01</p> <p>Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5544199','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5544199"><span>Disentangling the effects of a century of eutrophication and climate warming on freshwater lake fish assemblages</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hansen, Gretchen J. A.; Bethke, Bethany J.; Cross, Timothy K.</p> <p>2017-01-01</p> <p>Eutrophication and climate warming are profoundly affecting fish in many freshwater lakes. Understanding the specific effects of these stressors is critical for development of effective adaptation and remediation strategies for conserving fish populations in a changing environment. Ecological niche models that incorporated the individual effects of nutrient concentration and climate were developed for 25 species of fish sampled in standard gillnet surveys from 1,577 Minnesota lakes. Lake phosphorus concentrations and climates were hindcasted to a pre-disturbance period of 1896–1925 using existing land use models and historical temperature data. Then historical fish assemblages were reconstructed using the ecological niche models. Substantial changes were noted when reconstructed fish assemblages were compared to those from the contemporary period (1981–2010). Disentangling the sometimes opposing, sometimes compounding, effects of eutrophication and climate warming was critical for understanding changes in fish assemblages. Reconstructed abundances of eutrophication-tolerant, warmwater taxa increased in prairie lakes that experienced significant eutrophication and climate warming. Eutrophication-intolerant, warmwater taxa abundance increased in forest lakes where primarily climate warming was the stressor. Coolwater fish declined in abundance in both ecoregions. Large changes in modeled abundance occurred when the effects of both climate and eutrophication operated in the same direction for some species. Conversely, the effects of climate warming and eutrophication operated in opposing directions for other species and dampened net changes in abundance. Quantifying the specific effects of climate and eutrophication will allow water resource managers to better understand how lakes have changed and provide expectations for sustainable fish assemblages in the future. PMID:28777816</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19980004829','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19980004829"><span>Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Moore, Berrien, III; Sahagian, Dork</p> <p>1997-01-01</p> <p>The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1228428-multi-model-analysis-atlantic-influence-southern-amazon-rainfall','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1228428-multi-model-analysis-atlantic-influence-southern-amazon-rainfall"><span></span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Yoon, Jin -Ho</p> <p></p> <p>Amazon rainfall is subject to year-to-year fluctuation resulting in drought and flood in various intensities. A major climatic driver of the interannual variation of the Amazon rainfall is El Niño/Southern Oscillation. Also, the Sea Surface Temperature over the Atlantic Ocean is identified as an important climatic driver on the Amazon water cycle. Previously, observational datasets were used to support the Atlantic influence on Amazon rainfall. Furthermore, it is found that multiple global climate models do reproduce the Atlantic-Amazon link robustly. However, there exist differences in rainfall response, which primarily depends on the climatological rainfall amount.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=spaceship&pg=3&id=EJ517874','ERIC'); return false;" href="https://eric.ed.gov/?q=spaceship&pg=3&id=EJ517874"><span>Productive School Culture: Principals Working from the Inside.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Karpicke, Herbert; Murphy, Mary E.</p> <p>1996-01-01</p> <p>A positive climate is characterized by a comfortable, orderly, and safe environment. A healthy culture exists when all stakeholders understand an organization's goals and purposes and work productively to achieve them. This article contrasts the "McSchool" (efficiency-celebrating) cultural model with the spaceship-discovery model,…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPA41A4029M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPA41A4029M"><span>Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moore, B., III</p> <p>2014-12-01</p> <p>Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. Berrien Moore III (University of Oklahoma) The South Central Climate Science Center (CSC) is one of eight regional centers established by the Department of the Interior (DoI) under Secretarial Order 3289 to address the impacts of climate change on America's water, land, and other natural and cultural resources. Under DoI leadership and funding, these CSCs will provide scientific information tools and techniques to study impacts of climate change synthesize and integrate climate change impact data develop tools that the DoI managers and partners can use when managing the DOI's land, water, fish and wildlife, and cultural heritage resources (emphasis added) The network of Climate Science Centers will provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. Note from Webster, a tool is a device for doing work; it makes outcomes more realizable and more cost effective, and, in a word, better. Prior to the existence of CSCs, the university and federal scientific world certainly contained a large "set" of scientists with considerable strength in the physical, biological, natural, and social sciences to address the complexities and interdisciplinary nature of the challenges in the areas of climate variability, change, impacts, and adaptation. However, this set of scientists were hardly an integrated community let alone a focused team, but rather a collection of distinguished researchers, educators, and practitioners that were working with disparate though at times linked objectives, and they were rarely aligning themselves formally to an overarching strategic pathway. In addition, data, models, research results, tools, and products were generally somewhat "disconnected" from the broad range of stakeholders. I should note also that NOAA's Regional Integrated Sciences and Assessments ( RISA) program is an earlier "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. This contribution will discuss the important cultural shift that has flowed from Secretarial Order 3289.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70020928','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70020928"><span>Response of North American freshwater lakes to simulated future climates</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hostetler, S.W.; Small, E.E.</p> <p>1999-01-01</p> <p>We apply a physically based lake model to assess the response of North American lakes to future climate conditions as portrayed by the transient trace-gas simulations conducted with the Max Planck Institute (ECHAM4) and the Canadian Climate Center (CGCM1) atmosphere-ocean general circulation models (A/OGCMs). To quantify spatial patterns of lake responses (temperature, mixing, ice cover, evaporation) we ran the lake model for theoretical lakes of specified area, depth, and transparency over a uniformly spaced (50 km) grid. The simulations were conducted for two 10-year periods that represent present climatic conditions and those around the time of CO2 doubling. Although the climate model output produces simulated lake responses that differ in specific regional details, there is broad agreement with regard to the direction and area of change. In particular, lake temperatures are generally warmer in the future as a result of warmer climatic conditions and a substantial loss (> 100 days/yr) of winter ice cover. Simulated summer lake temperatures are higher than 30??C ever the Midwest and south, suggesting the potential for future disturbance of existing aquatic ecosystems. Overall increases in lake evaporation combine with disparate changes in A/OGCM precipitation to produce future changes in net moisture (precipitation minus evaporation) that are of less fidelity than those of lake temperature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.B31A1089C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.B31A1089C"><span>Assessment of the Effect of Climate Change on Grain Yields in China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chou, J.</p> <p>2006-12-01</p> <p>The paper elaborates the social background and research background; makes clear what the key scientific issues need to be resolved and where the difficulties are. In the research area of parasailing the grain yield change caused by climate change, massive works have been done both in the domestic and in the foreign. It is our upcoming work to evaluate how our countrywide climate change information provided by this pattern influence our economic and social development; and how to make related policies and countermeasures. the main idea in this paper is that the grain yield change is by no means the linear composition of social economy function effect and the climatic change function effect. This paper identifies the economic evaluation object, proposes one new concept - climate change output. The grain yields change affected by the social factors and the climatic change working together. Climate change influences the grain yields by the non ¨C linear function from both climate change and social factor changes, not only by climate change itself. Therefore, in my paper, the appraisal object is defined as: The social factors change based on actual social changing situations; under the two kinds of climate change situation, the invariable climate change situation and variable climate change situation; the difference of grain yield outputs is called " climate change output ", In order to solve this problem, we propose a method to analyze and imitate on the historical materials. Giving the condition that the climate is invariable, the social economic factor changes cause the grain yield change. However, this grain yield change is a tentative quantity index, not an actual quantity number. So we use the existing historical materials to exam the climate change output, based on the characteristic that social factor changes greater in year than in age, but the climate factor changes greater in age than in year. The paper proposes and establishes one economy - climate model (C-D-C model) to appraise the grain yield change caused by the climatic change. Also the preliminary test on this model has been done. In selection of the appraisal methods, we take the C-D production function model, which has been proved more mature in the economic research, as our fundamental model. Then, we introduce climate index (arid index) to the C-D model to develop one new model. This new model utilizes the climatic change factor in the economical model to appraise how the climatic change influence the grain yield change. The new way of appraise should have the better application prospect. The economy - climate model (The C-D-C model) has been applied on the eight Chinese regions that we divide; it has been proved satisfactory in its feasibility, rationality and the application prospect. So we can provide the theoretical fundamentals for policy-making under the more complex and uncertain climate change. Therefore, we open a new possible channel for the global climate change research moving toward the actual social, economic life.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1981Icar...47..112H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1981Icar...47..112H"><span>Liquid water on Mars - an energy balance climate model for CO2/H2O atmospheres</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hoffert, M. I.; Callegari, A. J.; Hsieh, T.; Ziegler, W.</p> <p>1981-07-01</p> <p>A simple climatic model is developed for a Mars atmosphere containing CO2 and sufficient liquid water to account for the observed hydrologic surface features by the existence of a CO2/H2O greenhouse effect. A latitude-resolved climate model originally devised for terrestrial climate studies is applied to Martian conditions, with the difference between absorbed solar flux and emitted long-wave flux to space per unit area attributed to the divergence of the meridional heat flux and the poleward heat flux assumed to equal the atmospheric eddy heat flux. The global mean energy balance is calculated as a function of atmospheric pressure to assess the CO2/H2O greenhouse liquid water hypothesis, and some latitude-resolved cases are examined in detail in order to clarify the role of atmospheric transport and temperature-albedo feedback. It is shown that the combined CO2/H2O greenhouse at plausible early surface pressures may account for climates hot enough to support a hydrological cycle and running water at present-day insolation and visible albedo levels.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820029400&hterms=CO2+H2O&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DCO2%2BH2O','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820029400&hterms=CO2+H2O&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DCO2%2BH2O"><span>Liquid water on Mars - An energy balance climate model for CO2/H2O atmospheres</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hoffert, M. I.; Callegari, A. J.; Hsieh, C. T.; Ziegler, W.</p> <p>1981-01-01</p> <p>A simple climatic model is developed for a Mars atmosphere containing CO2 and sufficient liquid water to account for the observed hydrologic surface features by the existence of a CO2/H2O greenhouse effect. A latitude-resolved climate model originally devised for terrestrial climate studies is applied to Martian conditions, with the difference between absorbed solar flux and emitted long-wave flux to space per unit area attributed to the divergence of the meridional heat flux and the poleward heat flux assumed to equal the atmospheric eddy heat flux. The global mean energy balance is calculated as a function of atmospheric pressure to assess the CO2/H2O greenhouse liquid water hypothesis, and some latitude-resolved cases are examined in detail in order to clarify the role of atmospheric transport and temperature-albedo feedback. It is shown that the combined CO2/H2O greenhouse at plausible early surface pressures may account for climates hot enough to support a hydrological cycle and running water at present-day insolation and visible albedo levels.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA43A2185B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA43A2185B"><span>Urban Climate Resilience - Connecting climate models with decision support cyberinfrastructure using open standards</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bermudez, L. E.; Percivall, G.; Idol, T. A.</p> <p>2015-12-01</p> <p>Experts in climate modeling, remote sensing of the Earth, and cyber infrastructure must work together in order to make climate predictions available to decision makers. Such experts and decision makers worked together in the Open Geospatial Consortium's (OGC) Testbed 11 to address a scenario of population displacement by coastal inundation due to the predicted sea level rise. In a Policy Fact Sheet "Harnessing Climate Data to Boost Ecosystem & Water Resilience", issued by White House Office of Science and Technology (OSTP) in December 2014, OGC committed to increase access to climate change information using open standards. In July 2015, the OGC Testbed 11 Urban Climate Resilience activity delivered on that commitment with open standards based support for climate-change preparedness. Using open standards such as the OGC Web Coverage Service and Web Processing Service and the NetCDF and GMLJP2 encoding standards, Testbed 11 deployed an interoperable high-resolution flood model to bring climate model outputs together with global change assessment models and other remote sensing data for decision support. Methods to confirm model predictions and to allow "what-if-scenarios" included in-situ sensor webs and crowdsourcing. A scenario was in two locations: San Francisco Bay Area and Mozambique. The scenarios demonstrated interoperation and capabilities of open geospatial specifications in supporting data services and processing services. The resultant High Resolution Flood Information System addressed access and control of simulation models and high-resolution data in an open, worldwide, collaborative Web environment. The scenarios examined the feasibility and capability of existing OGC geospatial Web service specifications in supporting the on-demand, dynamic serving of flood information from models with forecasting capacity. Results of this testbed included identification of standards and best practices that help researchers and cities deal with climate-related issues. Results of the testbeds will now be deployed in pilot applications. The testbed also identified areas of additional development needed to help identify scientific investments and cyberinfrastructure approaches needed to improve the application of climate science research results to urban climate resilence.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27624169','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27624169"><span>Modeling the impact of climate change on wild Piper nigrum (Black Pepper) in Western Ghats, India using ecological niche models.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sen, Sandeep; Gode, Ameya; Ramanujam, Srirama; Ravikanth, G; Aravind, N A</p> <p>2016-11-01</p> <p>The center of diversity of Piper nigrum L. (Black Pepper), one of the highly valued spice crops is reported to be from India. Black pepper is naturally distributed in India in the Western Ghats biodiversity hotspot and is the only known existing source of its wild germplasm in the world. We used ecological niche models to predict the potential distribution of wild P. nigrum in the present and two future climate change scenarios viz (A1B) and (A2A) for the year 2080. Three topographic and nine uncorrelated bioclim variables were used to develop the niche models. The environmental variables influencing the distribution of wild P. nigrum across different climate change scenarios were identified. We also assessed the direction and magnitude of the niche centroid shift and the change in niche breadth to estimate the impact of projected climate change on the distribution of P. nigrum. The study shows a niche centroid shift in the future climate scenarios. Both the projected future climate scenarios predicted a reduction in the habitat of P. nigrum in Southern Western Ghats, which harbors many wild accessions of P. nigrum. Our results highlight the impact of future climate change on P. nigrum and provide useful information for designing sound germplasm conservation strategies for P. nigrum.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMPA13C1350H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMPA13C1350H"><span>The Nested Regional Climate Model: An Approach Toward Prediction Across Scales</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hurrell, J. W.; Holland, G. J.; Large, W. G.</p> <p>2008-12-01</p> <p>The reality of global climate change has become accepted and society is rapidly moving to questions of consequences on space and time scales that are relevant to proper planning and development of adaptation strategies. There are a number of urgent challenges for the scientific community related to improved and more detailed predictions of regional climate change on decadal time scales. Two important examples are potential impacts of climate change on North Atlantic hurricane activity and on water resources over the intermountain West. The latter is dominated by complex topography, so that accurate simulations of regional climate variability and change require much finer spatial resolution than is provided with state-of-the-art climate models. Climate models also do not explicitly resolve tropical cyclones, even though these storms have dramatic societal impacts and play an important role in regulating climate. Moreover, the debate over the impact of global warming on tropical cyclones has at times been acrimonious, and the lack of hard evidence has left open opportunities for misinterpretation and justification of pre-existing beliefs. These and similar topics are being assessed at NCAR, in partnership with university colleagues, through the development of a Nested Regional Climate Model (NRCM). This is an ambitious effort to combine a state of the science mesoscale weather model (WRF), a high resolution regional ocean modeling system (ROMS), and a climate model (CCSM) to better simulate the complex, multi-scale interactions intrinsic to atmospheric and oceanic fluid motions that are limiting our ability to predict likely future changes in regional weather statistics and climate. The NRCM effort is attracting a large base of earth system scientists together with societal groups as diverse as the Western Governor's Association and the offshore oil industry. All of these groups require climate data on scales of a few kilometers (or less), so that the NRCM program is producing unique data sets of climate change scenarios of immense interest. In addition, all simulations are archived in a form that will be readily accessible to other researchers, thus enabling a wider group to investigate these important issues.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27222566','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27222566"><span>Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Seinfeld, John H; Bretherton, Christopher; Carslaw, Kenneth S; Coe, Hugh; DeMott, Paul J; Dunlea, Edward J; Feingold, Graham; Ghan, Steven; Guenther, Alex B; Kahn, Ralph; Kraucunas, Ian; Kreidenweis, Sonia M; Molina, Mario J; Nenes, Athanasios; Penner, Joyce E; Prather, Kimberly A; Ramanathan, V; Ramaswamy, Venkatachalam; Rasch, Philip J; Ravishankara, A R; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert</p> <p>2016-05-24</p> <p>The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170001439&hterms=1091&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3D%2526%25231091','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170001439&hterms=1091&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3D%2526%25231091"><span>Improving Our Fundamental Understanding of the Role of Aerosol Cloud Interactions in the Climate System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kahn, Ralph; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170001439'); toggleEditAbsImage('author_20170001439_show'); toggleEditAbsImage('author_20170001439_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170001439_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170001439_hide"></p> <p>2016-01-01</p> <p>The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth's clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1327134-improving-our-fundamental-understanding-role-aerosol-cloud-interactions-climate-system','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1327134-improving-our-fundamental-understanding-role-aerosol-cloud-interactions-climate-system"><span>Improving our fundamental understanding of the role of aerosol-cloud interactions in the climate system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; ...</p> <p>2016-05-24</p> <p>The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from pre-industrial time. General Circulation Models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol-cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions but significant challengesmore » exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol-cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. Lastly, we suggest strategies for improving estimates of aerosol-cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4889348','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4889348"><span>Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Seinfeld, John H.; Bretherton, Christopher; Carslaw, Kenneth S.; Coe, Hugh; DeMott, Paul J.; Dunlea, Edward J.; Feingold, Graham; Ghan, Steven; Guenther, Alex B.; Kraucunas, Ian; Molina, Mario J.; Nenes, Athanasios; Penner, Joyce E.; Prather, Kimberly A.; Ramanathan, V.; Ramaswamy, Venkatachalam; Rasch, Philip J.; Ravishankara, A. R.; Rosenfeld, Daniel; Stephens, Graeme; Wood, Robert</p> <p>2016-01-01</p> <p>The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty. PMID:27222566</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC53F..06G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC53F..06G"><span>Simulated Near-term Climate Change Impacts on Major Crops across Latin America and the Caribbean</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gourdji, S.; Mesa-Diez, J.; Obando-Bonilla, D.; Navarro-Racines, C.; Moreno, P.; Fisher, M.; Prager, S.; Ramirez-Villegas, J.</p> <p>2016-12-01</p> <p>Robust estimates of climate change impacts on agricultural production can help to direct investments in adaptation in the coming decades. In this study commissioned by the Inter-American Development Bank, near-term climate change impacts (2020-2049) are simulated relative to a historical baseline period (1971-2000) for five major crops (maize, rice, wheat, soybean and dry bean) across Latin America and the Caribbean (LAC) using the DSSAT crop model. No adaptation or technological change is assumed, thereby providing an analysis of existing climatic stresses on yields in the region and a worst-case scenario in the coming decades. DSSAT is run across irrigated and rain-fed growing areas in the region at a 0.5° spatial resolution for each crop. Crop model inputs for soils, planting dates, crop varieties and fertilizer applications are taken from previously-published datasets, and also optimized for this study. Results show that maize and dry bean are the crops most affected by climate change, followed by wheat, with only minimal changes for rice and soybean. Generally, rain-fed production sees more severe yield declines than irrigated production, although large increases in irrigation water are needed to maintain yields, reducing the yield-irrigation productivity in most areas and potentially exacerbating existing supply limitations in watersheds. This is especially true for rice and soybean, the two crops showing the most neutral yield changes. Rain-fed yields for maize and bean are projected to decline most severely in the sub-tropical Caribbean, Central America and northern South America, where climate models show a consistent drying trend. Crop failures are also projected to increase in these areas, necessitating switches to other crops or investment in adaptation measures. Generally, investment in agricultural adaptation to climate change (such as improved seed and irrigation infrastructure) will be needed throughout the LAC region in the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.H23G1306C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.H23G1306C"><span>Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Castro, C. L.; Dominguez, F.; Chang, H.</p> <p>2010-12-01</p> <p>Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5483041','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5483041"><span>Climate, soil or both? Which variables are better predictors of the distributions of Australian shrub species?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Esperón-Rodríguez, Manuel; Baumgartner, John B.; Beaumont, Linda J.</p> <p>2017-01-01</p> <p>Background Shrubs play a key role in biogeochemical cycles, prevent soil and water erosion, provide forage for livestock, and are a source of food, wood and non-wood products. However, despite their ecological and societal importance, the influence of different environmental variables on shrub distributions remains unclear. We evaluated the influence of climate and soil characteristics, and whether including soil variables improved the performance of a species distribution model (SDM), Maxent. Methods This study assessed variation in predictions of environmental suitability for 29 Australian shrub species (representing dominant members of six shrubland classes) due to the use of alternative sets of predictor variables. Models were calibrated with (1) climate variables only, (2) climate and soil variables, and (3) soil variables only. Results The predictive power of SDMs differed substantially across species, but generally models calibrated with both climate and soil data performed better than those calibrated only with climate variables. Models calibrated solely with soil variables were the least accurate. We found regional differences in potential shrub species richness across Australia due to the use of different sets of variables. Conclusions Our study provides evidence that predicted patterns of species richness may be sensitive to the choice of predictor set when multiple, plausible alternatives exist, and demonstrates the importance of considering soil properties when modeling availability of habitat for plants. PMID:28652933</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814326F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814326F"><span>Multi-disciplinary assessments of climate change impacts on agriculture to support adaptation decision making in developing countries</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fujisawa, Mariko; Kanamaru, Hideki</p> <p>2016-04-01</p> <p>Many existing climate change impact studies, carried out by academic researchers, are disconnected from decision making processes of stakeholders. On the other hand many climate change adaptation projects in developing countries lack a solid evidence base of current and future climate impacts as well as vulnerabilities assessment at different scales. In order to fill this information gap, FAO has developed and implemented a tool "MOSAICC (Modelling System for Agricultural Impacts of Climate Change)" in several developing countries such as Morocco, the Philippines and Peru, and recently in Malawi and Zambia. MOSAICC employs a multi-disciplinary assessment approach to addressing climate change impacts and adaptation planning in the agriculture and food security sectors, and integrates five components from different academic disciplines: 1. Statistical downscaling of climate change projections, 2. Yield simulation of major crops at regional scale under climate change, 3. Surface hydrology simulation model, 4. Macroeconomic model, and 5. Forestry model. Furthermore MOSAICC has been developed as a capacity development tool for the national scientists so that they can conduct the country assessment themselves, using their own data, and reflect the outcome into the national adaptation policies. The outputs are nation-wide coverage, disaggregated at sub-national level to support strategic planning, investments and decisions by national policy makers. MOSAICC is designed in such a way to promote stakeholders' participation and strengthen technical capacities in developing countries. The paper presents MOSAICC and projects that used MOSAICC as a tool with case studies from countries.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/47187','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/47187"><span>Climate change and land use drivers of fecal bacteria in tropical Hawaiian rivers</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Ayron M. Strauch; Richard A. Mackenzie; Gregory L. Bruland; Ralph Tingley; Christian P. Giardina</p> <p>2014-01-01</p> <p>Potential shifts in rainfall driven by climate change are anticipated to affect watershed processes (e.g., soil moisture, runoff, stream flow), yet few model systems exist in the tropics to test hypotheses about how these processes may respond to these shifts. We used a sequence of nine watersheds on Hawaii Island spanning 3000 mm (7500–4500 mm) of mean annual rainfall...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5434087','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5434087"><span>Extreme weather and climate events with ecological relevance: a review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Meehl, Gerald A.</p> <p>2017-01-01</p> <p>Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28483866','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28483866"><span>Extreme weather and climate events with ecological relevance: a review.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ummenhofer, Caroline C; Meehl, Gerald A</p> <p>2017-06-19</p> <p>Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23D2396B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23D2396B"><span>Causes of Cool-Season Precipitation Bias in the East South Central U.S.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bukovsky, M. S.; McCrary, R. R.; Rendfrey, T. S.; Schroeder, A. D.; Mearns, L.</p> <p>2017-12-01</p> <p>A climatological maximum in cool-season precipitation, secondary to that in the Pacific Northwest, exists in the East South Central U.S. region (ESC). Many regional climate simulations have difficulty reproducing this maximum, whether forced with a reanalysis or global climate model (GCM). This problem exists in some, but not all, of the simulations completed for the North American component of CORDEX (Coordinated Regional Downscaling Experiment) and NARCCAP (North American Regional Climate Change Assessment Program). We use both of these ensembles of regional climate model (RCM) simulations to examine precipitation and some of the factors that govern its climatology in this region to develop a better understanding of why some simulations perform better than others. The ESC roughly encompasses the Lower Mississippi, western South Atlantic, southern Ohio and Tennessee hydrologic regions. Cool-season precipitation (November-April) in the ESC is often convective in nature and strongly forced. In this presentation, we will examine some of the potential causes of the climatological precipitation bias for this region, including bias in: sea-surface temperature, moisture flux, El Nino-Southern Oscillation teleconnections, and the climatology of extratropical cyclones. We will also examine simulation configurations to identify any common threads between the simulations that perform better and those that perform worse.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040031738&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040031738&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dclimate%2Bchange%2Banthropogenic"><span>Status of Middle Atmosphere-Climate Models: Results SPARC-GRIPS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pawson, Steven; Kodera, Kunihiko</p> <p>2003-01-01</p> <p>The middle atmosphere is an important component of the climate system, primarily because of the radiative forcing of ozone. Middle atmospheric ozone can change, over long times, because of changes in the abundance of anthropogenic pollutants which catalytically destroy it, and because of the temperature sensitivity of kinetic reaction rates. There is thus a complex interaction between ozone, involving chemical and climatic mechanisms. One question of interest is how ozone will change over the next decades , as the "greenhouse-gas cooling" of the middle atmosphere increases but the concentrations of chlorine species decreases (because of policy changes). concerns the climate biases in current middle atmosphere-climate models, especially their ability to simulate the correct seasonal cycle at high latitudes, and the existence of temperature biases in the global mean. A major obstacle when addressing this question This paper will present a summary of recent results from the "GCM-Reality Intercomparison Project for SPARC" (GRIPS) initiative. A set of middle atmosphere-climate models has been compared, identifying common biases. Mechanisms for these biases are being studied in some detail, including off-line assessments of the radiation transfer codes and coordinated studies of the impacts of gravity wave drag due to sub-grid-scale processes. ensemble of models will be presented, along with numerical experiments undertaken with one or more models, designed to investigate the mechanisms at work in the atmosphere. The discussion will focus on dynamical and radiative mechanisms in the current climate, but implications for coupled ozone chemistry and the future climate will be assessed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=336580&keyword=climate%20change&subject=climate%20change%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=06/02/2012&dateendpublishedpresented=06/02/2017&sortby=pubdateyear','PESTICIDES'); return false;" href="https://cfpub.epa.gov/si/si_public_record_report.cfm?direntryid=336580&keyword=climate%20change&subject=climate%20change%20research&showcriteria=2&fed_org_id=111&datebeginpublishedpresented=06/02/2012&dateendpublishedpresented=06/02/2017&sortby=pubdateyear"><span>Characterizing the impact of projected changes in climate and ...</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.epa.gov/pesticides/search.htm">EPA Pesticide Factsheets</a></p> <p></p> <p></p> <p>The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O3) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O3 are much larger than the impacts of changing demographics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A13C0224V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A13C0224V"><span>The ARM Climate Research Facility - New Capabilities and the Expected Impacts on Climate Science and Modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Voyles, J.; Mather, J. H.</p> <p>2010-12-01</p> <p>The ARM Climate Research Facility is a Department of Energy national scientific user facility. Research sites include fixed and mobile facilities, which collect research quality data for climate research. Through the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy’s Office of Science allocated $60 million to the ARM Climate Research Facility for the purchase of instruments and improvement of research sites. With these funds, ARM is in the process of deploying a broad variety of new instruments that will greatly enhance the measurement capabilities of the facility. New instruments being purchased include dual-frequency scanning cloud radars, scanning precipitation radars, Doppler lidars, a mobile Aerosol Observing System and many others. A list of instruments being purchased is available at http://www.arm.gov/about/recovery-act. Orders for all instruments have now been placed and activities are underway to integrate these new systems with our research sites. The overarching goal is to provide instantaneous and statistical measurements of the climate that can be used to advance the physical understanding and predictive performance of climate models. The Recovery Act investments enable the ARM Climate Research Facility to enhance existing and add new measurements, which enable a more complete understanding of the 3-dimensional evolution of cloud processes and related atmospheric properties. Understanding cloud processes are important globally, to reduce climate-modeling uncertainties and help improve our nation’s ability to manage climate impacts. Domer Plot of W-Band Reflectivity</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002JGRE..107.5094N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002JGRE..107.5094N"><span>Stability of the Martian climate system under the seasonal change condition of solar radiation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nakamura, Takasumi; Tajika, Eiichi</p> <p>2002-11-01</p> <p>Previous studies on stability of the Martian climate system used essentially zero-dimensional energy balance climate models (EBMs) under the condition of annual mean solar radiation income. However, areal extent of polar ice caps should affect the Martian climate through the energy balance and the CO2 budget, and results under the seasonal change condition of solar radiation will be different from those under the annual mean condition. We therefore construct a one-dimensional energy balance climate model with CO2-dependent outgoing radiation, seasonal changes of solar radiation income, changes of areal extent of CO2 ice caps, and adsorption of CO2 by regolith. We have investigated behaviors of the Martian climate system and, in particular, examined the effect of the seasonal changes of solar radiation by comparing the results of previous studies under the condition of annual mean solar radiation. One of the major discrepancies between them is the condition for multiple solutions of the Martian climate system. Although the Martian climate system always has multiple solutions under the annual mean condition, under the seasonal change condition, existence of multiple solutions depends on the present amounts of CO2 in the ice caps and the regolith.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED31A0273T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED31A0273T"><span>A Faculty Workshop Model to Integrate Climate Change across the Curriculum</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Teranes, J. L.</p> <p>2017-12-01</p> <p>Much of the growing scientific certainty of human impacts on the climate system, and the implications of these impacts on current and future generations, have been discovered and documented in research labs in colleges and universities across the country. Often these institutions also take decisive action towards combatting climate change, by making significant reductions in greenhouse emissions and pledging to greater future reductions. Yet, there are still far too many students that graduate from these campuses without an adequate understanding of how climate change will impact them within their lifetimes and without adequate workforce preparation to implement solutions. It may be that where college and universities still have the largest influence on climate change adaption and mitigation is in the way that we educate students. Here I present a curriculum workshop model at UC San Diego that leverages faculty expertise to infuse climate change education across disciplines to enhance UC San Diego students' climate literacy, particularly for those students whose major focus is not in the geosciences. In this model, twenty faculty from a breadth of disciplines, including social sciences, humanities, arts, education, and natural sciences participated in workshops and developed curricula to infuse aspects of climate change into their existing undergraduate courses. We particularly encouraged development of climate change modules in courses in the humanities, social sciences and arts that are best positioned to address the important human and social dimensions of climate change. In this way, climate change content becomes embedded in current course offerings, including non-science courses, to increase climate literacy among a greater number and a broader cross-section of students.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA43B0321D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA43B0321D"><span>Examining the Performance of Statistical Downscaling Methods: Toward Matching Applications to Data Products</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dixon, K. W.; Lanzante, J. R.; Adams-Smith, D.</p> <p>2017-12-01</p> <p>Several challenges exist when seeking to use future climate model projections in a climate impacts study. A not uncommon approach is to utilize climate projection data sets derived from more than one future emissions scenario and from multiple global climate models (GCMs). The range of future climate responses represented in the set is sometimes taken to be indicative of levels of uncertainty in the projections. Yet, GCM outputs are deemed to be unsuitable for direct use in many climate impacts applications. GCM grids typically are viewed as being too coarse. Additionally, regional or local-scale biases in a GCM's simulation of the contemporary climate that may not be problematic from a global climate modeling perspective may be unacceptably large for a climate impacts application. Statistical downscaling (SD) of climate projections - a type of post-processing that uses observations to inform the refinement of GCM projections - is often used in an attempt to account for GCM biases and to provide additional spatial detail. "What downscaled climate projection is the best one to use" is a frequently asked question, but one that is not always easy to answer, as it can be dependent on stakeholder needs and expectations. Here we present results from a perfect model experimental design illustrating how SD method performance can vary not only by SD method, but how performance can also vary by location, season, climate variable of interest, amount of projected climate change, SD configuration choices, and whether one is interested in central tendencies or the tails of the distribution. Awareness of these factors can be helpful when seeking to determine the suitability of downscaled climate projections for specific climate impacts applications. It also points to the potential value of considering more than one SD data product in a study, so as to acknowledge uncertainties associated with the strengths and weaknesses of different downscaling methods.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1512371L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512371L"><span>Changing Permafrost in the Arctic and its Global Effects in the 21st Century (PAGE21): A very large international and integrated project to measure the impact of permafrost degradation on the climate system</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lantuit, Hugues; Boike, Julia; Dahms, Melanie; Hubberten, Hans-Wolfgang</p> <p>2013-04-01</p> <p>The northern permafrost region contains approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmos-pheric carbon pool. The sheer size of this carbon pool, together with the large amplitude of predicted arctic climate change im-plies that there is a high potential for global-scale feedbacks from arctic climate change if these carbon reservoirs are desta-bilized. Nonetheless, significant gaps exist in our current state of knowledge that prevent us from producing accurate assess-ments of the vulnerability of the arctic permafrost to climate change, or of the implications of future climate change for global greenhouse gas (GHG) emissions. Specifically: • Our understanding of the physical and biogeochemical processes at play in permafrost areas is still insuffi-cient in some key aspects • Size estimates for the high latitude continental carbon and nitrogen stocks vary widely between regions and research groups. • The representation of permafrost-related processes in global climate models still tends to be rudimentary, and is one reason for the frequently poor perform-ances of climate models at high latitudes. The key objectives of PAGE21 are: • to improve our understanding of the processes affect-ing the size of the arctic permafrost carbon and nitro-gen pools through detailed field studies and monitor-ing, in order to quantify their size and their vulnerability to climate change, • to produce, assemble and assess high-quality datasets in order to develop and evaluate representations of permafrost and related processes in global models, • to improve these models accordingly, • to use these models to reduce the uncertainties in feed-backs from arctic permafrost to global change, thereby providing the means to assess the feasibility of stabili-zation scenarios, and • to ensure widespread dissemination of our results in order to provide direct input into the ongoing debate on climate-change mitigation. The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, proc-ess studies and modeling on the pertinent temporal and spatial scales. Field sites have been selected to cover a wide range of environmental conditions for the validation of large scale mod-els, the development of permafrost monitoring capabilities, the study of permafrost processes, and for overlap with existing monitoring programs. PAGE21 will contribute to upgrading the project sites with the objective of providing a measurement baseline, both for process studies and for modeling programs. PAGE21 is determined to break down the traditional barriers in permafrost sciences between observational and model-supported site studies and large-scale climate modeling. Our concept for the interaction between site-scale studies and large-scale modeling is to establish and maintain a direct link be-tween these two areas for developing and evaluating, on all spatial scales, the land-surface modules of leading European global climate models taking part in the Coupled Model Inter-comparison Project Phase 5 (CMIP5), designed to inform the IPCC process. The timing of this project is such that the main scientific results from PAGE21, and in particular the model-based assessments will build entirely on new outputs and results from the CMIP5 Climate Model Intercomparison Project designed to inform the IPCC Fifth Assessment Report. However, PAGE21 is designed to leave a legacy that will en-dure beyond the lifetime of the projections that it produces. This legacy will comprise • an improved understanding of the key processes and parameters that determine the vulnerability of arctic permafrost to climate change, • the production of a suite of major European coupled climate models including detailed and validated repre-sentations of permafrost-related processes, that will reduce uncertainties in future climate projections pro-duced well beyond the lifetime of PAGE21, and • the training of a new generation of permafrost scien-tists who will bridge the long-standing gap between permafrost field science and global climate modeling, for the long-term benefit of science and society.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.8367S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.8367S"><span>Cost Analysis of Water Transport for Climate Change Impact Assessment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Szaleniec, V.; Buytaert, W.</p> <p>2012-04-01</p> <p>It is expected that climate change will have a strong impact on water resources worldwide. Many studies exist that couple the output of global climate models with hydrological models to assess the impact of climate change on physical water availability. However, the water resources topology of many regions and especially that of cities can be very complex. Changes in physical water availability do therefore not translate easily into impacts on water resources for cities. This is especially the case for cities with a complex water supply topology, for instance because of geographical barriers, strong gradients in precipitation patterns, or competing water uses. In this study we explore the use of cost maps to enable the inclusion of water supply topologies in climate change impact studies. We use the city of Lima as a case study. Lima is the second largest desert city in the world. Although Peru as a whole has no water shortage, extreme gradients exist. Most of the economic activities including the city of Lima are located in the coastal desert. This region is geographically disconnected from the wet Amazon basin because of the Andes mountain range. Hence, water supply is precarious, provided by a complex combination of high mountain ecosystems including wetlands and glaciers, as well as groundwater aquifers depending on recharge from the mountains. We investigate the feasibility and costs of different water abstraction scenarios and the impact of climate change using cost functions for different resources. The option of building inter basins tunnels across the Andes is compared to the costs of desalinating seawater from the Pacific Ocean under different climate change scenarios and population growth scenarios. This approach yields recommendations for the most cost-effective options for the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820017703&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820017703&hterms=seasonal+forecast&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dseasonal%2Bforecast"><span>The seasonal-cycle climate model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Marx, L.; Randall, D. A.</p> <p>1981-01-01</p> <p>The seasonal cycle run which will become the control run for the comparison with runs utilizing codes and parameterizations developed by outside investigators is discussed. The climate model currently exists in two parallel versions: one running on the Amdahl and the other running on the CYBER 203. These two versions are as nearly identical as machine capability and the requirement for high speed performance will allow. Developmental changes are made on the Amdahl/CMS version for ease of testing and rapidity of turnaround. The changes are subsequently incorporated into the CYBER 203 version using vectorization techniques where speed improvement can be realized. The 400 day seasonal cycle run serves as a control run for both medium and long range climate forecasts alsensitivity studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN53A0079B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN53A0079B"><span>Climate Classification is an Important Factor in ­Assessing Hospital Performance Metrics</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boland, M. R.; Parhi, P.; Gentine, P.; Tatonetti, N. P.</p> <p>2017-12-01</p> <p>Context/Purpose: Climate is a known modulator of disease, but its impact on hospital performance metrics remains unstudied. Methods: We assess the relationship between Köppen-Geiger climate classification and hospital performance metrics, specifically 30-day mortality, as reported in Hospital Compare, and collected for the period July 2013 through June 2014 (7/1/2013 - 06/30/2014). A hospital-level multivariate linear regression analysis was performed while controlling for known socioeconomic factors to explore the relationship between all-cause mortality and climate. Hospital performance scores were obtained from 4,524 hospitals belonging to 15 distinct Köppen-Geiger climates and 2,373 unique counties. Results: Model results revealed that hospital performance metrics for mortality showed significant climate dependence (p<0.001) after adjusting for socioeconomic factors. Interpretation: Currently, hospitals are reimbursed by Governmental agencies using 30-day mortality rates along with 30-day readmission rates. These metrics allow Government agencies to rank hospitals according to their `performance' along these metrics. Various socioeconomic factors are taken into consideration when determining individual hospitals performance. However, no climate-based adjustment is made within the existing framework. Our results indicate that climate-based variability in 30-day mortality rates does exist even after socioeconomic confounder adjustment. Use of standardized high-level climate classification systems (such as Koppen-Geiger) would be useful to incorporate in future metrics. Conclusion: Climate is a significant factor in evaluating hospital 30-day mortality rates. These results demonstrate that climate classification is an important factor when comparing hospital performance across the United States.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=Usability&pg=5&id=EJ1038402','ERIC'); return false;" href="https://eric.ed.gov/?q=Usability&pg=5&id=EJ1038402"><span>Evaluating the Usability of a Professional Modeling Tool Repurposed for Middle School Learning</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Peters, Vanessa L.; Songer, Nancy Butler</p> <p>2013-01-01</p> <p>This paper reports the results of a three-stage usability test of a modeling tool designed to support learners' deep understanding of the impacts of climate change on ecosystems. The design process involved repurposing an existing modeling technology used by professional scientists into a learning tool specifically designed for middle school…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27500587','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27500587"><span>Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P</p> <p>2017-03-01</p> <p>How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70176315','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70176315"><span>Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.</p> <p>2017-01-01</p> <p>How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.B41G0532Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.B41G0532Y"><span>Integration of climatic water deficit and fine-scale physiography in process-based modeling of forest landscape resilience to large-scale tree mortality</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yang, J.; Weisberg, P.; Dilts, T.</p> <p>2016-12-01</p> <p>Climate warming can lead to large-scale drought-induced tree mortality events and greatly affect forest landscape resilience. Climatic water deficit (CWD) and its physiographic variations provide a key mechanism in driving landscape dynamics in response to climate change. Although CWD has been successfully applied in niche-based species distribution models, its application in process-based forest landscape models is still scarce. Here we present a framework incorporating fine-scale influence of terrain on ecohydrology in modeling forest landscape dynamics. We integrated CWD with a forest landscape succession and disturbance model (LANDIS-II) to evaluate how tree species distribution might shift in response to different climate-fire scenarios across an elevation-aspect gradient in a semi-arid montane landscape of northeastern Nevada, USA. Our simulations indicated that drought-intolerant tree species such as quaking aspen could experience greatly reduced distributions in the more arid portions of their existing ranges due to water stress limitations under future climate warming scenarios. However, even at the most xeric portions of its range, aspen is likely to persist in certain environmental settings due to unique and often fine-scale combinations of resource availability, species interactions and disturbance regime. The modeling approach presented here allowed identification of these refugia. In addition, this approach helped quantify how the direction and magnitude of fire influences on species distribution would vary across topoclimatic gradients, as well as furthers our understanding on the role of environmental conditions, fire, and inter-specific competition in shaping potential responses of landscape resilience to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN14A..08E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN14A..08E"><span>Generating and Visualizing Climate Indices using Google Earth Engine</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Erickson, T. A.; Guentchev, G.; Rood, R. B.</p> <p>2017-12-01</p> <p>Climate change is expected to have largest impacts on regional and local scales. Relevant and credible climate information is needed to support the planning and adaptation efforts in our communities. The volume of climate projections of temperature and precipitation is steadily increasing, as datasets are being generated on finer spatial and temporal grids with an increasing number of ensembles to characterize uncertainty. Despite advancements in tools for querying and retrieving subsets of these large, multi-dimensional datasets, ease of access remains a barrier for many existing and potential users who want to derive useful information from these data, particularly for those outside of the climate modelling research community. Climate indices, that can be derived from daily temperature and precipitation data, such as annual number of frost days or growing season length, can provide useful information to practitioners and stakeholders. For this work the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset was loaded into Google Earth Engine, a cloud-based geospatial processing platform. Algorithms that use the Earth Engine API to generate several climate indices were written. The indices were chosen from the set developed by the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI). Simple user interfaces were created that allow users to query, produce maps and graphs of the indices, as well as download results for additional analyses. These browser-based interfaces could allow users in low-bandwidth environments to access climate information. This research shows that calculating climate indices from global downscaled climate projection datasets and sharing them widely using cloud computing technologies is feasible. Further development will focus on exposing the climate indices to existing applications via the Earth Engine API, and building custom user interfaces for presenting climate indices to a diverse set of user groups.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20429949','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20429949"><span>Climate change: what competencies and which medical education and training approaches?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bell, Erica J</p> <p>2010-04-30</p> <p>Much research has been devoted to identifying healthcare needs in a climate-changing world. However, while there are now global and national policy statements about the importance of health workforce development for climate change, little has been published about what competencies might be demanded of practitioners in a climate-changing world. In such a context, this debate and discussion paper aims to explore the nature of key competencies and related opportunities for teaching climate change in medical education and training. Particular emphasis is made on preparation for practice in rural and remote regions likely to be greatly affected by climate change. The paper describes what kinds of competencies for climate change might be included in medical education and training. It explores which curricula, teaching, learning and assessment approaches might be involved. Rather than arguing for major changes to medical education and training, this paper explores well established precedents to offer practical suggestions for where a particular kind of literacy--eco-medical literacy--and related competencies could be naturally integrated into existing elements of medical education and training. The health effects of climate change have, generally, not yet been integrated into medical education and training systems. However, the necessary competencies could be taught by building on existing models, best practice and innovative traditions in medicine. Even in crowded curricula, climate change offers an opportunity to reinforce and extend understandings of how interactions between people and place affect health.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990063741&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DGlobal%2Bwarming','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990063741&hterms=Global+warming&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DGlobal%2Bwarming"><span>Global Warming: Discussion for EOS Science Writers Workshop</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hansen, James E</p> <p>1999-01-01</p> <p>The existence of global warming this century is no longer an issue of scientific debate. But there are many important questions about the nature and causes of long-term climate change, th roles of nature and human-made climate forcings and unforced (chaotic) climate variability, the practical impacts of climate change, and what, if anything, should be done to reduce global warming, Global warming is not a uniform increase of temperature, but rather involves at complex geographically varying climate change. Understanding of global warming will require improved observations of climate change itself and the forcing factors that can lead to climate change. The NASA Terra mission and other NASA Earth Science missions will provide key measurement of climate change and climate forcings. The strategy to develop an understanding of the causes and predictability of long-term climate change must be based on combination of observations with models and analysis. The upcoming NASA missions will make important contributions to the required observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMOS23E..02F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMOS23E..02F"><span>Assessing the Role of Seafloor Weathering in Global Geochemical Cycling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Farahat, N. X.; Abbot, D. S.; Archer, D. E.</p> <p>2015-12-01</p> <p>Low-temperature alteration of the basaltic upper oceanic crust, known as seafloor weathering, has been proposed as a mechanism for long-term climate regulation similar to the continental climate-weathering negative feedback. Despite this potentially far-reaching impact of seafloor weathering on habitable planet evolution, existing modeling frameworks do not include the full scope of alteration reactions or recent findings of convective flow dynamics. We present a coupled fluid dynamic and geochemical numerical model of low-temperature, off-axis hydrothermal activity. This model is designed to explore the the seafloor weathering flux of carbon to the oceanic crust and its responsiveness to climate fluctuations. The model's ability to reproduce the seafloor weathering environment is evaluated by constructing numerical simulations for comparison with two low-temperature hydrothermal systems: A transect east of the Juan de Fuca Ridge and the southern Costa Rica Rift flank. We explore the sensitivity of carbon uptake by seafloor weathering on climate and geology by varying deep ocean temperature, seawater dissolved inorganic carbon, continental weathering inputs, and basaltic host rock in a suite of numerical experiments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28924607','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28924607"><span>Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Foreman, Brady Z; Straub, Kyle M</p> <p>2017-09-01</p> <p>Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910721H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910721H"><span>Compressing climate model simulations: reducing storage burden while preserving information</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hammerling, Dorit; Baker, Allison; Xu, Haiying; Clyne, John; Li, Samuel</p> <p>2017-04-01</p> <p>Climate models, which are run at high spatial and temporal resolutions, generate massive quantities of data. As our computing capabilities continue to increase, storing all of the generated data is becoming a bottleneck, which negatively affects scientific progress. It is thus important to develop methods for representing the full datasets by smaller compressed versions, which still preserve all the critical information and, as an added benefit, allow for faster read and write operations during analysis work. Traditional lossy compression algorithms, as for example used for image files, are not necessarily ideally suited for climate data. While visual appearance is relevant, climate data has additional critical features such as the preservation of extreme values and spatial and temporal gradients. Developing alternative metrics to quantify information loss in a manner that is meaningful to climate scientists is an ongoing process still in its early stages. We will provide an overview of current efforts to develop such metrics to assess existing algorithms and to guide the development of tailored compression algorithms to address this pressing challenge.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5597307','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5597307"><span>Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Foreman, Brady Z.; Straub, Kyle M.</p> <p>2017-01-01</p> <p>Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110013337','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110013337"><span>Accelerating Climate Simulations Through Hybrid Computing</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark</p> <p>2009-01-01</p> <p>Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28777201','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28777201"><span>Role Stress and Emotional Exhaustion Among Health Care Workers: The Buffering Effect of Supportive Coworker Climate in a Multilevel Perspective.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Portoghese, Igor; Galletta, Maura; Burdorf, Alex; Cocco, Pierluigi; D'Aloja, Ernesto; Campagna, Marcello</p> <p>2017-10-01</p> <p>The aim of the study was to examine the relationship between role stress, emotional exhaustion, and a supportive coworker climate among health care workers, by adopting a multilevel perspective. Aggregated data of 738 health care workers nested within 67 teams of three Italian hospitals were collected. Multilevel regression analysis with a random intercept model was used. Hierarchical linear modeling showed that a lack of role clarity was significantly linked to emotional exhaustion at the individual level. At the unit level, the cross-level interaction revealed that a supportive coworker climate moderated the relationship between lack of role clarity and emotional exhaustion. This study supports previous results of single-level burnout studies, extending the existing literature with evidence on the multidimensional and cross-level interaction associations of a supportive coworker climate as a key aspect of job resources on burnout.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ERL....10b4017W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ERL....10b4017W"><span>How model and input uncertainty impact maize yield simulations in West Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli</p> <p>2015-02-01</p> <p>Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC14A..01S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC14A..01S"><span>Robust Engineering Designs for Infrastructure Adaptation to a Changing Climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Samaras, C.; Cook, L.</p> <p>2015-12-01</p> <p>Infrastructure systems are expected to be functional, durable and safe over long service lives - 50 to over 100 years. Observations and models of climate science show that greenhouse gas emissions resulting from human activities have changed climate, weather and extreme events. Projections of future changes (albeit with uncertainties caused by inadequacies of current climate/weather models) can be made based on scenarios for future emissions, but actual future emissions are themselves uncertain. Most current engineering standards and practices for infrastructure assume that the probabilities of future extreme climate and weather events will match those of the past. Climate science shows that this assumption is invalid, but is unable, at present, to define these probabilities over the service lives of existing and new infrastructure systems. Engineering designs, plans, and institutions and regulations will need to be adaptable for a range of future conditions (conditions of climate, weather and extreme events, as well as changing societal demands for infrastructure services). For their current and future projects, engineers should: Involve all stakeholders (owners, financers, insurance, regulators, affected public, climate/weather scientists, etc.) in key decisions; Use low regret, adaptive strategies, such as robust decision making and the observational method, comply with relevant standards and regulations, and exceed their requirements where appropriate; Publish design studies and performance/failure investigations to extend the body of knowledge for advancement of practice. The engineering community should conduct observational and modeling research with climate/weather/social scientists and the concerned communities and account rationally for climate change in revised engineering standards and codes. This presentation presents initial research on decisionmaking under uncertainty for climate resilient infrastructure design.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1076751','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1076751"><span>Quantifying Climate Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Schlosser, Courtney Adam; Walter-Anthony, Katey; Zhuang, Qianlai</p> <p>2013-04-26</p> <p>Our overall goal was to quantify the potential for threshold changes in natural emission rates of trace gases, particularly methane and carbon dioxide, from pan-arctic terrestrial systems under the spectrum of anthropogenically forced climate warming, and the extent to which these emissions provide a strong feedback mechanism to global climate warming. This goal is motivated under the premise that polar amplification of global climate warming will induce widespread thaw and degradation of the permafrost, and would thus cause substantial changes in the extent of wetlands and lakes, especially thermokarst (thaw) lakes, over the Arctic. Through a coordinated effort of fieldmore » measurements, model development, and numerical experimentation with an integrated assessment model framework, we have investigated the following hypothesis: There exists a climate-warming threshold beyond which permafrost degradation becomes widespread and thus instigates strong and/or sharp increases in methane emissions (via thermokarst lakes and wetland expansion). These would outweigh any increased uptake of carbon (e.g. from peatlands) and would result in a strong, positive feedback to global climate warming.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27326549','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27326549"><span>Measuring Workplace Climate in Community Clinics and Health Centers.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Friedberg, Mark W; Rodriguez, Hector P; Martsolf, Grant R; Edelen, Maria O; Vargas Bustamante, Arturo</p> <p>2016-10-01</p> <p>The effectiveness of community clinics and health centers' efforts to improve the quality of care might be modified by clinics' workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (staff relationships, quality improvement orientation, managerial readiness for change, and staff readiness for change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called "Clinic Functionality." This 2-level, 6-factor model fit the data well in the exploratory and confirmatory samples. For all but 1 factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics' quality improvement efforts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5991803','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5991803"><span>Measuring Workplace Climate in Community Clinics and Health Centers</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Friedberg, Mark W.; Rodriguez, Hector P.; Martsolf, Grant; Edelen, Maria Orlando; Vargas-Bustamante, Arturo</p> <p>2018-01-01</p> <p>Background The effectiveness of community clinics and health centers’ efforts to improve the quality of care might be modified by clinics’ workplace climates. Several surveys to measure workplace climate exist, but their relationships to each other and to distinguishable dimensions of workplace climate are unknown. Objective To assess the psychometric properties of a survey instrument combining items from several existing surveys of workplace climate and to generate a shorter instrument for future use. Methods We fielded a 106-item survey, which included items from 9 existing instruments, to all clinicians and staff members (n=781) working in 30 California community clinics and health centers, receiving 628 responses (80% response rate). We performed exploratory factor analysis of survey responses, followed by confirmatory factor analysis of 200 reserved survey responses. We generated a new, shorter survey instrument of items with strong factor loadings. Results Six factors, including 44 survey items, emerged from the exploratory analysis. Two factors (Clinic Workload and Teamwork) were independent from the others. The remaining 4 factors (Staff Relationships, Quality Improvement Orientation, Managerial Readiness for Change, and Staff Readiness for Change) were highly correlated, indicating that these represented dimensions of a higher-order factor we called “Clinic Functionality.” This two-level, six-factor model fit the data well in the exploratory and confirmatory samples. For all but one factor, fewer than 20 survey responses were needed to achieve clinic-level reliability >0.7. Conclusion Survey instruments designed to measure workplace climate have substantial overlap. The relatively parsimonious item set we identified might help target and tailor clinics’ quality improvement efforts. PMID:27326549</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNH23E2871K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNH23E2871K"><span>An observational and modeling study of the August 2017 Florida climate extreme event.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Konduru, R.; Singh, V.; Routray, A.</p> <p>2017-12-01</p> <p>A special report on the climate extremes by the Intergovernmental Panel on Climate Change (IPCC) elucidates that the sole cause of disasters is due to the exposure and vulnerability of the human and natural system to the climate extremes. The cause of such a climate extreme could be anthropogenic or non-anthropogenic. Therefore, it is challenging to discern the critical factor of influence for a particular climate extreme. Such kind of perceptive study with reasonable confidence on climate extreme events is possible only if there exist any past case studies. A similar rarest climate extreme problem encountered in the case of Houston floods and extreme rainfall over Florida in August 2017. A continuum of hurricanes like Harvey and Irma targeted the Florida region and caused catastrophe. Due to the rarity of August 2017 Florida climate extreme event, it requires the in-depth study on this case. To understand the multi-faceted nature of the event, a study on the development of the Harvey hurricane and its progression and dynamics is significant. Current article focus on the observational and modeling study on the Harvey hurricane. A global model named as NCUM (The global UK Met office Unified Model (UM) operational at National Center for Medium Range Weather Forecasting, India, was utilized to simulate the Harvey hurricane. The simulated rainfall and wind fields were compared with the observational datasets like Tropical Rainfall Measuring Mission rainfall datasets and Era-Interim wind fields. The National Centre for Environmental Prediction (NCEP) automated tracking system was utilized to track the Harvey hurricane, and the tracks were analyzed statistically for different forecasts concerning the Harvey hurricane track of Joint Typhon Warning Centre. Further, the current study will be continued to investigate the atmospheric processes involved in the August 2017 Florida climate extreme event.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000004826&hterms=continental+drift&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcontinental%2Bdrift','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000004826&hterms=continental+drift&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcontinental%2Bdrift"><span>Real Time Land-Surface Hydrologic Modeling Over Continental US</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Houser, Paul R.</p> <p>1998-01-01</p> <p>The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatSR...628785C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatSR...628785C"><span>Projected asymmetric response of Adélie penguins to Antarctic climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cimino, Megan A.; Lynch, Heather J.; Saba, Vincent S.; Oliver, Matthew J.</p> <p>2016-06-01</p> <p>The contribution of climate change to shifts in a species’ geographic distribution is a critical and often unresolved ecological question. Climate change in Antarctica is asymmetric, with cooling in parts of the continent and warming along the West Antarctic Peninsula (WAP). The Adélie penguin (Pygoscelis adeliae) is a circumpolar meso-predator exposed to the full range of Antarctic climate and is undergoing dramatic population shifts coincident with climate change. We used true presence-absence data on Adélie penguin breeding colonies to estimate past and future changes in habitat suitability during the chick-rearing period based on historic satellite observations and future climate model projections. During the contemporary period, declining Adélie penguin populations experienced more years with warm sea surface temperature compared to populations that are increasing. Based on this relationship, we project that one-third of current Adélie penguin colonies, representing ~20% of their current population, may be in decline by 2060. However, climate model projections suggest refugia may exist in continental Antarctica beyond 2099, buffering species-wide declines. Climate change impacts on penguins in the Antarctic will likely be highly site specific based on regional climate trends, and a southward contraction in the range of Adélie penguins is likely over the next century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791639','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2791639"><span>On the stability of the Atlantic meridional overturning circulation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hofmann, Matthias; Rahmstorf, Stefan</p> <p>2009-01-01</p> <p>One of the most important large-scale ocean current systems for Earth's climate is the Atlantic meridional overturning circulation (AMOC). Here we review its stability properties and present new model simulations to study the AMOC's hysteresis response to freshwater perturbations. We employ seven different versions of an Ocean General Circulation Model by using a highly accurate tracer advection scheme, which minimizes the problem of numerical diffusion. We find that a characteristic freshwater hysteresis also exists in the predominantly wind-driven, low-diffusion limit of the AMOC. However, the shape of the hysteresis changes, indicating that a convective instability rather than the advective Stommel feedback plays a dominant role. We show that model errors in the mean climate can make the hysteresis disappear, and we investigate how model innovations over the past two decades, like new parameterizations and mixing schemes, affect the AMOC stability. Finally, we discuss evidence that current climate models systematically overestimate the stability of the AMOC. PMID:19897722</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016QSRv..149..188C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016QSRv..149..188C"><span>The influence of climate on species distribution over time and space during the late Quaternary</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Carotenuto, F.; Di Febbraro, M.; Melchionna, M.; Castiglione, S.; Saggese, F.; Serio, C.; Mondanaro, A.; Passaro, F.; Loy, A.; Raia, P.</p> <p>2016-10-01</p> <p>Understanding the effect of climate on the composition of communities and its change over time and space is one of the major aims in ecology and paleoecology. Herein, we tackled on this issue by studying late Quaternary large mammal paleocommunities of Eurasia. The late Quaternary was a period of strong environmental instability, especially characterized by the occurrence of the last glacial maximum (LGM). We used community phylogenetics and joint species distribution models in order to understand the factors determining paleocommunity composition in the late Quaternary. Our results support the existence of strong climatic selection operating on the LGM fauna, both through the disappearance of warm-adapted species such as Elephas antiquus, Hippopothamus amphibious, and Stephanorhinus hemitoechus, and by setting the stage for the existence of a community characterized by cold-adapted large mammals. Patterns of abundance in the fossil record, co-occurrence between species pairs, and the extent of climatic forcing on faunal composition, differ between paleocommunities, but not between extinct and extant species, which is consistent with the idea that climate change, rather than the presence of humans, exerted a major effect on the survival of the late Quaternary megafauna.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1121625','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1121625"><span>MIDWESTERN REGIONAL CENTER OF THE DOE NATIONAL INSTITUTE FOR CLIMATIC CHANGE RESEARCH</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Burton, Andrew J.</p> <p>2014-02-28</p> <p>The goal of NICCR (National Institute for Climatic Change Research) was to mobilize university researchers, from all regions of the country, in support of the climatic change research objectives of DOE/BER. The NICCR Midwestern Regional Center (MRC) supported work in the following states: North Dakota, South Dakota, Nebraska, Kansas, Oklahoma, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Michigan, Indiana, and Ohio. The MRC of NICCR was able to support nearly $8 million in climatic change research, including $6,671,303 for twenty projects solicited and selected by the MRC over five requests for proposals (RFPs) and $1,051,666 for the final year of ten projectsmore » from the discontinued DOE NIGEC (National Institute for Global Environmental Change) program. The projects selected and funded by the MRC resulted in 135 peer-reviewed publications and supported the training of 25 PhD students and 23 Masters students. Another 36 publications were generated by the final year of continuing NIGEC projects supported by the MRC. The projects funded by the MRC used a variety of approaches to answer questions relevant to the DOE’s climate change research program. These included experiments that manipulated temperature, moisture and other global change factors; studies that sought to understand how the distribution of species and ecosystems might change under future climates; studies that used measurements and modeling to examine current ecosystem fluxes of energy and mass and those that would exist under future conditions; and studies that synthesized existing data sets to improve our understanding of the effects of climatic change on terrestrial ecosystems. In all of these efforts, the MRC specifically sought to identify and quantify responses of terrestrial ecosystems that were not well understood or not well modeled by current efforts. The MRC also sought to better understand and model important feedbacks between terrestrial ecosystems, atmospheric chemistry, and regional and global climate systems. The broad variety of projects the MRC has supported gave us a unique opportunity to greatly improve our ability to predict the future health, composition and function of important agricultural and natural terrestrial ecosystems within the Midwestern Region.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4758O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4758O"><span>Characterizing bias correction uncertainty in wheat yield predictions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam</p> <p>2017-04-01</p> <p>Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A13K3325C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A13K3325C"><span>Tuning a climate model using nudging to reanalysis.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cheedela, S. K.; Mapes, B. E.</p> <p>2014-12-01</p> <p>Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21B3020R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21B3020R"><span>The Construction of 3-d Neutral Density for Arbitrary Data Sets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Riha, S.; McDougall, T. J.; Barker, P. M.</p> <p>2014-12-01</p> <p>The Neutral Density variable allows inference of water pathways from thermodynamic properties in the global ocean, and is therefore an essential component of global ocean circulation analysis. The widely used algorithm for the computation of Neutral Density yields accurate results for data sets which are close to the observed climatological ocean. Long-term numerical climate simulations, however, often generate a significant drift from present-day climate, which renders the existing algorithm inaccurate. To remedy this problem, new algorithms which operate on arbitrary data have been developed, which may potentially be used to compute Neutral Density during runtime of a numerical model.We review existing approaches for the construction of Neutral Density in arbitrary data sets, detail their algorithmic structure, and present an analysis of the computational cost for implementations on a single-CPU computer. We discuss possible strategies for the implementation in state-of-the-art numerical models, with a focus on distributed computing environments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080024183','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080024183"><span>Evaluation and Applications of Cloud Climatologies from CALIOP</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Winker, David; Getzewitch, Brian; Vaughan, Mark</p> <p>2008-01-01</p> <p>Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EaFut...5...72B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EaFut...5...72B"><span>Pan-Arctic river discharge: Prioritizing monitoring of future climate change hot spots</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bring, Arvid; Shiklomanov, Alexander; Lammers, Richard B.</p> <p>2017-01-01</p> <p>The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNG41A0119W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNG41A0119W"><span>Generalised and Fractional Langevin Equations-Implications for Energy Balance Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Watkins, N. W.; Chapman, S. C.; Chechkin, A.; Ford, I.; Klages, R.; Stainforth, D. A.</p> <p>2017-12-01</p> <p>Energy Balance Models (EBMs) have a long heritage in climate science, including their use in modelling anomalies in global mean temperature. Many types of EBM have now been studied, and this presentation concerns the stochastic EBMs, which allow direct treatment of climate fluctuations and noise. Some recent stochastic EBMs (e.g. [1]) map on to Langevin's original form of his equation, with temperature anomaly replacing velocity, and other corresponding replacements being made. Considerable sophistication has now been reached in the application of multivariate stochastic Langevin modelling in many areas of climate. Our work is complementary in intent and investigates the Mori-Kubo "Generalised Langevin Equation" (GLE) which incorporates non-Markovian noise and response in a univariate framework, as a tool for modelling GMT [2]. We show how, if it is present, long memory simplifies the GLE to a fractional Langevin equation (FLE). Evidence for long range memory in global temperature, and the success of fractional Gaussian noise in its prediction [5] has already motivated investigation of a power law response model [3,4,5]. We go beyond this work to ask whether an EBM of FLE-type exists, and what its solutions would be. [l] Padilla et al, J. Climate (2011); [2] Watkins, GRL (2013); [3] Rypdal, JGR (2012); [4] Rypdal and Rypdal, J. Climate (2014); [5] Lovejoy et al, ESDD (2015).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JMetR..31..633C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JMetR..31..633C"><span>An overview of mineral dust modeling over East Asia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Siyu; Huang, Jianping; Qian, Yun; Zhao, Chun; Kang, Litai; Yang, Ben; Wang, Yong; Liu, Yuzhi; Yuan, Tiangang; Wang, Tianhe; Ma, Xiaojun; Zhang, Guolong</p> <p>2017-08-01</p> <p>East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015QSRv..127..155W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015QSRv..127..155W"><span>Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn</p> <p>2015-11-01</p> <p>Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GMD....11.1799L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GMD....11.1799L"><span>Crossing the chasm: how to develop weather and climate models for next generation computers?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lawrence, Bryan N.; Rezny, Michael; Budich, Reinhard; Bauer, Peter; Behrens, Jörg; Carter, Mick; Deconinck, Willem; Ford, Rupert; Maynard, Christopher; Mullerworth, Steven; Osuna, Carlos; Porter, Andrew; Serradell, Kim; Valcke, Sophie; Wedi, Nils; Wilson, Simon</p> <p>2018-05-01</p> <p>Weather and climate models are complex pieces of software which include many individual components, each of which is evolving under pressure to exploit advances in computing to enhance some combination of a range of possible improvements (higher spatio-temporal resolution, increased fidelity in terms of resolved processes, more quantification of uncertainty, etc.). However, after many years of a relatively stable computing environment with little choice in processing architecture or programming paradigm (basically X86 processors using MPI for parallelism), the existing menu of processor choices includes significant diversity, and more is on the horizon. This computational diversity, coupled with ever increasing software complexity, leads to the very real possibility that weather and climate modelling will arrive at a chasm which will separate scientific aspiration from our ability to develop and/or rapidly adapt codes to the available hardware. In this paper we review the hardware and software trends which are leading us towards this chasm, before describing current progress in addressing some of the tools which we may be able to use to bridge the chasm. This brief introduction to current tools and plans is followed by a discussion outlining the scientific requirements for quality model codes which have satisfactory performance and portability, while simultaneously supporting productive scientific evolution. We assert that the existing method of incremental model improvements employing small steps which adjust to the changing hardware environment is likely to be inadequate for crossing the chasm between aspiration and hardware at a satisfactory pace, in part because institutions cannot have all the relevant expertise in house. Instead, we outline a methodology based on large community efforts in engineering and standardisation, which will depend on identifying a taxonomy of key activities - perhaps based on existing efforts to develop domain-specific languages, identify common patterns in weather and climate codes, and develop community approaches to commonly needed tools and libraries - and then collaboratively building up those key components. Such a collaborative approach will depend on institutions, projects, and individuals adopting new interdependencies and ways of working.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24082126','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24082126"><span>Stratospheric water vapor feedback.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dessler, A E; Schoeberl, M R; Wang, T; Davis, S M; Rosenlof, K H</p> <p>2013-11-05</p> <p>We show here that stratospheric water vapor variations play an important role in the evolution of our climate. This comes from analysis of observations showing that stratospheric water vapor increases with tropospheric temperature, implying the existence of a stratospheric water vapor feedback. We estimate the strength of this feedback in a chemistry-climate model to be +0.3 W/(m(2)⋅K), which would be a significant contributor to the overall climate sensitivity. One-third of this feedback comes from increases in water vapor entering the stratosphere through the tropical tropopause layer, with the rest coming from increases in water vapor entering through the extratropical tropopause.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.9347A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.9347A"><span>Inter-model variability in hydrological extremes projections for Amazonian sub-basins</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Andres Rodriguez, Daniel; Garofolo, Lucas; Lázaro de Siqueira Júnior, José; Samprogna Mohor, Guilherme; Tomasella, Javier</p> <p>2014-05-01</p> <p>Irreducible uncertainties due to knowledge's limitations, chaotic nature of climate system and human decision-making process drive uncertainties in Climate Change projections. Such uncertainties affect the impact studies, mainly when associated to extreme events, and difficult the decision-making process aimed at mitigation and adaptation. However, these uncertainties allow the possibility to develop exploratory analyses on system's vulnerability to different sceneries. The use of different climate model's projections allows to aboard uncertainties issues allowing the use of multiple runs to explore a wide range of potential impacts and its implications for potential vulnerabilities. Statistical approaches for analyses of extreme values are usually based on stationarity assumptions. However, nonstationarity is relevant at the time scales considered for extreme value analyses and could have great implications in dynamic complex systems, mainly under climate change transformations. Because this, it is required to consider the nonstationarity in the statistical distribution parameters. We carried out a study of the dispersion in hydrological extremes projections using climate change projections from several climate models to feed the Distributed Hydrological Model of the National Institute for Spatial Research, MHD-INPE, applied in Amazonian sub-basins. This model is a large-scale hydrological model that uses a TopModel approach to solve runoff generation processes at the grid-cell scale. MHD-INPE model was calibrated for 1970-1990 using observed meteorological data and comparing observed and simulated discharges by using several performance coeficients. Hydrological Model integrations were performed for present historical time (1970-1990) and for future period (2010-2100). Because climate models simulate the variability of the climate system in statistical terms rather than reproduce the historical behavior of climate variables, the performances of the model's runs during the historical period, when feed with climate model data, were tested using descriptors of the Flow Duration Curves. The analyses of projected extreme values were carried out considering the nonstationarity of the GEV distribution parameters and compared with extremes events in present time. Results show inter-model variability in a broad dispersion on projected extreme's values. Such dispersion implies different degrees of socio-economic impacts associated to extreme hydrological events. Despite the no existence of one optimum result, this variability allows the analyses of adaptation strategies and its potential vulnerabilities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A43A0128T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A43A0128T"><span>NCPP's Use of Standard Metadata to Promote Open and Transparent Climate Modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Treshansky, A.; Barsugli, J. J.; Guentchev, G.; Rood, R. B.; DeLuca, C.</p> <p>2012-12-01</p> <p>The National Climate Predictions and Projections (NCPP) Platform is developing comprehensive regional and local information about the evolving climate to inform decision making and adaptation planning. This includes both creating and providing tools to create metadata about the models and processes used to create its derived data products. NCPP is using the Common Information Model (CIM), an ontology developed by a broad set of international partners in climate research, as its metadata language. This use of a standard ensures interoperability within the climate community as well as permitting access to the ecosystem of tools and services emerging alongside the CIM. The CIM itself is divided into a general-purpose (UML & XML) schema which structures metadata documents, and a project or community-specific (XML) Controlled Vocabulary (CV) which constraints the content of metadata documents. NCPP has already modified the CIM Schema to accommodate downscaling models, simulations, and experiments. NCPP is currently developing a CV for use by the downscaling community. Incorporating downscaling into the CIM will lead to several benefits: easy access to the existing CIM Documents describing CMIP5 models and simulations that are being downscaled, access to software tools that have been developed in order to search, manipulate, and visualize CIM metadata, and coordination with national and international efforts such as ES-DOC that are working to make climate model descriptions and datasets interoperable. Providing detailed metadata descriptions which include the full provenance of derived data products will contribute to making that data (and, the models and processes which generated that data) more open and transparent to the user community.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A53G..01O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A53G..01O"><span>Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.</p> <p>2015-12-01</p> <p>Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015506','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015506"><span>Software Testing and Verification in Climate Model Development</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Clune, Thomas L.; Rood, RIchard B.</p> <p>2011-01-01</p> <p>Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1715533D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1715533D"><span>LandCaRe-DSS - model based tools for irrigation management under climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dotterweich, Markus; Wilkinson, Kristina; Cassel, Martin; Scherzer, Jörg; Köstner, Barbara; Berg, Michael; Grocholl, Jürgen</p> <p>2015-04-01</p> <p>Climate change is expected to have a strong influence on agricultural systems in the future. It will be important for decision makers and stakeholders to assess the impact of climate change at the farm and regional level in order to facilitate and maintain a sustainable and profitable farming infrastructure. Climate change impact studies have to incorporate aspects of uncertainty and the underlying knowledge is constantly expanding and improving. Decision support systems (DSS) with flexible data bases are therefore a useful tool for management and planning: different models can be applied under varying boundary conditions within a conceptual framework and the results can be used e.g. to show the effects of climate change scenarios and different land management options. Within this project, the already existing LandCaRe DSS will be further enhanced and improved. A first prototype had been developed for two regions in eastern Germany, mainly to show the effects of climate change on yields, nutrient balances and farm economy. The new model version will be tested and applied for a region in north-western Germany (Landkreis Uelzen) where arable land makes up about 50% of overall land-use and where 80 % of the arable land is already irrigated. For local decision makers, it will be important to know how water demand and water availability are likely to change in the future: Is more water needed for irrigation? Is more water actually available for irrigation? Will the existing limits for ground water withdrawal be sufficient for farmers to irrigate their crops? How can the irrigation water demand be influenced by land management options like the use of different crops and varieties or different farming and irrigation techniques? The main tasks of the project are (I) the integration of an improved irrigation model, (II) the development of a standardized interface to apply the DSS in different regions, (III) to optimize the graphical user interface, (IV) to transfer and apply the DSS in an example region in north-west Germany and (V) to expand the underlying data base of climate change models and scenarios. The project is funded by the Bundesministeriums für Bildung und Forschung (BMBF), Förderkennzeichen Förderkennzeichen: 02WQ1304.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMED52A..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMED52A..01G"><span>Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goldenson, N. L.</p> <p>2014-12-01</p> <p>Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect, reservoirs and flows, albedo feedback, Snowball Earth, climate sensitivity, and model experiment design. Climate calculations are extended to Mars with some modifications to the Earth climate component, and could be used in lessons about the Mars atmosphere, and exploring scenarios of Mars climate history.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913780K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913780K"><span>The WASCAL high-resolution climate projection ensemble for West Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kunstmann, Harald; Heinzeller, Dominikus; Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Hamann, Ilse; Salack, Seyni</p> <p>2017-04-01</p> <p>With climate change being one of the most severe challenges to rural Africa in the 21st century, West Africa is facing an urgent need to develop effective adaptation and mitigation measures to protect its constantly growing population. We perform ensemble-based regional climate simulations at a high resolution of 12km for West Africa to allow a scientifically sound derivation of climate change adaptation measures. Based on the RCP4.5 scenario, our ensemble consist of three simulation experiments with the Weather Research & Forecasting Tool (WRF) and one additional experiment with the Consortium for Small-scale Modelling Model COSMO in Climate Mode (COSMO-CLM). We discuss the model performance over the validation period 1980-2010, including a novel, station-based precipitation database for West Africa obtained within the WASCAL (West African Science Service Centre for Climate Change and Adapted Land Use) program. Particular attention is paid to the representation of the dynamics of the West African Summer Monsoon and to the added value of our high-resolution models over existing data sets. We further present results on the climate change signal obtained for the two future periods 2020-2050 and 2070-2100 and compare them to current state-of-the-art projections from the CORDEX-Africa project. While the temperature change signal is similar to that obtained within CORDEX-Africa, our simulations predict a wetter future for the Coast of Guinea and the southern Soudano area and a slight drying in the northernmost part of the Sahel.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AtmRe.204...37Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AtmRe.204...37Z"><span>Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan</p> <p>2018-05-01</p> <p>A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B21K..01G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B21K..01G"><span>Plant leaf traits, canopy processes, and global atmospheric chemistry interactions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Guenther, A. B.</p> <p>2017-12-01</p> <p>Plants produce and emit a diverse array of volatile metabolites into the atmosphere that participate in chemical reactions that influence distributions of air pollutants and short-lived climate forcers including organic aerosol, ozone and methane. It is now widely accepted that accurate estimates of these emissions are required as inputs for regional air quality and global climate models. Predicting these emissions is complicated by the large number of volatile organic compounds, driving variables (e.g., temperature, solar radiation, abiotic and biotic stresses) and processes operating across a range of scales. Modeling efforts to characterize emission magnitude and variations will be described along with an assessment of the observations available for parameterizing and evaluating these models including discussion of the limitations and challenges associated with existing model approaches. A new approach for simulating canopy scale organic emissions on regional to global scales will be described and compared with leaf, canopy and regional scale flux measurements. The importance of including additional compounds and processes as well as improving estimates of existing ones will also be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27124597','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27124597"><span>Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Mann, Michael L; Batllori, Enric; Moritz, Max A; Waller, Eric K; Berck, Peter; Flint, Alan L; Flint, Lorraine E; Dolfi, Emmalee</p> <p>2016-01-01</p> <p>The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state's fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20956364','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20956364"><span>How uncertain are climate model projections of water availability indicators across the Middle East?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hemming, Debbie; Buontempo, Carlo; Burke, Eleanor; Collins, Mat; Kaye, Neil</p> <p>2010-11-28</p> <p>The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4849771','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4849771"><span>Incorporating Anthropogenic Influences into Fire Probability Models: Effects of Human Activity and Climate Change on Fire Activity in California</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Batllori, Enric; Moritz, Max A.; Waller, Eric K.; Berck, Peter; Flint, Alan L.; Flint, Lorraine E.; Dolfi, Emmalee</p> <p>2016-01-01</p> <p>The costly interactions between humans and wildfires throughout California demonstrate the need to understand the relationships between them, especially in the face of a changing climate and expanding human communities. Although a number of statistical and process-based wildfire models exist for California, there is enormous uncertainty about the location and number of future fires, with previously published estimates of increases ranging from nine to fifty-three percent by the end of the century. Our goal is to assess the role of climate and anthropogenic influences on the state’s fire regimes from 1975 to 2050. We develop an empirical model that integrates estimates of biophysical indicators relevant to plant communities and anthropogenic influences at each forecast time step. Historically, we find that anthropogenic influences account for up to fifty percent of explanatory power in the model. We also find that the total area burned is likely to increase, with burned area expected to increase by 2.2 and 5.0 percent by 2050 under climatic bookends (PCM and GFDL climate models, respectively). Our two climate models show considerable agreement, but due to potential shifts in rainfall patterns, substantial uncertainty remains for the semiarid inland deserts and coastal areas of the south. Given the strength of human-related variables in some regions, however, it is clear that comprehensive projections of future fire activity should include both anthropogenic and biophysical influences. Previous findings of substantially increased numbers of fires and burned area for California may be tied to omitted variable bias from the exclusion of human influences. The omission of anthropogenic variables in our model would overstate the importance of climatic ones by at least 24%. As such, the failure to include anthropogenic effects in many models likely overstates the response of wildfire to climatic change. PMID:27124597</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/25978','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/25978"><span>Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Mike D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot</p> <p>2006-01-01</p> <p>The relative importance of variables in determining area burned is an important management consideration although gaining insights from existing empirical data has proven difficult. The purpose of this study was to compare the sensitivity of modeled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/2451','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/2451"><span>A Linked Model for Simulating Stand Development and Growth Processes of Loblolly Pine</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>V. Clark Baldwin; Phillip M. Dougherty; Harold E. Burkhart</p> <p>1998-01-01</p> <p>Linking models of different scales (e.g., process, tree-stand-ecosystem) is essential for furthering our understanding of stand, climatic, and edaphic effects on tree growth and forest productivity. Moreover, linking existing models that differ in scale and levels of resolution quickly identifies knowledge gaps in information required to scale from one level to another...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4991643','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4991643"><span>CLIMATE VARIABILITY, LAND OWNERSHIP AND MIGRATION: EVIDENCE FROM THAILAND ABOUT GENDER IMPACTS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Curran, Sara R.; Meijer-Irons, Jacqueline</p> <p>2016-01-01</p> <p>Scholars point to climate change, often in the form of more frequent and severe drought, as a potential driver of migration in the developing world, particularly for places where populations rely on agriculture for their livelihoods. To date, however, there have been few large-scale, longitudinal studies that explore the relationship between climate change and migration. This study significantly extends current scholarship by evaluating distinctive effects of climatic variation and models these effects on men’s and women’s responsiveness to drought and rainfall. Our study also investigates how land ownership moderates these effects. We find small, but significant, increases in migration above existing migratory levels during periods of prolonged climatic stress, and that these patterns differ both by gender and land tenure. PMID:27547492</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3033278','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3033278"><span>Climate change induces demographic resistance to disease in novel coral assemblages</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Yakob, Laith; Mumby, Peter J.</p> <p>2011-01-01</p> <p>Climate change is reshaping biological communities and has already generated novel ecosystems. The functioning of novel ecosystems could depart markedly from that of existing systems and therefore obscure the impacts of climate change. We illustrate this possibility for coral reefs, which are at the forefront of climatic stress. Disease has been a principal cause of reef degradation and is expected to worsen with increased future thermal stress. However, using a field-tested epizoological model, we show that high population turnover within novel ecosystems enhances coral resistance to epizootics. Thus, disease could become a less important driver of change in the future. We emphasize the need to move away from projections based on historic trends toward predictions that account for novel behavior of ecosystems under climate change. PMID:21245326</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP44B..01E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP44B..01E"><span>The Paleoclimate Uncertainty Cascade: Tracking Proxy Errors Via Proxy System Models.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Emile-Geay, J.; Dee, S. G.; Evans, M. N.; Adkins, J. F.</p> <p>2014-12-01</p> <p>Paleoclimatic observations are, by nature, imperfect recorders of climate variables. Empirical approaches to their calibration are challenged by the presence of multiple sources of uncertainty, which may confound the interpretation of signals and the identifiability of the noise. In this talk, I will demonstrate the utility of proxy system models (PSMs, Evans et al, 2013, 10.1016/j.quascirev.2013.05.024) to quantify the impact of all known sources of uncertainty. PSMs explicitly encode the mechanistic knowledge of the physical, chemical, biological and geological processes from which paleoclimatic observations arise. PSMs may be divided into sensor, archive and observation components, all of which may conspire to obscure climate signals in actual paleo-observations. As an example, we couple a PSM for the δ18O of speleothem calcite to an isotope-enabled climate model (Dee et al, submitted) to analyze the potential of this measurement as a proxy for precipitation amount. A simple soil/karst model (Partin et al, 2013, 10.1130/G34718.1) is used as sensor model, while a hiatus-permitting chronological model (Haslett & Parnell, 2008, 10.1111/j.1467-9876.2008.00623.x) is used as part of the observation model. This subdivision allows us to explicitly model the transformation from precipitation amount to speleothem calcite δ18O as a multi-stage process via a physical and chemical sensor model, and a stochastic archive model. By illustrating the PSM's behavior within the context of the climate simulations, we show how estimates of climate variability may be affected by each submodel's transformation of the signal. By specifying idealized climate signals(periodic vs. episodic, slow vs. fast) to the PSM, we investigate how frequency and amplitude patterns are modulated by sensor and archive submodels. To the extent that the PSM and the climate models are representative of real world processes, then the results may help us more accurately interpret existing paleodata, characterize their uncertainties, and design sampling strategies that exploit their strengths while mitigating their weaknesses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18577087','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18577087"><span>Integrated monitoring and information systems for managing aquatic invasive species in a changing climate.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lee, Henry; Reusser, Deborah A; Olden, Julian D; Smith, Scott S; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S; Piorkowski, Robert J; McPhedran, John</p> <p>2008-06-01</p> <p>Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70179371','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70179371"><span>Integrated monitoring and information systems for managing aquatic invasive species in a changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Lee, Henry; Reusser, Deborah A.; Olden, Julian D.; Smith, Scott S.; Graham, Jim; Burkett, Virginia; Dukes, Jeffrey S.; Piorkowski, Robert J.; Mcphedran, John</p> <p>2008-01-01</p> <p>Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1912409F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1912409F"><span>Transitions between multiple equilibria of paleo climate: a glimpse in to the dynamics of abrupt climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferreira, David; Marshall, John; Ito, Takamitsu; McGee, David; Moreno-Chamarro, Eduardo</p> <p>2017-04-01</p> <p>The dynamics regulating large climatic transitions such as glacial-interglacial cycles or DO events remains a puzzle. Forcings behind these transitions are not robustly identified and potential candidates (e.g. Milankovitch cycles, freshwater perturbations) often appear too weak to explain such dramatic transitions. A potential solution to this long-standing puzzle is that Earth's climate is endowed with multiple equilibrium states of global extent. Such states are commonly found in low-order or conceptual climate models, but it is unclear whether a system as complex as Earth's climate can sustain multiple equilibrium states. Here we report that multiple equilibrium states of the climate system are also possible in a complex, fully dynamical coupled ocean-atmosphere-sea ice GCM with idealized Earth-like geometry, resolved weather systems and a hydrological cycle. In our model, two equilibrium states coexist for the same parameters and external forcings: a Warm climate with a small Northern hemisphere sea ice cap and a large southern one and a Cold climate with large ice caps at both poles. The dynamical states of the Warm and Cold solutions exhibit striking similarities with our present-day climate and the climate of the Last Glacial Maximum, respectively. A carbon cycle model driven by the two dynamical states produces an atmospheric pCO2 draw-down of about 110 pm between the Warm and Cold states, close to Glacial-Interglacial differences found in ice cores. Mechanism controlling the existence of the multiple states and changes in the atmospheric CO2 will be briefly presented. Finally we willdescribe transition experiments from the Cold to the Warm state, focusing on the lead-lags in the system, notably between the Northern and Southern Hemispheres climates.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22938527','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22938527"><span>Effects of temperature change on mussel, Mytilus.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zippay, Mackenzie L; Helmuth, Brian</p> <p>2012-09-01</p> <p>An increasing body of research has demonstrated the often idiosyncratic responses of organisms to climate-related factors, such as increases in air, sea and land surface temperatures, especially when coupled with non-climatic stressors. This argues that sweeping generalizations about the likely impacts of climate change on organisms and ecosystems are likely less valuable than process-based explorations that focus on key species and ecosystems. Mussels in the genus Mytilus have been studied for centuries, and much is known of their physiology and ecology. Like other intertidal organisms, these animals may serve as early indicators of climate change impacts. As structuring species, their survival has cascading impacts on many other species, making them ecologically important, in addition to their economic value as a food source. Here, we briefly review the categories of information available on the effects of temperature change on mussels within this genus. Although a considerable body of information exists about the genus in general, knowledge gaps still exist, specifically in our ability to predict how specific populations are likely to respond to the effects of multiple stressors, both climate and non-climate related, and how these changes are likely to result in ecosystem-level responses. Whereas this genus provides an excellent model for exploring the effects of climate change on natural and human-managed ecosystems, much work remains if we are to make predictions of likely impacts of environmental change on scales that are relevant to climate adaptation. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29696859','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29696859"><span>[Potential distribution of Panax ginseng and its predicted responses to climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Zhao, Ze Fang; Wei, Hai Yan; Guo, Yan Long; Gu, Wei</p> <p>2016-11-18</p> <p>This study utilized Panax ginseng as the research object. Based on BioMod2 platform, with species presence data and 22 climatic variables, the potential geographic distribution of P. ginseng under the current conditions in northeast China was simulated with ten species distribution model. And then with the receiver-operating characteristic curve (ROC) as weights, we build an ensemble model, which integrated the results of 10 models, using the ensemble model, the future distributions of P. ginseng were also projected for the periods 2050s and 2070s under the climate change scenarios of RCP 8.5, RCP 6, RCP 4.5 and RCP 2.6 emission scenarios described in the Special Report on Emissions Scenarios (SRES) of IPCC (Intergovernmental Panel on Climate Change). The results showed that for the entire region of study area, under the present climatic conditions, 10.4% of the areas were identified as suitable habitats, which were mainly located in northeast Changbai Mountains area and the southeastern region of the Xiaoxing'an Mountains. The model simulations indicated that the suitable habitats would have a relatively significant change under the different climate change scenarios, and generally the range of suitable habitats would be a certain degree of decrease. Meanwhile, the goodness-of-fit, predicted ranges, and weights of explanatory variables was various for each model. And according to the goodness-of-fit, Maxent had the highest model performance, and GAM, RF and ANN were followed, while SRE had the lowest prediction accuracy. In this study we established an ensemble model, which could improve the accuracy of the existing species distribution models, and optimization of species distribution prediction results.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT.......191W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT.......191W"><span>Complexity in Climatic Controls on Plant Species Distribution: Satellite Data Reveal Unique Climate for Giant Sequoia in the California Sierra Nevada</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Waller, Eric Kindseth</p> <p></p> <p>A better understanding of the environmental controls on current plant species distribution is essential if the impacts of such diverse challenges as invasive species, changing fire regimes, and global climate change are to be predicted and important diversity conserved. Climate, soil, hydrology, various biotic factors fire, history, and chance can all play a role, but disentangling these factors is a daunting task. Increasingly sophisticated statistical models relying on existing distributions and mapped climatic variables, among others, have been developed to try to answer these questions. Any failure to explain pattern with existing mapped climatic variables is often taken as a referendum on climate as a whole, rather than on the limitations of the particular maps or models. Every location has a unique and constantly changing climate so that any distribution could be explained by some aspect of climate. Chapter 1 of this dissertation reviews some of the major flaws in species distribution modeling and addresses concerns that climate may therefore not be predictive of, or even relevant to, species distributions. Despite problems with climate-based models, climate and climate-derived variables still have substantial merit for explaining species distribution patterns. Additional generation of relevant climate variables and improvements in other climate and climate-derived variables are still needed to demonstrate this more effectively. Satellite data have a long history of being used for vegetation mapping and even species distribution mapping. They have great potential for being used for additional climatic information, and for improved mapping of other climate and climate-derived variables. Improving the characterization of cloud cover frequency with satellite data is one way in which the mapping of important climate and climate-derived variables can be improved. An important input to water balance models, solar radiation maps could be vastly improved with a better mapping of spatial and temporal patterns in cloud cover. Chapter 2 of this dissertation describes the generation of custom daily cloud cover maps from Advanced Very High Resolution Radiometer (AVHRR) satellite data from 1981-1999 at ~5 km resolution and Moderate Resolution Imagine Spectroradiomter (MODIS) satellite reflectance data at ~500 meter resolution for much of the western U.S., from 2000 to 2012. Intensive comparisons of reflectance spectra from a variety of cloud and snow-covered scenes from the southwestern United States allowed the generation of new rules for the classification of clouds and snow in both the AVHRR and MODIS data. The resulting products avoid many of the problems that plague other cloud mapping efforts, such as the tendency for snow cover and bright desert soils to be mapped as cloud. This consistency in classification across cover types is critically important for any distribution modeling of a plant species that might be dependent on cloud cover. In Chapter 3, monthly cloud frequencies derived from the daily classifications were used directly in species distribution models for giant sequoia and were found to be the strongest predictors of giant sequoia distribution. A high frequency of cloud cover, especially in the spring, differentiated the climate of the west slope of the southern Sierra Nevada, where giant sequoia are prolific, from central and northern parts of the range, where the tree is rare and generally absent. Other mapped cloud products, contaminated by confusion with high elevation snow, would likely not have found this important result. The result illustrates the importance of accuracy in mapping as well as the importance of previously overlooked aspects of climate for species distribution modeling. But it also raises new questions about why the clouds form where they do and whether they might be associated with other aspects of climate important to giant sequoia distribution. What are the exact climatic mechanisms governing the distribution? Detailed aspects of the local climate warranted more investigation. Chapter 4 investigates the climate associated with the frequent cloud formation over the western slopes of the southern Sierra Nevada: the "sequoia belt". This region is climatically distinct in a number of ways, all of which could be factors in influencing the distribution of giant sequoia and other species. Satellite and micrometeorological flux tower data reveal characteristics of the sequoia belt that were not evident with surface climate measurements and maps derived from them. Results have implications for species distributions everywhere, but especially in rugged mountains, where climates are complex and poorly mapped. Chapter 5 summarizes some of the main conclusions from the work and suggests directions for related future research. (Abstract shortened by UMI.).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28894099','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28894099"><span>Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Aalto, Juha; Harrison, Stephan; Luoto, Miska</p> <p>2017-09-11</p> <p>The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26PSL.486...61M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26PSL.486...61M"><span>Mineralogical evidence of reduced East Asian summer monsoon rainfall on the Chinese loess plateau during the early Pleistocene interglacials</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meng, Xianqiang; Liu, Lianwen; Wang, Xingchen T.; Balsam, William; Chen, Jun; Ji, Junfeng</p> <p>2018-03-01</p> <p>The East Asian summer monsoon (EASM) is an important component of the global climate system. A better understanding of EASM rainfall variability in the past can help constrain climate models and better predict the response of EASM to ongoing global warming. The warm early Pleistocene, a potential analog of future climate, is an important period to study EASM dynamics. However, existing monsoon proxies for reconstruction of EASM rainfall during the early Pleistocene fail to disentangle monsoon rainfall changes from temperature variations, complicating the comparison of these monsoon records with climate models. Here, we present three 2.6 million-year-long EASM rainfall records from the Chinese Loess Plateau (CLP) based on carbonate dissolution, a novel proxy for rainfall intensity. These records show that the interglacial rainfall on the CLP was lower during the early Pleistocene and then gradually increased with global cooling during the middle and late Pleistocene. These results are contrary to previous suggestions that a warmer climate leads to higher monsoon rainfall on tectonic timescales. We propose that the lower interglacial EASM rainfall during the early Pleistocene was caused by reduced sea surface temperature gradients across the equatorial Pacific, providing a testable hypothesis for climate models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29451851','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29451851"><span>Validation of a pre-existing safety climate scale for the Turkish furniture manufacturing industry.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Akyuz, Kadri Cemil; Yildirim, Ibrahim; Gungor, Celal</p> <p>2018-03-22</p> <p>Understanding the safety climate level is essential to implement a proactive safety program. The objective of this study is to explore the possibility of having a safety climate scale for the Turkish furniture manufacturing industry since there has not been any scale available. The questionnaire recruited 783 subjects. Confirmatory factor analysis (CFA) tested a pre-existing safety scale's fit to the industry. The CFA indicated that the structures of the model present a non-satisfactory fit with the data (χ 2  = 2033.4, df = 314, p ≤ 0.001; root mean square error of approximation = 0.08, normed fit index = 0.65, Tucker-Lewis index = 0.65, comparative fit index = 0.69, parsimony goodness-of-fit index = 0.68). The results suggest that a new scale should be developed and validated to measure the safety climate level in the Turkish furniture manufacturing industry. Due to the hierarchical structure of organizations, future studies should consider a multilevel approach in their exploratory factor analyses while developing a new scale.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.C13B0433B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.C13B0433B"><span>Glaciological reconstruction of Holocene ice margins in northwestern Greenland</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Birkel, S. D.; Osterberg, E. C.; Kelly, M. A.; Axford, Y.</p> <p>2014-12-01</p> <p>The past few decades of climate warming have brought overall margin retreat to the Greenland Ice Sheet. In order to place recent and projected changes in context, we are undertaking a collaborative field-modeling study that aims to reconstruct the Holocene history of ice-margin fluctuation near Thule (~76.5°N, 68.7°W), and also along the North Ice Cap (NIC) in the Nunatarssuaq region (~76.7°N, 67.4°W). Fieldwork reported by Kelly et al. (2013) reveals that ice in the study areas was less extensive than at present ca. 4700 (GIS) and ca. 880 (NIC) cal. years BP, presumably in response to a warmer climate. We are now exploring Holocene ice-climate coupling using the University of Maine Ice Sheet Model (UMISM). Our approach is to first test what imposed climate anomalies can afford steady state ice margins in accord with field data. A second test encompasses transient simulation of the Holocene, with climate boundary conditions supplied by existing paleo runs of the Community Climate System Model version 4 (CCSM4), and a climate forcing signal derived from Greenland ice cores. In both cases, the full ice sheet is simulated at 10 km resolution with nested domains at 0.5 km for the study areas. UMISM experiments are underway, and results will be reported at the meeting.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H14G..07O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H14G..07O"><span>Downscaling Future Climate Change Projections for Water Resource Applications: A Case Study for Mesoamerica (Invited)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oglesby, R. J.; Rowe, C. M.; Munoz-Arriola, F.</p> <p>2013-12-01</p> <p>Mesoamerica is a region that is potentially at severe risk due to future climate change. This is especially true for the water resources required for agriculture, human consumption, and hydroelectric power generation. Yet global climate models cannot properly resolve surface climate in the region, due to it's complex topography and nearness to oceans. Precipitation in particular is poorly handled. Further, Mesoamerica is hardly the only region worldwide for which these issues exist. To address this deficiency, a series of high-resolution (4-12 km) dynamical downscaling simulations of future climate change between now and 2060 have been made for Mesoamerica and the Caribbean. We used the Weather Research and Forecasting (WRF) regional climate model to downscale results from the NCAR CCSM4 CMIP5 RCP8.5 global simulation. The entire region is covered at 12 km horizontal spatial resolution, with as much as possible (especially in mountainous regions) at 4 km. We compare a control period (2006-2010) with 50 years into the future (2056-2060). Basic results for surface climate will be presented, as well as a developing strategy for explicitly employing these results in projecting the implications for water resources in the region. Connections will also be made to other regions around the globe that could benefit from this type of integrated modeling and analysis.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC33G..01R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC33G..01R"><span>Tropical and Extratropical Cyclone Damages under Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ranson, M.; Kousky, C.; Ruth, M.; Jantarasami, L.; Crimmins, A.; Tarquinio, L.</p> <p>2014-12-01</p> <p>This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone losses under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 296 estimates of the temperature-damage relationship from twenty studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models (84 and 92 percent, respectively) predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5°C increase in global surface air temperature would cause hurricane damages to increase by 62 percent. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are approximately one third of that magnitude. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22860062','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22860062"><span>Niche tracking and rapid establishment of distributional equilibrium in the house sparrow show potential responsiveness of species to climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Monahan, William B; Tingley, Morgan W</p> <p>2012-01-01</p> <p>The ability of species to respond to novel future climates is determined in part by their physiological capacity to tolerate climate change and the degree to which they have reached and continue to maintain distributional equilibrium with the environment. While broad-scale correlative climatic measurements of a species' niche are often described as estimating the fundamental niche, it is unclear how well these occupied portions actually approximate the fundamental niche per se, versus the fundamental niche that exists in environmental space, and what fitness values bounding the niche are necessary to maintain distributional equilibrium. Here, we investigate these questions by comparing physiological and correlative estimates of the thermal niche in the introduced North American house sparrow (Passer domesticus). Our results indicate that occupied portions of the fundamental niche derived from temperature correlations closely approximate the centroid of the existing fundamental niche calculated on a fitness threshold of 50% population mortality. Using these niche measures, a 75-year time series analysis (1930-2004) further shows that: (i) existing fundamental and occupied niche centroids did not undergo directional change, (ii) interannual changes in the two niche centroids were correlated, (iii) temperatures in North America moved through niche space in a net centripetal fashion, and consequently, (iv) most areas throughout the range of the house sparrow tracked the existing fundamental niche centroid with respect to at least one temperature gradient. Following introduction to a new continent, the house sparrow rapidly tracked its thermal niche and established continent-wide distributional equilibrium with respect to major temperature gradients. These dynamics were mediated in large part by the species' broad thermal physiological tolerances, high dispersal potential, competitive advantage in human-dominated landscapes, and climatically induced changes to the realized environmental space. Such insights may be used to conceptualize mechanistic climatic niche models in birds and other taxa.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A13A0190O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A13A0190O"><span>AN INITIAL ASSESSMENT OF THE CLIMATE IMPACT OF SECONDARY ORGANIC AEROSOLS</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>O'Donnell, D.; Feichter, J.</p> <p>2009-12-01</p> <p>Atmospheric aerosols influence the Earth’s climate by absorbing and scattering solar radiation (the direct effect) and by altering the properties of clouds (indirect effects). Measurements have shown that a substantial fraction of the tropospheric aerosol burden consists of organic compounds. Hundreds of different organic species have been identified. While progress has been made in the understanding of the role of certain aerosol types in the climate system, that of organic aerosols remains poorly understood and the climate influences resulting from their presence poorly constrained. Organic aerosols are emitted directly from the surface (primary organic aerosols, POA) and are also formed in the atmosphere from gaseous precursors by oxidation reactions (secondary organic aerosols, SOA). Both biogenic and anthropogenic precursors have been identified. Biogenic emissions of aerosol precursors are known to be climate-dependent. Thus, a bi-directional dependency exists between the biosphere and the atmosphere, whereby aerosols of biogenic origin influence the climate system, which in turn affects biogenic aerosol precursor production. This study builds upon the global aerosol-climate model ECHAM5/HAM and adds techniques to model SOA as well as the necessary global emission inventories. Emission of biogenic precursors is calculated online. Formation of SOA is modeled by the well-known two-product model of SOA formation. SOA is subject to the same aerosol microphysics and sink processes as other modeled species (sulphate, black carbon, primary organic carbon, sea salt and dust). The aerosol radiative effects are calculated on a size resolved basis, and the aerosol scheme is coupled to the model cloud microphysics, permitting estimation of both direct and indirect aerosol effects. The following results will be discussed: (i) Estimation of the direct and indirect effects of biogenic and anthropogenic SOA, (ii) Estimation of the sign and magnitude of the biospheric feedback (through biogenic aerosol precursor emission) on the climate system, and (iii) Identification of physical processes and aerosol physical properties that need further experimental investigation in order to improve our understanding of the climate impact of SOA</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMED33B0755C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMED33B0755C"><span>Using Web 2.0 Techniques To Bring Global Climate Modeling To More Users</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chandler, M. A.; Sohl, L. E.; Tortorici, S.</p> <p>2012-12-01</p> <p>The Educational Global Climate Model has been used for many years in undergraduate courses and professional development settings to teach the fundamentals of global climate modeling and climate change simulation to students and teachers. While course participants have reported a high level of satisfaction in these courses and overwhelmingly claim that EdGCM projects are worth the effort, there is often a high level of frustration during the initial learning stages. Many of the problems stem from issues related to installation of the software suite and to the length of time it can take to run initial experiments. Two or more days of continuous run time may be required before enough data has been gathered to begin analyses. Asking users to download existing simulation data has not been a solution because the GCM data sets are several gigabytes in size, requiring substantial bandwidth and stable dedicated internet connections. As a means of getting around these problems we have been developing a Web 2.0 utility called EzGCM (Easy G-G-M) which emphasizes that participants learn the steps involved in climate modeling research: constructing a hypothesis, designing an experiment, running a computer model and assessing when an experiment has finished (reached equilibrium), using scientific visualization to support analysis, and finally communicating the results through social networking methods. We use classic climate experiments that can be "rediscovered" through exercises with EzGCM and are attempting to make this Web 2.0 tool an entry point into climate modeling for teachers with little time to cover the subject, users with limited computer skills, and for those who want an introduction to the process before tackling more complex projects with EdGCM.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24664919','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24664919"><span>Possible climates on terrestrial exoplanets.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Forget, F; Leconte, J</p> <p>2014-04-28</p> <p>What kind of environment may exist on terrestrial planets around other stars? In spite of the lack of direct observations, it may not be premature to speculate on exoplanetary climates, for instance, to optimize future telescopic observations or to assess the probability of habitable worlds. To begin with, climate primarily depends on (i) the atmospheric composition and the volatile inventory; (ii) the incident stellar flux; and (iii) the tidal evolution of the planetary spin, which can notably lock a planet with a permanent night side. The atmospheric composition and mass depends on complex processes, which are difficult to model: origins of volatiles, atmospheric escape, geochemistry, photochemistry, etc. We discuss physical constraints, which can help us to speculate on the possible type of atmosphere, depending on the planet size, its final distance for its star and the star type. Assuming that the atmosphere is known, the possible climates can be explored using global climate models analogous to the ones developed to simulate the Earth as well as the other telluric atmospheres in the solar system. Our experience with Mars, Titan and Venus suggests that realistic climate simulators can be developed by combining components, such as a 'dynamical core', a radiative transfer solver, a parametrization of subgrid-scale turbulence and convection, a thermal ground model and a volatile phase change code. On this basis, we can aspire to build reliable climate predictors for exoplanets. However, whatever the accuracy of the models, predicting the actual climate regime on a specific planet will remain challenging because climate systems are affected by strong positive feedbacks. They can drive planets with very similar forcing and volatile inventory to completely different states. For instance, the coupling among temperature, volatile phase changes and radiative properties results in instabilities, such as runaway glaciations and runaway greenhouse effect.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A23L..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A23L..06S"><span>The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.</p> <p>2016-12-01</p> <p>Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24677422','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24677422"><span>Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lambert, Emily; Pierce, Graham J; Hall, Karen; Brereton, Tom; Dunn, Timothy E; Wall, Dave; Jepson, Paul D; Deaville, Rob; MacLeod, Colin D</p> <p>2014-06-01</p> <p>There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio-climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs "hindcasting" of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species-specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white-beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time-scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies. © 2014 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1988JCli....1..669C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1988JCli....1..669C"><span>The Potential Impacts of a Scenario of C02-Induced Climatic Change on Ontafio, Canada.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cohen, S. J.; Allsopp, T. R.</p> <p>1988-07-01</p> <p>In 1984, Environment Canada, Ontario Region, with financial and expert support from the Canadian Climate Program, initiated an interdisciplinary pilot study to investigate the potential impact, on Ontario, of a climate scenario which might be anticipated under doubling of atmospheric C02 conditions.There were many uncertainties involved in the climate scenario development and the impacts modeling. Time and resource constraints restricted this study to one climate scenario and to the selection of several available models that could be adapted to these impact studies. The pilot study emphasized the approach and process required to investigate potential regional impacts in an interdisciplinary manner, rather than to produce a forecast of the future.The climate scenario chosen was adapted from experimental model results produced by the Goddard Institute for Space Studies (GISS), coupled with current climate normals. Gridded monthly mean temperatures and precipitation were then used to develop projected biophysical effects. For example, existing physical and/or statistical models were adapted to determine impacts on the Great Lakes net basin supplies, levels and outflows, streamflow subbasin, snowfall and length of snow season.The second phase of the study addressed the impacts of the climate system scenario on natural resources and resource dependent activities. For example, the impacts of projected decreased lake levels and outflows on commercial navigation and hydroelectric generation were assessed. The impacts of the climate scenario on municipal water use, residential beating and cooling energy requirements opportunities and constraints for food production and tourism and recreation were determined quantitatively where models and methodologies were available, otherwise, qualitatively.First order interdependencies of the biophysical effects of the climate scenario and resource dependent activities were evaluated qualitatively in a workshop format culminating in a series of statements on (i) possible preventive, compensatory and substitution strategies and (ii) an assessment of current knowledge gaps and deficiencies, with recommendations for future areas of research.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/39708','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/39708"><span>A project in two parts: Developing fire histories for the eastern U.S. and creating a climate-based continental fire frequency model to fill data gaps</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Richard Guyette; Michael Stambaugh; Daniel Dey</p> <p>2011-01-01</p> <p>Tree-ring dated fire scars provide long-term records of fire frequency, giving land managers valuable baseline information about the fire regimes that existed prior to Euro-American settlement. However, for the East, fire history data prove difficult to acquire because the generally moister climate of the region causes rapid decay of wood. In an endeavor to fill data...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23625663','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23625663"><span>Modelling the effects of climate change on the distribution and production of marine fishes: accounting for trophic interactions in a dynamic bioclimate envelope model.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fernandes, Jose A; Cheung, William W L; Jennings, Simon; Butenschön, Momme; de Mora, Lee; Frölicher, Thomas L; Barange, Manuel; Grant, Alastair</p> <p>2013-08-01</p> <p>Climate change has already altered the distribution of marine fishes. Future predictions of fish distributions and catches based on bioclimate envelope models are available, but to date they have not considered interspecific interactions. We address this by combining the species-based Dynamic Bioclimate Envelope Model (DBEM) with a size-based trophic model. The new approach provides spatially and temporally resolved predictions of changes in species' size, abundance and catch potential that account for the effects of ecological interactions. Predicted latitudinal shifts are, on average, reduced by 20% when species interactions are incorporated, compared to DBEM predictions, with pelagic species showing the greatest reductions. Goodness-of-fit of biomass data from fish stock assessments in the North Atlantic between 1991 and 2003 is improved slightly by including species interactions. The differences between predictions from the two models may be relatively modest because, at the North Atlantic basin scale, (i) predators and competitors may respond to climate change together; (ii) existing parameterization of the DBEM might implicitly incorporate trophic interactions; and/or (iii) trophic interactions might not be the main driver of responses to climate. Future analyses using ecologically explicit models and data will improve understanding of the effects of inter-specific interactions on responses to climate change, and better inform managers about plausible ecological and fishery consequences of a changing environment. © 2013 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.U13B0068P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.U13B0068P"><span>A Model for Climate Change Adaptation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pasqualini, D.; Keating, G. N.</p> <p>2009-12-01</p> <p>Climate models predict serious impacts on the western U.S. in the next few decades, including increased temperatures and reduced precipitation. In combination, these changes are linked to profound impacts on fundamental systems, such as water and energy supplies, agriculture, population stability, and the economy. Global and national imperatives for climate change mitigation and adaptation are made actionable at the state level, for instance through greenhouse gas (GHG) emission regulations and incentives for renewable energy sources. However, adaptation occurs at the local level, where energy and water usage can be understood relative to local patterns of agriculture, industry, and culture. In response to the greenhouse gas emission reductions required by California’s Assembly Bill 32 (2006), Sonoma County has committed to sharp emissions reductions across several sectors, including water, energy, and transportation. To assist Sonoma County develop a renewable energy (RE) portfolio to achieve this goal we have developed an integrated assessment model, CLEAR (CLimate-Energy Assessment for Resiliency) model. Building on Sonoma County’s existing baseline studies of energy use, carbon emissions and potential RE sources, the CLEAR model simulates the complex interactions among technology deployment, economics and social behavior. This model enables assessment of these and other components with specific analysis of their coupling and feedbacks because, due to the complex nature of the problem, the interrelated sectors cannot be studied independently. The goal is an approach to climate change mitigation and adaptation that is replicable for use by other interested communities. The model user interfaces helps stakeholders and policymakers understand options for technology implementation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011FrES....5..363C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011FrES....5..363C"><span>Adapting water treatment design and operations to the impacts of global climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clark, Robert M.; Li, Zhiwei; Buchberger, Steven G.</p> <p>2011-12-01</p> <p>It is anticipated that global climate change will adversely impact source water quality in many areas of the United States and will therefore, potentially, impact the design and operation of current and future water treatment systems. The USEPA has initiated an effort called the Water Resources Adaptation Program (WRAP) which is intended to develop tools and techniques that can assess the impact of global climate change on urban drinking water and wastewater infrastructure. A three step approach for assessing climate change impacts on water treatment operation and design is being persude in this effort. The first step is the stochastic characterization of source water quality, the second step is the application of the USEPA Water Treatment Plant model and the third step is the application of cost algorithms to provide a metric that can be used to assess the coat impact of climate change. A model has been validated using data collected from Cincinnati's Richard Miller Water Treatment Plant for the USEPA Information Collection Rule (ICR) database. An analysis of the water treatment processes in response to assumed perturbations in raw water quality identified TOC, pH, and bromide as the three most important parameters affecting performance of the Miller WTP. The Miller Plant was simulated using the EPA WTP model to examine the impact of these parameters on selected regulated water quality parameters. Uncertainty in influent water quality was analyzed to estimate the risk of violating drinking water maximum contaminant levels (MCLs).Water quality changes in the Ohio River were projected for 2050 using Monte Carlo simulation and the WTP model was used to evaluate the effects of water quality changes on design and operation. Results indicate that the existing Miller WTP might not meet Safe Drinking Water Act MCL requirements for certain extreme future conditions. However, it was found that the risk of MCL violations under future conditions could be controlled by enhancing existing WTP design and operation or by process retrofitting and modification.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29522016','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29522016"><span>First decadal lunar results from the Moon and Earth Radiation Budget Experiment.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Matthews, Grant</p> <p>2018-03-01</p> <p>A need to gain more confidence in computer model predictions of coming climate change has resulted in greater analysis of the quality of orbital Earth radiation budget (ERB) measurements being used today to constrain, validate, and hence improve such simulations. These studies conclude from time series analysis that for around a quarter of a century, no existing satellite ERB climate data record is of a sufficient standard to partition changes to the Earth from those of un-tracked and changing artificial instrumentation effects. This led to the creation of the Moon and Earth Radiation Budget Experiment (MERBE), which instead takes existing decades old climate data to a higher calibration standard using thousands of scans of Earth's Moon. The Terra and Aqua satellite ERB climate records have been completely regenerated using signal-processing improvements, combined with a substantial increase in precision from more comprehensive in-flight spectral characterization techniques. This study now builds on previous Optical Society of America work by describing new Moon measurements derived using accurate analytical mapping of telescope spatial response. That then allows a factor of three reduction in measurement noise along with an order of magnitude increase in the number of retrieved independent lunar results. Given decadal length device longevity and the use of solar and thermal lunar radiance models to normalize the improved ERB results to the International System of Units traceable radiance scale of the "MERBE Watt," the same established environmental time series analysis techniques are applied to MERBE data. They evaluate it to perhaps be of sufficient quality to immediately begin narrowing the largest of climate prediction uncertainties. It also shows that if such Terra/Aqua ERB devices can operate into the 2020s, it could become possible to halve these same uncertainties decades sooner than would be possible with existing or even planned new observing systems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27458474','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27458474"><span>TreeWatch.net: A Water and Carbon Monitoring and Modeling Network to Assess Instant Tree Hydraulics and Carbon Status.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Steppe, Kathy; von der Crone, Jonas S; De Pauw, Dirk J W</p> <p>2016-01-01</p> <p>TreeWatch.net is an initiative that has been developed to watch trees grow and function in real-time. It is a water- and carbon-monitoring and modeling network, in which high-quality measurements of sap flow and stem diameter variation are collected on individual trees. Automated data processing using a cloud service enables instant visualization of water movement and radial stem growth. This can be used to demonstrate the sensitivity of trees to changing weather conditions, such as drought, heat waves, or heavy rain showers. But TreeWatch.net's true innovation lies in its use of these high-precision harmonized data to also parameterize process-based tree models in real-time, which makes displaying the much-needed mechanisms underlying tree responses to climate change possible. Continuous simulation of turgor to describe growth processes and long-term time series of hydraulic resistance to assess drought-vulnerability in real-time are only a few of the opportunities our approach offers. TreeWatch.net has been developed with the view to be complementary to existing forest monitoring networks and with the aim to contribute to existing dynamic global vegetation models. It provides high-quality data and real-time simulations in order to advance research on the impact of climate change on the biological response of trees and forests. Besides its application in natural forests to answer climate-change related scientific and political questions, we also envision a broader societal application of TreeWatch.net by selecting trees in nature reserves, public areas, cities, university areas, schoolyards, and parks to teach youngsters and create public awareness on the effects of changing weather conditions on trees and forests in this era of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.6355V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.6355V"><span>Climate projections of the ALARO-0 model on the EURO-CORDEX domain</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van Schaeybroeck, Bert; Berckmans, Julie; Caluwaerts, Steven; De Troch, Rozemien; De Cruz, Lesley; Duchêne, François; Giot, Olivier; Hamdi, Rafiq; Termonia, Piet</p> <p>2016-04-01</p> <p>Results of the future scenario runs are presented within the EURO-CORDEX framework using the regional climate model ALARO-0. This model has been primarily developed for operational numerical weather predictions and is therefore not tuned specifically for climate purposes. It features a new microphysics scheme called 3MT, which allows for a more sophisticated representation of convective precipitation. In Giot et al. (2015) validation results were presented for the 12.5-km and 50-km resolution runs forced by ERA-Interim reanalysis. It was shown that ALARO-0 is well capable of representing the European climate. More specifically, most of the ALARO-0 scores were within the existing EURO-CORDEX ensemble. For precipitation, due to the 3MT scheme, the ALARO-0 model produces some of the best scores within the ensemble. The comparison of the historical run with the climate scenarios runs (RCP8.5, RCP4.5) allows the determination of the ALARO-0 climate changes. These runs are all coupled to the GCM of Météo-France, namely CNRM-CM5. The climate-change signals are investigated with a focus on heavy precipitation and heat wave changes and the signals are put against the ones of the other EURO-CORDEX models (Jacob et al., 2013). Giot, O., Termonia, P., Degrauwe, D., De Troch, R., Caluwaerts, S., Smet, G., Berckmans, J., Deckmyn, A., De Cruz, L., De Meutter, P., Duerinckx, A., Gerard, L., Hamdi, R., Van den Bergh, J., Van Ginderachter, M., and Van Schaeybroeck, B.: Validation of the ALARO-0 model within the EURO-CORDEX framework, Geosci. Model Dev. Discuss., 8, 8387-8409, 2015. Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer, L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G., et al., 2014. EURO-CORDEX: new high-resolution climate change projections for european impact research. Regional Environmental Change 14 (2), 563-578.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29212051','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29212051"><span>Land use and climate change impacts on runoff and soil erosion at the hillslope scale in the Brazilian Cerrado.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Anache, Jamil A A; Flanagan, Dennis C; Srivastava, Anurag; Wendland, Edson C</p> <p>2018-05-01</p> <p>Land use and climate change can influence runoff and soil erosion, threatening soil and water conservation in the Cerrado biome in Brazil. The adoption of a process-based model was necessary due to the lack of long-term observed data. Our goals were to calibrate the WEPP (Water Erosion Prediction Project) model for different land uses under subtropical conditions in the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change. We performed the model calibration using a 5-year dataset (2012-2016) of observed runoff and soil loss in four different land uses (wooded Cerrado, tilled fallow without plant cover, pasture, and sugarcane) in experimental plots. Selected soil and management parameters were optimized for each land use during the WEPP model calibration with the existing field data. The simulations were conducted using the calibrated WEPP model components with a 100-year climate dataset created with CLIGEN (weather generator) based on regional climate statistics. We obtained downscaled General Circulation Model (GCM) projections, and runoff and soil loss were predicted with WEPP using future climate scenarios for 2030, 2060, and 2090 considering different Representative Concentration Pathways (RCPs). The WEPP model had an acceptable performance for the subtropical conditions. Land use can influence runoff and soil loss rates in a significant way. Potential climate changes, which indicate the increase of rainfall intensities and depths, may increase the variability and rates of runoff and soil erosion. However, projected climate changes did not significantly affect the runoff and soil erosion for the four analyzed land uses at our location. Finally, the runoff behavior was distinct for each land use, but for soil loss we found similarities between pasture and wooded Cerrado, suggesting that the soil may attain a sustainable level when the land management follows conservation principles. Copyright © 2017 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..873H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..873H"><span>Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat</p> <p>2017-11-01</p> <p>In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020090248','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020090248"><span>The Finer Details: Climate Modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2000-01-01</p> <p>If you want to know whether you will need sunscreen or an umbrella for tomorrow's picnic, you can simply read the local weather report. However, if you are calculating the impact of gas combustion on global temperatures, or anticipating next year's rainfall levels to set water conservation policy, you must conduct a more comprehensive investigation. Such complex matters require long-range modeling techniques that predict broad trends in climate development rather than day-to-day details. Climate models are built from equations that calculate the progression of weather-related conditions over time. Based on the laws of physics, climate model equations have been developed to predict a number of environmental factors, for example: 1. Amount of solar radiation that hits the Earth. 2. Varying proportions of gases that make up the air. 3. Temperature at the Earth's surface. 4. Circulation of ocean and wind currents. 5. Development of cloud cover. Numerical modeling of the climate can improve our understanding of both the past and, the future. A model can confirm the accuracy of environmental measurements taken. in, the past and can even fill in gaps in those records. In addition, by quantifying the relationship between different aspects of climate, scientists can estimate how a future change in one aspect may alter the rest of the world. For example, could an increase in the temperature of the Pacific Ocean somehow set off a drought on the other side of the world? A computer simulation could lead to an answer for this and other questions. Quantifying the chaotic, nonlinear activities that shape our climate is no easy matter. You cannot run these simulations on your desktop computer and expect results by the time you have finished checking your morning e-mail. Efficient and accurate climate modeling requires powerful computers that can process billions of mathematical calculations in a single second. The NCCS exists to provide this degree of vast computing capability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1130634','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1130634"><span>Evaluation of Modeled and Measured Energy Savings in Existing All Electric Public Housing in the Pacific Northwest</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Gordon, A.; Lubliner, M.; Howard, L.</p> <p>2014-04-01</p> <p>This project analyzes the cost effectiveness of energy savings measures installed by a large public housing authority in Salishan, a community in Tacoma Washington. Research focuses on the modeled and measured energy usage of the first six phases of construction, and compares the energy usage of those phases to phase 7. Market-ready energy solutions were also evaluated to improve the efficiency of affordable housing for new and existing (built since 2001) affordable housing in the marine climate of Washington State.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/272849-biomes-computed-from-simulated-climatologies','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/272849-biomes-computed-from-simulated-climatologies"><span>Biomes computed from simulated climatologies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Claussen, M.; Esch, M.</p> <p>1994-01-01</p> <p>The biome model of Prentice et al. is used to predict global patterns of potential natural plant formations, or biomes, from climatologies simulated by ECHAM, a model used for climate simulations at the Max-Planck-Institut fuer Meteorologie. This study undertaken in order to show the advantage of this biome model in diagnosing the performance of a climate model and assessing effects of past and future climate changes predicted by a climate model. Good overall agreement is found between global patterns of biomes computed from observed and simulated data of present climate. But there are also major discrepancies indicated by a differencemore » in biomes in Australia, in the Kalahari Desert, and in the Middle West of North America. These discrepancies can be traced back to in simulated rainfall as well as summer or winter temperatures. Global patterns of biomes computed from an ice age simulation reveal that North America, Europe, and Siberia should have been covered largely by tundra and taiga, whereas only small differences are for the tropical rain forests. A potential northeast shift of biomes is expected from a simulation with enhanced CO{sub 2} concentration according to the IPCC Scenario A. Little change is seen in the tropical rain forest and the Sahara. Since the biome model used is not capable of predicting chances in vegetation patterns due to a rapid climate change, the latter simulation to be taken as a prediction of chances in conditions favourable for the existence of certain biomes, not as a reduction of a future distribution of biomes. 15 refs., 8 figs., 2 tabs.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H21B1022G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H21B1022G"><span>Data-based discharge extrapolation: estimating annual discharge for a partially gauged large river basin from its small sub-basins</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gong, L.</p> <p>2013-12-01</p> <p>Large-scale hydrological models and land surface models are by far the only tools for accessing future water resources in climate change impact studies. Those models estimate discharge with large uncertainties, due to the complex interaction between climate and hydrology, the limited quality and availability of data, as well as model uncertainties. A new purely data-based scale-extrapolation method is proposed, to estimate water resources for a large basin solely from selected small sub-basins, which are typically two-orders-of-magnitude smaller than the large basin. Those small sub-basins contain sufficient information, not only on climate and land surface, but also on hydrological characteristics for the large basin In the Baltic Sea drainage basin, best discharge estimation for the gauged area was achieved with sub-basins that cover 2-4% of the gauged area. There exist multiple sets of sub-basins that resemble the climate and hydrology of the basin equally well. Those multiple sets estimate annual discharge for gauged area consistently well with 5% average error. The scale-extrapolation method is completely data-based; therefore it does not force any modelling error into the prediction. The multiple predictions are expected to bracket the inherent variations and uncertainties of the climate and hydrology of the basin. The method can be applied in both un-gauged basins and un-gauged periods with uncertainty estimation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28120830','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28120830"><span>Characterizing the impact of projected changes in climate and air quality on human exposures to ozone.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Dionisio, Kathie L; Nolte, Christopher G; Spero, Tanya L; Graham, Stephen; Caraway, Nina; Foley, Kristen M; Isaacs, Kristin K</p> <p>2017-05-01</p> <p>The impact of climate change on human and environmental health is of critical concern. Population exposures to air pollutants both indoors and outdoors are influenced by a wide range of air quality, meteorological, behavioral, and housing-related factors, many of which are also impacted by climate change. An integrated methodology for modeling changes in human exposures to tropospheric ozone (O 3 ) owing to potential future changes in climate and demographics was implemented by linking existing modeling tools for climate, weather, air quality, population distribution, and human exposure. Human exposure results from the Air Pollutants Exposure Model (APEX) for 12 US cities show differences in daily maximum 8-h (DM8H) exposure patterns and levels by sex, age, and city for all scenarios. When climate is held constant and population demographics are varied, minimal difference in O 3 exposures is predicted even with the most extreme demographic change scenario. In contrast, when population is held constant, we see evidence of substantial changes in O 3 exposure for the most extreme change in climate. Similarly, we see increases in the percentage of the population in each city with at least one O 3 exposure exceedance above 60 p.p.b and 70 p.p.b thresholds for future changes in climate. For these climate and population scenarios, the impact of projected changes in climate and air quality on human exposure to O 3 are much larger than the impacts of changing demographics. These results indicate the potential for future changes in O 3 exposure as a result of changes in climate that could impact human health.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19..854T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19..854T"><span>A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan</p> <p>2017-04-01</p> <p>Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19251790','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19251790"><span>Climate change and respiratory disease: European Respiratory Society position statement.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Ayres, J G; Forsberg, B; Annesi-Maesano, I; Dey, R; Ebi, K L; Helms, P J; Medina-Ramón, M; Windt, M; Forastiere, F</p> <p>2009-08-01</p> <p>Climate change will affect individuals with pre-existing respiratory disease, but the extent of the effect remains unclear. The present position statement was developed on behalf of the European Respiratory Society in order to identify areas of concern arising from climate change for individuals with respiratory disease, healthcare workers in the respiratory sector and policy makers. The statement was developed following a 2-day workshop held in Leuven (Belgium) in March 2008. Key areas of concern for the respiratory community arising from climate change are discussed and recommendations made to address gaps in knowledge. The most important recommendation was the development of more accurate predictive models for predicting the impact of climate change on respiratory health. Respiratory healthcare workers also have an advocatory role in persuading governments and the European Union to maintain awareness and appropriate actions with respect to climate change, and these areas are also discussed in the position statement.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A23F0398W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A23F0398W"><span>Transport and radiative impacts of atmospheric pollen using online, observation-based emissions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wozniak, M. C.; Steiner, A. L.; Solmon, F.; Li, Y.</p> <p>2015-12-01</p> <p>Atmospheric pollen emitted from trees and grasses exhibits both a high temporal variability and a highly localized spatial distribution that has been difficult to quantify in the atmosphere. Pollen's radiative impact is also not quantified because it is neglected in climate modeling studies. Here we couple an online, meteorological active pollen emissions model guided by observations of airborne pollen to understand the role of pollen in the atmosphere. We use existing pollen counts from 2003-2008 across the continental U.S. in conjunction with a tree database and historical meteorological data to create an observation-based phenological model that produces accurately scaled and timed emissions. These emissions are emitted and transported within the regional climate model (RegCM4) and the direct radiative effect is calculated. Additionally, we simulate the rupture of coarse pollen grains into finer particles by adding a second size mode for pollen emissions, which contributes to the shortwave radiative forcing and also has an indirect effect on climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A52E..07P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A52E..07P"><span>Influence of North Atlantic modes on European climate extremes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Proemmel, K.; Cubasch, U.</p> <p>2017-12-01</p> <p>It is well known that the North Atlantic strongly influences European climate. Only few studies exist that focus on its impact on climate extremes. We are interested in these extremes and the processes and mechanisms behind it. For the analysis of the North Atlantic Oscillation (NAO) we use simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM). The NAO has a strong impact especially on European winter and the changes in minimum temperature are even larger than in maximum temperature. The impact of the Atlantic Multi-decadal Variability (AMV) on climate extremes is analyzed in ECHAM6 simulations forced with AMV warm and AMV cold sea surface temperature patterns. We analyze different extreme indices and try to understand the processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23144839','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23144839"><span>Word diffusion and climate science.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bentley, R Alexander; Garnett, Philip; O'Brien, Michael J; Brock, William A</p> <p>2012-01-01</p> <p>As public and political debates often demonstrate, a substantial disjoint can exist between the findings of science and the impact it has on the public. Using climate-change science as a case example, we reconsider the role of scientists in the information-dissemination process, our hypothesis being that important keywords used in climate science follow "boom and bust" fashion cycles in public usage. Representing this public usage through extraordinary new data on word frequencies in books published up to the year 2008, we show that a classic two-parameter social-diffusion model closely fits the comings and goings of many keywords over generational or longer time scales. We suggest that the fashions of word usage contributes an empirical, possibly regular, correlate to the impact of climate science on society.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC51A0747W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC51A0747W"><span>The Use of Statistical Downscaling to Project Regional Climate Changes as they Relate to Future Energy Production</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Werth, D. W.; O'Steen, L.; Chen, K.; Altinakar, M. S.; Garrett, A.; Aleman, S.; Ramalingam, V.</p> <p>2010-12-01</p> <p>Global climate change has the potential for profound impacts on society, and poses significant challenges to government and industry in the areas of energy security and sustainability. Given that the ability to exploit energy resources often depends on the climate, the possibility of climate change means we cannot simply assume that the untapped potential of today will still exist in the future. Predictions of future climate are generally based on global climate models (GCMs) which, due to computational limitations, are run at spatial resolutions of hundreds of kilometers. While the results from these models can predict climatic trends averaged over large spatial and temporal scales, their ability to describe the effects of atmospheric phenomena that affect weather on regional to local scales is inadequate. We propose the use of several optimized statistical downscaling techniques that can infer climate change at the local scale from coarse resolution GCM predictions, and apply the results to assess future sustainability for two sources of energy production dependent on adequate water resources: nuclear power (through the dissipation of waste heat from cooling towers, ponds, etc.) and hydroelectric power. All methods will be trained with 20th century data, and applied to data from the years 2040-2049 to get the local-scale changes. Models of cooling tower operation and hydropower potential will then use the downscaled data to predict the possible changes in energy production, and the implications of climate change on plant siting, design, and contribution to the future energy grid can then be examined.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/6155','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/6155"><span>A biologically-based individual tree model for managing the longleaf pine ecosystem</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Rick Smith; Greg Somers</p> <p>1998-01-01</p> <p>Duration: 1995-present Objective: Develop a longleaf pine dynamics model and simulation system to define desirable ecosystem management practices in existing and future longleaf pine stands. Methods: Naturally-regenerated longleaf pine trees are being destructively sampled to measure their recent growth and dynamics. Soils and climate data will be combined with the...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA488754','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA488754"><span>Smart Climatology Applications for Undersea Warfare</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2008-09-01</p> <p>Comparisons of these climatologies with existing Navy climatologies based on the Generalized Digital Environmental Model ( GDEM ) reveal differences in sonic...undersea warfare. 15. NUMBER OF PAGES 117 14. SUBJECT TERMS antisubmarine warfare, climate variations, climatology, GDEM , ocean, re...climatologies based on the Generalized Digital Environmental Model ( GDEM ) to our smart ocean climatologies reveal a number of differences. The</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28068411','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28068411"><span>Projected Impacts of Climate, Urbanization, Water Management, and Wetland Restoration on Waterbird Habitat in California's Central Valley.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Matchett, Elliott L; Fleskes, Joseph P</p> <p>2017-01-01</p> <p>The Central Valley of California is one of the most important regions for wintering waterbirds in North America despite extensive anthropogenic landscape modification and decline of historical wetlands there. Like many other mediterranean-climate ecosystems across the globe, the Central Valley has been subject to a burgeoning human population and expansion and intensification of agricultural and urban development that have impacted wildlife habitats. Future effects of urban development, changes in water supply management, and precipitation and air temperature related to global climate change on area of waterbird habitat in the Central Valley are uncertain, yet potentially substantial. Therefore, we modeled area of waterbird habitats for 17 climate, urbanization, water supply management, and wetland restoration scenarios for years 2006-2099 using a water resources and scenario modeling framework. Planned wetland restoration largely compensated for adverse effects of climate, urbanization, and water supply management changes on habitat areas through 2065, but fell short thereafter for all except one scenario. Projected habitat reductions due to climate models were more frequent and greater than under the recent historical climate and their magnitude increased through time. After 2065, area of waterbird habitat in all scenarios that included severe warmer, drier climate was projected to be >15% less than in the "existing" landscape most years. The greatest reduction in waterbird habitat occurred in scenarios that combined warmer, drier climate and plausible water supply management options affecting priority and delivery of water available for waterbird habitats. This scenario modeling addresses the complexity and uncertainties in the Central Valley landscape, use and management of related water supplies, and climate to inform waterbird habitat conservation and other resource management planning. Results indicate that increased wetland restoration and additional conservation and climate change adaptation strategies may be warranted to maintain habitat adequate to support waterbirds in the Central Valley.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1418516-forecasting-climate-change-impacts-plant-populations-over-large-spatial-extents','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1418516-forecasting-climate-change-impacts-plant-populations-over-large-spatial-extents"><span>Forecasting climate change impacts on plant populations over large spatial extents</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...</p> <p>2016-10-24</p> <p>Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1418516','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1418516"><span>Forecasting climate change impacts on plant populations over large spatial extents</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.</p> <p></p> <p>Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70188067','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70188067"><span>Forecasting climate change impacts on plant populations over large spatial extents</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.</p> <p>2016-01-01</p> <p>Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23496320','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23496320"><span>Congruence between distribution modelling and phylogeographical analyses reveals Quaternary survival of a toadflax species (Linaria elegans) in oceanic climate areas of a mountain ring range.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fernández-Mazuecos, Mario; Vargas, Pablo</p> <p>2013-06-01</p> <p>· The role of Quaternary climatic shifts in shaping the distribution of Linaria elegans, an Iberian annual plant, was investigated using species distribution modelling and molecular phylogeographical analyses. Three hypotheses are proposed to explain the Quaternary history of its mountain ring range. · The distribution of L. elegans was modelled using the maximum entropy method and projected to the last interglacial and to the last glacial maximum (LGM) using two different paleoclimatic models: the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC). Two nuclear and three plastid DNA regions were sequenced for 24 populations (119 individuals sampled). Bayesian phylogenetic, phylogeographical, dating and coalescent-based population genetic analyses were conducted. · Molecular analyses indicated the existence of northern and southern glacial refugia and supported two routes of post-glacial recolonization. These results were consistent with the LGM distribution as inferred under the CCSM paleoclimatic model (but not under the MIROC model). Isolation between two major refugia was dated back to the Riss or Mindel glaciations, > 100 kyr before present (bp). · The Atlantic distribution of inferred refugia suggests that the oceanic (buffered)-continental (harsh) gradient may have played a key and previously unrecognized role in determining Quaternary distribution shifts of Mediterranean plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.1373Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.1373Z"><span>On the influence of simulated SST warming on rainfall projections in the Indo-Pacific domain: an AGCM study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Huqiang; Zhao, Y.; Moise, A.; Ye, H.; Colman, R.; Roff, G.; Zhao, M.</p> <p>2018-02-01</p> <p>Significant uncertainty exists in regional climate change projections, particularly for rainfall and other hydro-climate variables. In this study, we conduct a series of Atmospheric General Circulation Model (AGCM) experiments with different future sea surface temperature (SST) warming simulated by a range of coupled climate models. They allow us to assess the extent to which uncertainty from current coupled climate model rainfall projections can be attributed to their simulated SST warming. Nine CMIP5 model-simulated global SST warming anomalies have been super-imposed onto the current SSTs simulated by the Australian climate model ACCESS1.3. The ACCESS1.3 SST-forced experiments closely reproduce rainfall means and interannual variations as in its own fully coupled experiments. Although different global SST warming intensities explain well the inter-model difference in global mean precipitation changes, at regional scales the SST influence vary significantly. SST warming explains about 20-25% of the patterns of precipitation changes in each of the four/five models in its rainfall projections over the oceans in the Indo-Pacific domain, but there are also a couple of models in which different SST warming explains little of their precipitation pattern changes. The influence is weaker again for rainfall changes over land. Roughly similar levels of contribution can be attributed to different atmospheric responses to SST warming in these models. The weak SST influence in our study could be due to the experimental setup applied: superimposing different SST warming anomalies onto the same SSTs simulated for current climate by ACCESS1.3 rather than directly using model-simulated past and future SSTs. Similar modelling and analysis from other modelling groups with more carefully designed experiments are needed to tease out uncertainties caused by different SST warming patterns, different SST mean biases and different model physical/dynamical responses to the same underlying SST forcing.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21553956','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21553956"><span>Public understanding of climate change in the United States.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Weber, Elke U; Stern, Paul C</p> <p>2011-01-01</p> <p>This article considers scientific and public understandings of climate change and addresses the following question: Why is it that while scientific evidence has accumulated to document global climate change and scientific opinion has solidified about its existence and causes, U.S. public opinion has not and has instead become more polarized? Our review supports a constructivist account of human judgment. Public understanding is affected by the inherent difficulty of understanding climate change, the mismatch between people's usual modes of understanding and the task, and, particularly in the United States, a continuing societal struggle to shape the frames and mental models people use to understand the phenomena. We conclude by discussing ways in which psychology can help to improve public understanding of climate change and link a better understanding to action. (PsycINFO Database Record (c) 2011 APA, all rights reserved).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B11I..06P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B11I..06P"><span>To Tip or Not to Tip: The Case of the Congo Basin Rainforest Realm</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pietsch, S.; Bednar, J. E.; Fath, B. D.; Winter, P. A.</p> <p>2017-12-01</p> <p>The future response of the Congo basin rainforest, the second largest tropical carbon reservoir, to climate change is still under debate. Different Climate projections exist stating increase and decrease in rainfall and different changes in rainfall patterns. Within this study we assess all options of climate change possibilities to define the climatic thresholds of Congo basin rainforest stability and assess the limiting conditions for rainforest persistence. We use field data from 199 research plots from the Western Congo basin to calibrate and validate a complex BioGeoChemistry model (BGC-MAN) and assess model performance against an array of possible future climates. Next, we analyze the reasons for the occurrence of tipping points, their spatial and temporal probability of occurrence, will present effects of hysteresis and derive probabilistic spatial-temporal resilience landscapes for the region. Additionally, we will analyze attractors of forest growth dynamics and assess common linear measures for early warning signals of sudden shifts in system dynamics for their robustness in the context of the Congo Basin case, and introduce the correlation integral as a nonlinear measure of risk assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3831493','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3831493"><span>Stratospheric water vapor feedback</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Dessler, A. E.; Schoeberl, M. R.; Wang, T.; Davis, S. M.; Rosenlof, K. H.</p> <p>2013-01-01</p> <p>We show here that stratospheric water vapor variations play an important role in the evolution of our climate. This comes from analysis of observations showing that stratospheric water vapor increases with tropospheric temperature, implying the existence of a stratospheric water vapor feedback. We estimate the strength of this feedback in a chemistry–climate model to be +0.3 W/(m2⋅K), which would be a significant contributor to the overall climate sensitivity. One-third of this feedback comes from increases in water vapor entering the stratosphere through the tropical tropopause layer, with the rest coming from increases in water vapor entering through the extratropical tropopause. PMID:24082126</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2040370','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=2040370"><span>Projecting Heat-Related Mortality Impacts Under a Changing Climate in the New York City Region</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Knowlton, Kim; Lynn, Barry; Goldberg, Richard A.; Rosenzweig, Cynthia; Hogrefe, Christian; Rosenthal, Joyce Klein; Kinney, Patrick L.</p> <p>2007-01-01</p> <p>Objectives. We sought to project future impacts of climate change on summer heat-related premature deaths in the New York City metropolitan region. Methods. Current and future climates were simulated over the northeastern United States with a global-to-regional climate modeling system. Summer heat-related premature deaths in the 1990s and 2050s were estimated by using a range of scenarios and approaches to modeling acclimatization (e.g., increased use of air conditioning, gradual physiological adaptation). Results. Projected regional increases in heat-related premature mortality by the 2050s ranged from 47% to 95%, with a mean 70% increase compared with the 1990s. Acclimatization effects reduced regional increases in summer heat-related premature mortality by about 25%. Local impacts varied considerably across the region, with urban counties showing greater numbers of deaths and smaller percentage increases than less-urbanized counties. Conclusions. Although considerable uncertainty exists in climate forecasts and future health vulnerability, the range of projections we developed suggests that by midcentury, acclimatization may not completely mitigate the effects of climate change in the New York City metropolitan region, which would result in an overall net increase in heat-related premature mortality. PMID:17901433</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70155521','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70155521"><span>Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn</p> <p>2015-01-01</p> <p>Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC53G1287J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC53G1287J"><span>Assessing the impact of future climate extremes on the US corn and soybean production</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jin, Z.</p> <p>2015-12-01</p> <p>Future climate changes will place big challenges to the US agricultural system, among which increasing heat stress and precipitation variability were the two major concerns. Reliable prediction of crop productions in response to the increasingly frequent and severe extreme climate is a prerequisite for developing adaptive strategies on agricultural risk management. However, the progress has been slow on quantifying the uncertainty of computational predictions at high spatial resolutions. Here we assessed the risks of future climate extremes on the US corn and soybean production using the Agricultural Production System sIMulator (APSIM) model under different climate scenarios. To quantify the uncertainty due to conceptual representations of heat, drought and flooding stress in crop models, we proposed a new strategy of algorithm ensemble in which different methods for simulating crop responses to those extreme climatic events were incorporated into the APSIM. This strategy allowed us to isolate irrelevant structure differences among existing crop models but only focus on the process of interest. Future climate inputs were derived from high-spatial-resolution (12km × 12km) Weather Research and Forecasting (WRF) simulations under Representative Concentration Pathways 4.5 (RCP 4.5) and 8.5 (RCP 8.5). Based on crop model simulations, we analyzed the magnitude and frequency of heat, drought and flooding stress for the 21st century. We also evaluated the water use efficiency and water deficit on regional scales if farmers were to boost their yield by applying more fertilizers. Finally we proposed spatially explicit adaptation strategies of irrigation and fertilizing for different management zones.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC53B1203G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC53B1203G"><span>Applying Multimodel Ensemble from Regional Climate Models for Improving Runoff Projections on Semiarid Regions of Spain</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Garcia Galiano, S. G.; Olmos, P.; Giraldo Osorio, J. D.</p> <p>2015-12-01</p> <p>In the Mediterranean area, significant changes on temperature and precipitation are expected throughout the century. These trends could exacerbate the existing conditions in regions already vulnerable to climatic variability, reducing the water availability. Improving knowledge about plausible impacts of climate change on water cycle processes at basin scale, is an important step for building adaptive capacity to the impacts in this region, where severe water shortages are expected for the next decades. RCMs ensemble in combination with distributed hydrological models with few parameters, constitutes a valid and robust methodology to increase the reliability of climate and hydrological projections. For reaching this objective, a novel methodology for building Regional Climate Models (RCMs) ensembles of meteorological variables (rainfall an temperatures), was applied. RCMs ensembles are justified for increasing the reliability of climate and hydrological projections. The evaluation of RCMs goodness-of-fit to build the ensemble is based on empirical probability density functions (PDF) extracted from both RCMs dataset and a highly resolution gridded observational dataset, for the time period 1961-1990. The applied method is considering the seasonal and annual variability of the rainfall and temperatures. The RCMs ensembles constitute the input to a distributed hydrological model at basin scale, for assessing the runoff projections. The selected hydrological model is presenting few parameters in order to reduce the uncertainties involved. The study basin corresponds to a head basin of Segura River Basin, located in the South East of Spain. The impacts on runoff and its trend from observational dataset and climate projections, were assessed. Considering the control period 1961-1990, plausible significant decreases in runoff for the time period 2021-2050, were identified.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/15899975','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/15899975"><span>Human-modified temperatures induce species changes: Joint attribution.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Root, Terry L; MacMynowski, Dena P; Mastrandrea, Michael D; Schneider, Stephen H</p> <p>2005-05-24</p> <p>Average global surface-air temperature is increasing. Contention exists over relative contributions by natural and anthropogenic forcings. Ecological studies attribute plant and animal changes to observed warming. Until now, temperature-species connections have not been statistically attributed directly to anthropogenic climatic change. Using modeled climatic variables and observed species data, which are independent of thermometer records and paleoclimatic proxies, we demonstrate statistically significant "joint attribution," a two-step linkage: human activities contribute significantly to temperature changes and human-changed temperatures are associated with discernible changes in plant and animal traits. Additionally, our analyses provide independent testing of grid-box-scale temperature projections from a general circulation model (HadCM3).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GMD....10.1209H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GMD....10.1209H"><span>The Met Office HadGEM3-ES chemistry-climate model: evaluation of stratospheric dynamics and its impact on ozone</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hardiman, Steven C.; Butchart, Neal; O'Connor, Fiona M.; Rumbold, Steven T.</p> <p>2017-03-01</p> <p>Free-running and nudged versions of a Met Office chemistry-climate model are evaluated and used to investigate the impact of dynamics versus transport and chemistry within the model on the simulated evolution of stratospheric ozone. Metrics of the dynamical processes relevant for simulating stratospheric ozone are calculated, and the free-running model is found to outperform the previous model version in 10 of the 14 metrics. In particular, large biases in stratospheric transport and tropical tropopause temperature, which existed in the previous model version, are substantially reduced, making the current model more suitable for the simulation of stratospheric ozone. The spatial structure of the ozone hole, the area of polar stratospheric clouds, and the increased ozone concentrations in the Northern Hemisphere winter stratosphere following sudden stratospheric warmings, were all found to be sensitive to the accuracy of the dynamics and were better simulated in the nudged model than in the free-running model. Whilst nudging can, in general, provide a useful tool for removing the influence of dynamical biases from the evolution of chemical fields, this study shows that issues can remain in the climatology of nudged models. Significant biases in stratospheric vertical velocities, age of air, water vapour, and total column ozone still exist in the Met Office nudged model. Further, these can lead to biases in the downward flux of ozone into the troposphere.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27386089','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27386089"><span>Weighing the relative potential impacts of climate change and land-use change on an endangered bird.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bancroft, Betsy A; Lawler, Joshua J; Schumaker, Nathan H</p> <p>2016-07-01</p> <p>Climate change and land-use change are projected to be the two greatest drivers of biodiversity loss over the coming century. Land-use change has resulted in extensive habitat loss for many species. Likewise, climate change has affected many species resulting in range shifts, changes in phenology, and altered interactions. We used a spatially explicit, individual-based model to explore the effects of land-use change and climate change on a population of the endangered Red-cockaded Woodpecker (RCW; Picoides borealis). We modeled the effects of land-use change using multiple scenarios representing different spatial arrangements of new training areas for troops across Fort Benning. We used projected climate-driven changes in habitat and changes in reproductive output to explore the potential effects of climate change. We summarized potential changes in habitat based on the output of the dynamic vegetation model LPJ-GUESS, run for multiple climate change scenarios through the year 2100. We projected potential changes in reproduction based on an empirical relationship between spring precipitation and the mean number of successful fledglings produced per nest attempt. As modeled in our study, climate change had virtually no effect on the RCW population. Conversely, simulated effects of land-use change resulted in the loss of up to 28 breeding pairs by 2100. However, the simulated impacts of development depended on where the development occurred and could be completely avoided if the new training areas were placed in poor-quality habitat. Our results demonstrate the flexibility inherent in many systems that allows seemingly incompatible human land uses, such as development, and conservation actions to exist side by side.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70036730','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70036730"><span>Are there pre-Quaternary geological analogues for a future greenhouse warming?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Haywood, A.M.; Ridgwell, A.; Lunt, D.J.; Hill, D.J.; Pound, M.J.; Dowsett, H.J.; Dolan, A.M.; Francis, J.E.; Williams, M.</p> <p>2011-01-01</p> <p>Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race's current grand climate experiment. This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean-atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene-Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO2 forcing-whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate-or the sensitivity of the climate system itself to CO2 was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO2) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO2 concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO2 thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate. ?? 2011 The Royal Society.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21282155','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21282155"><span>Are there pre-Quaternary geological analogues for a future greenhouse warming?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Haywood, Alan M; Ridgwell, Andy; Lunt, Daniel J; Hill, Daniel J; Pound, Matthew J; Dowsett, Harry J; Dolan, Aisling M; Francis, Jane E; Williams, Mark</p> <p>2011-03-13</p> <p>Given the inherent uncertainties in predicting how climate and environments will respond to anthropogenic emissions of greenhouse gases, it would be beneficial to society if science could identify geological analogues to the human race's current grand climate experiment. This has been a focus of the geological and palaeoclimate communities over the last 30 years, with many scientific papers claiming that intervals in Earth history can be used as an analogue for future climate change. Using a coupled ocean-atmosphere modelling approach, we test this assertion for the most probable pre-Quaternary candidates of the last 100 million years: the Mid- and Late Cretaceous, the Palaeocene-Eocene Thermal Maximum (PETM), the Early Eocene, as well as warm intervals within the Miocene and Pliocene epochs. These intervals fail as true direct analogues since they either represent equilibrium climate states to a long-term CO(2) forcing--whereas anthropogenic emissions of greenhouse gases provide a progressive (transient) forcing on climate--or the sensitivity of the climate system itself to CO(2) was different. While no close geological analogue exists, past warm intervals in Earth history provide a unique opportunity to investigate processes that operated during warm (high CO(2)) climate states. Palaeoclimate and environmental reconstruction/modelling are facilitating the assessment and calculation of the response of global temperatures to increasing CO(2) concentrations in the longer term (multiple centuries); this is now referred to as the Earth System Sensitivity, which is critical in identifying CO(2) thresholds in the atmosphere that must not be crossed to avoid dangerous levels of climate change in the long term. Palaeoclimatology also provides a unique and independent way to evaluate the qualities of climate and Earth system models used to predict future climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.3240T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.3240T"><span>Potential ecological and economic consequences of climate-driven agricultural and silvicultural transformations in central Siberia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tchebakova, Nadezhda M.; Zander, Evgeniya V.; Pyzhev, Anton I.; Parfenova, Elena I.; Soja, Amber J.</p> <p>2014-05-01</p> <p>Increased warming predicted from general circulation models (GCMs) by the end of the century is expected to dramatically impact Siberian forests. Both natural climate-change-caused disturbance (weather, wildfire, infestation) and anthropogenic disturbance (legal/illegal logging) has increased, and their impact on Siberian boreal forest has been mounting over the last three decades. The Siberian BioClimatic Model (SiBCliM) was used to simulate Siberian forests, and the resultant maps show a severely decreased forest that has shifted northwards and a changed composition. Predicted dryer climates would enhance the risks of high fire danger and thawing permafrost, both of which challenge contemporary ecosystems. Our current goal is to evaluate the ecological and economic consequences of climate warming, to optimise economic loss/gain effects in forestry versus agriculture, to question the relative economic value of supporting forestry, agriculture or a mixed agro-forestry at the southern forest border in central Siberia predicted to undergo the most noticeable landcover and landuse changes. We developed and used forest and agricultural bioclimatic models to predict forest shifts; novel tree species and their climatypes are introduced in a warmer climate and/or potential novel agriculture are introduced with a potential variety of crops by the end of the century. We applied two strategies to estimate climate change effects, motivated by forest disturbance. One is a genetic means of assisting trees and forests to be harmonized with a changing climate by developing management strategies for seed transfer to locations that are best ecologically suited to the genotypes in future climates. The second strategy is the establishment of agricultural lands in new forest-steppe and steppe habitats, because the forests would retreat northwards. Currently, food, forage, and biofuel crops primarily reside in the steppe and forest-steppe zones which are known to have favorable climatic and soil resources. During this century, traditional Siberian crops are predicted to gradually shift northwards and new crops, which are currently non-existent but potentially important in a warmer climate, could be introduced in the extreme south. In a future warmer climate, the economic effect of climate change impacts on agriculture was estimated based on a production function approach and the Ricardian model. The production function estimated climate impacts of temperature, precipitation and carbon dioxide levels. The Ricardian model examined climate impacts on the net rent or value of farmland at various regions. The models produced the optimal distribution of agricultural lands between crop, livestock, and forestry sectors to compensate economic losses in forestry in potential landuse areas depending on climatic change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA51B..05K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA51B..05K"><span>Working with South Florida County Planners to Understand and Mitigate Uncertain Climate Risks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Knopman, D.; Groves, D. G.; Berg, N.</p> <p>2017-12-01</p> <p>This talk describes a novel approach for evaluating climate change vulnerabilities and adaptations in Southeast Florida to support long-term resilience planning. The work is unique in that it combines state-of-the-art hydrologic modeling with the region's long-term land use and transportation plans to better assess the future climate vulnerability and adaptations for the region. Addressing uncertainty in future projections is handled through the use of decisionmaking under deep uncertainty methods. Study findings, including analysis of key tradeoffs, were conveyed to the region's stakeholders through an innovative web-based decision support tool. This project leverages existing groundwater models spanning Miami-Dade and Broward Counties developed by the USGS, along with projections of land use and asset valuations for Miami-Dade and Broward County planning agencies. Model simulations are executed on virtual cloud-based servers for a highly scalable and parallelized platform. Groundwater elevations and the saltwater-freshwater interface and intrusion zones from the integrated modeling framework are analyzed under a wide range of long-term climate futures, including projected sea level rise and precipitation changes. The hydrologic hazards are then combined with current and future land use and asset valuation projections to estimate assets at risk across the range of futures. Lastly, an interactive decision support tool highlights the areas with critical climate vulnerabilities; distinguishes between vulnerability due to new development, increased climate hazards, or both; and provides guidance for adaptive management and development practices and decisionmaking in Southeast Florida.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC43E..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC43E..06T"><span>Building a Framework in Improving Drought Monitoring and Early Warning Systems in Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tadesse, T.; Wall, N.; Haigh, T.; Shiferaw, A. S.; Beyene, S.; Demisse, G. B.; Zaitchik, B.</p> <p>2015-12-01</p> <p>Decision makers need a basic understanding of the prediction models and products of hydro-climatic extremes and their suitability in time and space for strategic resource and development planning to develop mitigation and adaptation strategies. Advances in our ability to assess and predict climate extremes (e.g., droughts and floods) under evolving climate change suggest opportunity to improve management of climatic/hydrologic risk in agriculture and water resources. In the NASA funded project entitled, "Seasonal Prediction of Hydro-Climatic Extremes in the Greater Horn of Africa (GHA) under Evolving Climate Conditions to Support Adaptation Strategies," we are attempting to develop a framework that uses dialogue between managers and scientists on how to enhance the use of models' outputs and prediction products in the GHA as well as improve the delivery of this information in ways that can be easily utilized by managers. This process is expected to help our multidisciplinary research team obtain feedback on the models and forecast products. In addition, engaging decision makers is essential in evaluating the use of drought and flood prediction models and products for decision-making processes in drought and flood management. Through this study, we plan to assess information requirements to implement a robust Early Warning Systems (EWS) by engaging decision makers in the process. This participatory process could also help the existing EWSs in Africa and to develop new local and regional EWSs. In this presentation, we report the progress made in the past two years of the NASA project.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPA33D..06K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPA33D..06K"><span>Designing the Bridge: Perceptions and Use of Downscaled Climate Data by Climate Modelers and Resource Managers in Hawaii</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Keener, V. W.; Brewington, L.; Jaspers, K.</p> <p>2016-12-01</p> <p>To build an effective bridge from the climate modeling community to natural resource managers, we assessed the existing landscape to see where different groups diverge in their perceptions of climate data and needs. An understanding of a given community's shared knowledge and differences can help design more actionable science. Resource managers in Hawaii are eager to have future climate projections at spatial scales relevant to the islands. National initiatives to downscale climate data often exclude US insular regions, so researchers in Hawaii have generated regional dynamically and statistically downscaled projections. Projections of precipitation diverge, however, leading to difficulties in communication and use. Recently, a two day workshop was held with scientists and managers to evaluate available models and determine a set of best practices for moving forward with decision-relevant downscaling in Hawaii. To seed the discussion, the Pacific Regional Integrated Sciences and Assessments (RISA) program conducted a pre-workshop survey (N=65) of climate modelers and freshwater, ecosystem, and wildfire managers working in Hawaii. Scientists reported spending less than half of their time on operational research, although the majority was eager to partner with managers on specific projects. Resource managers had varying levels of familiarity with downscaled climate projections, but reported needing more information about uncertainty for decision making, and were less interested in the technical model details. There were large differences between groups of managers, with 41.7% of freshwater managers reporting that they used climate projections regularly, while a majority of ecosystem and wildfire managers reported having "no familiarity". Scientists and managers rated which spatial and temporal scales were most relevant to decision making. Finally, when asked to compare how confident they were in projections of specific climate variables between the dynamical and statistical data, 80-90% of managers responded that they had no opinion. Workshop attendees were very interested in the survey results, adding to evidence of a need for sustained engagement between modeler and user groups, as well as different strategies for working with different types of resource managers.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3991569','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3991569"><span>Effect of Climate Change on Soil Temperature in Swedish Boreal Forests</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jungqvist, Gunnar; Oni, Stephen K.; Teutschbein, Claudia; Futter, Martyn N.</p> <p>2014-01-01</p> <p>Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions. PMID:24747938</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24747938','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24747938"><span>Effect of climate change on soil temperature in Swedish boreal forests.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jungqvist, Gunnar; Oni, Stephen K; Teutschbein, Claudia; Futter, Martyn N</p> <p>2014-01-01</p> <p>Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15..544H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15..544H"><span>Path Dependence of Regional Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Herrington, Tyler; Zickfeld, Kirsten</p> <p>2013-04-01</p> <p>Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25015069','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25015069"><span>Humidity-regulated dormancy onset in the Fabaceae: a conceptual model and its ecological implications for the Australian wattle Acacia saligna.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tozer, Mark G; Ooi, Mark K J</p> <p>2014-09-01</p> <p>Seed dormancy enhances fitness by preventing seeds from germinating when the probability of seedling survival and recruitment is low. The onset of physical dormancy is sensitive to humidity during ripening; however, the implications of this mechanism for seed bank dynamics have not been quantified. This study proposes a model that describes how humidity-regulated dormancy onset may control the accumulation of a dormant seed bank, and seed experiments are conducted to calibrate the model for an Australian Fabaceae, Acacia saligna. The model is used to investigate the impact of climate on seed dormancy and to forecast the ecological implications of human-induced climate change. The relationship between relative humidity and dormancy onset was quantified under laboratory conditions by exposing freshly matured non-dormant seeds to constant humidity levels for fixed durations. The model was field-calibrated by measuring the response of seeds exposed to naturally fluctuating humidity. The model was applied to 3-hourly records of humidity spanning the period 1972-2007 in order to estimate both temporal variability in dormancy and spatial variability attributable to climatic differences among populations. Climate change models were used to project future changes in dormancy onset. A sigmoidal relationship exists between dormancy and humidity under both laboratory and field conditions. Seeds ripened under field conditions became dormant following very short exposure to low humidity (<20 %). Prolonged exposure at higher humidity did not increase dormancy significantly. It is predicted that populations growing in a temperate climate produce 33-55 % fewer dormant seeds than those in a Mediterranean climate; however, dormancy in temperate populations is predicted to increase as a result of climate change. Humidity-regulated dormancy onset may explain observed variation in physical dormancy. The model offers a systematic approach to modelling this variation in population studies. Forecast changes in climate have the potential to alter the seed bank dynamics of species with physical dormancy regulated by this mechanism, with implications for their capacity to delay germination and exploit windows for recruitment. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4204671','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4204671"><span>Humidity-regulated dormancy onset in the Fabaceae: a conceptual model and its ecological implications for the Australian wattle Acacia saligna</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Tozer, Mark G.; Ooi, Mark K. J.</p> <p>2014-01-01</p> <p>Background and aims Seed dormancy enhances fitness by preventing seeds from germinating when the probability of seedling survival and recruitment is low. The onset of physical dormancy is sensitive to humidity during ripening; however, the implications of this mechanism for seed bank dynamics have not been quantified. This study proposes a model that describes how humidity-regulated dormancy onset may control the accumulation of a dormant seed bank, and seed experiments are conducted to calibrate the model for an Australian Fabaceae, Acacia saligna. The model is used to investigate the impact of climate on seed dormancy and to forecast the ecological implications of human-induced climate change. Methods The relationship between relative humidity and dormancy onset was quantified under laboratory conditions by exposing freshly matured non-dormant seeds to constant humidity levels for fixed durations. The model was field-calibrated by measuring the response of seeds exposed to naturally fluctuating humidity. The model was applied to 3-hourly records of humidity spanning the period 1972–2007 in order to estimate both temporal variability in dormancy and spatial variability attributable to climatic differences among populations. Climate change models were used to project future changes in dormancy onset. Key Results A sigmoidal relationship exists between dormancy and humidity under both laboratory and field conditions. Seeds ripened under field conditions became dormant following very short exposure to low humidity (<20 %). Prolonged exposure at higher humidity did not increase dormancy significantly. It is predicted that populations growing in a temperate climate produce 33–55 % fewer dormant seeds than those in a Mediterranean climate; however, dormancy in temperate populations is predicted to increase as a result of climate change. Conclusions Humidity-regulated dormancy onset may explain observed variation in physical dormancy. The model offers a systematic approach to modelling this variation in population studies. Forecast changes in climate have the potential to alter the seed bank dynamics of species with physical dormancy regulated by this mechanism, with implications for their capacity to delay germination and exploit windows for recruitment. PMID:25015069</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ERL....11l3001S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ERL....11l3001S"><span>A network-based approach for semi-quantitative knowledge mining and its application to yield variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph</p> <p>2016-12-01</p> <p>Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.C21E1162L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.C21E1162L"><span>Exploring changes in vertical ice extent along the margin of the East Antarctic Ice Sheet in western Dronning Maud Land - initial results of the MAGIC-DML collaboration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lifton, N. A.; Newall, J. C.; Fredin, O.; Glasser, N. F.; Fabel, D.; Rogozhina, I.; Bernales, J.; Prange, M.; Sams, S.; Eisen, O.; Hättestrand, C.; Harbor, J.; Stroeven, A. P.</p> <p>2017-12-01</p> <p>Numerical ice sheet models constrained by theory and refined by comparisons with observational data are a central component of work to address the interactions between the cryosphere and changing climate, at a wide range of scales. Such models are tested and refined by comparing model predictions of past ice geometries with field-based reconstructions from geological, geomorphological, and ice core data. However, on the East Antarctic Ice sheet, there are few empirical data with which to reconstruct changes in ice sheet geometry in the Dronning Maud Land (DML) region. In addition, there is poor control on the regional climate history of the ice sheet margin, because ice core locations, where detailed reconstructions of climate history exist, are located on high inland domes. This leaves numerical models of regional glaciation history in this near-coastal area largely unconstrained. MAGIC-DML is an ongoing Swedish-US-Norwegian-German-UK collaboration with a focus on improving ice sheet models by combining advances in numerical modeling with filling critical data gaps that exist in our knowledge of the timing and pattern of ice surface changes on the western Dronning Maud Land margin. A combination of geomorphological mapping using remote sensing data, field investigations, cosmogenic nuclide surface exposure dating, and numerical ice-sheet modeling are being used in an iterative manner to produce a comprehensive reconstruction of the glacial history of western Dronning Maud Land. We will present an overview of the project, as well as field observations and preliminary in situ cosmogenic nuclide measurements from the 2016/17 expedition.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011942','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011942"><span>Cloud Macroscopic Organization: Order Emerging from Randomness</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yuan, Tianle</p> <p>2011-01-01</p> <p>Clouds play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of clouds in climate models is a major challenge because cloud processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in cloud size distribution of low-level clouds, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of clouds emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex cloud-clear field thus has its root in random local interactions. Studying cloud organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of cloud statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing clouds in our climate models when working in tandem.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910677M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910677M"><span>Soil mapping and processes models to support climate change mitigation and adaptation strategies: a review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Muñoz-Rojas, Miriam; Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Jordan, Antonio</p> <p>2017-04-01</p> <p>As agreed in Paris in December 2015, global average temperature is to be limited to "well below 2 °C above pre-industrial levels" and efforts will be made to "limit the temperature increase to 1.5 °C above pre-industrial levels. Thus, reducing greenhouse gas emissions (GHG) in all sectors becomes critical and appropriate sustainable land management practices need to be taken (Pereira et al., 2017). Mitigation strategies focus on reducing the rate and magnitude of climate change by reducing its causes. Complementary to mitigation, adaptation strategies aim to minimise impacts and maximize the benefits of new opportunities. The adoption of both practices will require developing system models to integrate and extrapolate anticipated climate changes such as global climate models (GCMs) and regional climate models (RCMs). Furthermore, integrating climate models driven by socio-economic scenarios in soil process models has allowed the investigation of potential changes and threats in soil characteristics and functions in future climate scenarios. One of the options with largest potential for climate change mitigation is sequestering carbon in soils. Therefore, the development of new methods and the use of existing tools for soil carbon monitoring and accounting have therefore become critical in a global change context. For example, soil C maps can help identify potential areas where management practices that promote C sequestration will be productive and guide the formulation of policies for climate change mitigation and adaptation strategies. Despite extensive efforts to compile soil information and map soil C, many uncertainties remain in the determination of soil C stocks, and the reliability of these estimates depends upon the quality and resolution of the spatial datasets used for its calculation. Thus, better estimates of soil C pools and dynamics are needed to advance understanding of the C balance and the potential of soils for climate change mitigation. Here, we discuss the most recent advances on the application of soil mapping and modeling to support climate change mitigation and adaptation strategies; and These strategies are a key component of the implementation of sustainable land management policies need to be integrated are critical to. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. Muñoz-Rojas, M., Pereira, P., Brevic, E., Cerda, A., Jordan, A. (2017) Soil mapping and processes models for sustainable land management applied to modern challenges. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013JHyd..480...85F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013JHyd..480...85F"><span>Modeling impacts of climate change on freshwater availability in Africa</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Faramarzi, Monireh; Abbaspour, Karim C.; Ashraf Vaghefi, Saeid; Farzaneh, Mohammad Reza; Zehnder, Alexander J. B.; Srinivasan, Raghavan; Yang, Hong</p> <p>2013-02-01</p> <p>SummaryThis study analyzes the impact of climate change on freshwater availability in Africa at the subbasin level for the period of 2020-2040. Future climate projections from five global circulation models (GCMs) under the four IPCC emission scenarios were fed into an existing SWAT hydrological model to project the impact on different components of water resources across the African continent. The GCMs have been downscaled based on observed data of Climate Research Unit to represent local climate conditions at 0.5° grid spatial resolution. The results show that for Africa as a whole, the mean total quantity of water resources is likely to increase. For individual subbasins and countries, variations are substantial. Although uncertainties are high in the simulated results, we found that in many regions/countries, most of the climate scenarios projected the same direction of changes in water resources, suggesting a relatively high confidence in the projections. The assessment of the number of dry days and the frequency of their occurrences suggests an increase in the drought events and their duration in the future. Overall, the dry regions have higher uncertainties than the wet regions in the projected impacts on water resources. This poses additional challenge to the agriculture in dry regions where water shortage is already severe while irrigation is expected to become more important to stabilize and increase food production.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12g4025B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12g4025B"><span>Future summer mega-heatwave and record-breaking temperatures in a warmer France climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bador, Margot; Terray, Laurent; Boé, Julien; Somot, Samuel; Alias, Antoinette; Gibelin, Anne-Laure; Dubuisson, Brigitte</p> <p>2017-07-01</p> <p>This study focuses on future very hot summers associated with severe heatwaves and record-breaking temperatures in France. Daily temperature observations and a pair of historical and scenario (greenhouse gas radiative concentration pathway 8.5) simulations with the high-resolution (∼12.5 km) ALADIN regional climate model provide a robust framework to examine the spatial distribution of these extreme events and their 21st century evolution. Five regions are identified with an extreme event spatial clustering algorithm applied to observed temperatures. They are used to diagnose the 21st century heatwave spatial patterns. In the 2070s, we find a simulated mega-heatwave as severe as the 2003 observed heatwave relative to its contemporaneous climate. A 20-member initial condition ensemble is used to assess the sensitivity of this future heatwave to the internal variability in the regional climate model and to pre-existing land surface conditions. Even in a much warmer and drier climate in France, late spring dry land conditions may lead to a significant amplification of summer extreme temperatures and heatwave intensity through limitations in evapotranspiration. By 2100, the increase in summer temperature maxima exhibits a range from 6 °C to almost 13 °C in the five regions in France, relative to historical maxima. These projections are comparable with the estimates given by a large number of global climate models.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRD..11719113D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRD..11719113D"><span>Reconstructing the 20th century high-resolution climate of the southeastern United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dinapoli, Steven M.; Misra, Vasubandhu</p> <p>2012-10-01</p> <p>We dynamically downscale the 20th Century Reanalysis (20CR) to a 10-km grid resolution from 1901 to 2008 over the southeastern United States and the Gulf of Mexico using the Regional Spectral Model. The downscaled data set, which we call theFlorida Climate Institute-Florida State University Land-Atmosphere Reanalysis for theSoutheastern United States at 10-km resolution (FLAReS1.0), will facilitate the study of the effects of low-frequency climate variability and major historical climate events on local hydrology and agriculture. To determine the suitability of the FLAReS1.0 downscaled data set for any subsequent applied climate studies, we compare the annual, seasonal, and diurnal variability of temperature and precipitation in the model to various observation data sets. In addition, we examine the model's depiction of several meteorological phenomena that affect the climate of the region, including extreme cold waves, summer sea breezes and associated convective activity, tropical cyclone landfalls, and midlatitude frontal systems. Our results show that temperature and precipitation variability are well-represented by FLAReS1.0 on most time scales, although systematic biases do exist in the data. FLAReS1.0 accurately portrays some of the major weather phenomena in the region, but the severity of extreme weather events is generally underestimated. The high resolution of FLAReS1.0 makes it more suitable for local climate studies than the coarser 20CR.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMEP51E..08P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMEP51E..08P"><span>Global hotspots of river erosion under global warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Plink-Bjorklund, P.; Reichler, T.</p> <p>2017-12-01</p> <p>Extreme precipitation plays a significant role for river hydrology, flood hazards and landscape response. For example, the September 2013 rainstorm in the Colorado Front Range evacuated the equivalent of hundreds to thousands of years of hillslope weathering products. Although promoted by steep topography, the Colorado event is clearly linked to rainfall intensity, since most of the 1100 debris flows occurred within the highest rainfall contour. Additional evidence for a strong link between extreme precipitation and river erosion comes from the sedimentary record, and especially from that of past greenhouse climates. The existence of such a link suggests that information about global rainfall patterns can be used to define regions of increased erosion potential. However, the question arises what rainfall criteria to use and how well the method works. A related question is how ongoing climate change and the corresponding shifts in rainfall might impact the results. Here, we use atmospheric reanalysis and output from a climate model to identify regions that are particularly susceptible to landscape change in response to extreme precipitation. In order to define the regions, we combine several hydroclimatological and geomorphological criteria into a single index of erosion potential. We show that for current climate, our criteria applied to atmospheric reanalysis or to climate model data successfully localize known areas of increased erosion potential, such as the Colorado region. We then apply our criteria to climate model data for future climate to document how the location, extent, and intensity of erosion hotspots are likely to change under global warming.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMED24A..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMED24A..04D"><span>Climate Change Professional Development Approaches: Design Considerations, Teacher Enactment, and Student Learning</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Drewes, A.; Henderson, J.; Mouza, C.</p> <p>2017-12-01</p> <p>Climate change is one of the most pressing challenges facing society, and climate change educational models are emerging in response. This study investigates the implementation and enactment of a climate change professional development model for science educators and its impact on student learning. Using an intrinsic case study methodology, we focused analytic attention on how one teacher made specific curricular, pedagogical, and content decisions, and the implications of those decisions for student's conceptual learning.The research presented here reports on the instructional design, pedagogical enactment, and subsequent effects on student learning of a climate change professional development (PD) model in the United States. Using anthropological theories of conceptual travel, we traced salient ideas from the PD through instructional delivery and into the evidence of student reasoning. We sought to address the following research questions: 1) How did a middle school teacher integrate climate change concepts into her science curriculum following PD participation? and 2) How did climate change instruction influence student understanding of key climate change constructs?From observation of the classroom instruction, we determined that the teacher effectively integrated new climate change information into her pre-existing schema. Additionally, through retrospective analysis of the PD, we found the design of the PD foregrounded the causes, mechanisms and likely effects of anthropogenic climate change at the expense of mitigation and adaptation strategies, and this differentially shaped how climate change was taught in the teacher's classroom. Analysis of student reasoning evidence showed that students gained an increased understanding of the enhanced greenhouse effect and the implications of human activity on this enhanced effect at statistically significant levels and with moderate effect sizes. However, students demonstrated a limited, though non-significant gain on the likely effects of climate change. Student reasoning on the tangible actions to deal with these problems also remained underdeveloped, reflecting omissions in both professional development and teacher enactment. We discuss implications and considerations for the emerging field of climate change education.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/381000-climatic-impact-amazon-deforestation-mechanistic-model-study','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/381000-climatic-impact-amazon-deforestation-mechanistic-model-study"><span>Climatic impact of Amazon deforestation - a mechanistic model study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ning Zeng; Dickinson, R.E.; Xubin Zeng</p> <p>1996-04-01</p> <p>Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A33E0266D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A33E0266D"><span>The impacts of land use, radiative forcing, and biological changes on regional climate in Japan</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dairaku, K.; Pielke, R. A., Sr.</p> <p>2013-12-01</p> <p>Because regional responses of surface hydrological and biogeochemical changes are particularly complex, it is necessary to develop assessment tools for regional scale adaptation to climate. We developed a dynamical downscaling method using the regional climate model (NIED-RAMS) over Japan. The NIED-RAMS model includes a plant model that considers biological processes, the General Energy and Mass Transfer Model (GEMTM) which adds spatial resolution to accurately assess critical interactions within the regional climate system for vulnerability assessments to climate change. We digitalized a potential vegetation map that formerly existed only on paper into Geographic Information System data. It quantified information on the reduction of green spaces and the expansion of urban and agricultural areas in Japan. We conducted regional climate sensitivity experiments of land use and land cover (LULC) change, radiative forcing, and biological effects by using the NIED-RAMS with horizontal grid spacing of 20 km. We investigated regional climate responses in Japan for three experimental scenarios: 1. land use and land cover is changed from current to potential vegetation; 2. radiative forcing is changed from 1 x CO2 to 2 x CO2; and 3. biological CO2 partial pressures in plants are doubled. The experiments show good accuracy in reproducing the surface air temperature and precipitation. The experiments indicate the distinct change of hydrological cycles in various aspects due to anthropogenic LULC change, radiative forcing, and biological effects. The relative impacts of those changes are discussed and compared. Acknowledgments This study was conducted as part of the research subject "Vulnerability and Adaptation to Climate Change in Water Hazard Assessed Using Regional Climate Scenarios in the Tokyo Region' (National Research Institute for Earth Science and Disaster Prevention; PI: Koji Dairaku) of Research Program on Climate Change Adaptation (RECCA), and was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1422299-arm-cloud-radar-simulator-global-climate-models-bridging-field-data-climate-models','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1422299-arm-cloud-radar-simulator-global-climate-models-bridging-field-data-climate-models"><span>The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Zhang, Yuying; Xie, Shaocheng; Klein, Stephen A.</p> <p></p> <p>Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the conceptmore » of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are difficult for the CloudSat radar to detect due to surface contamination (Mace et al. 2007; Marchand et al. 2008). Therefore, the ARM ground-based cloud observations can provide important observations of clouds that complement measurements from space.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1514093W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1514093W"><span>Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van</p> <p>2013-04-01</p> <p>Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1811761O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1811761O"><span>A simple integrated assessment approach to global change simulation and evaluation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ogutu, Keroboto; D'Andrea, Fabio; Ghil, Michael</p> <p>2016-04-01</p> <p>We formulate and study the Coupled Climate-Economy-Biosphere (CoCEB) model, which constitutes the basis of our idealized integrated assessment approach to simulating and evaluating global change. CoCEB is composed of a physical climate module, based on Earth's energy balance, and an economy module that uses endogenous economic growth with physical and human capital accumulation. A biosphere model is likewise under study and will be coupled to the existing two modules. We concentrate on the interactions between the two subsystems: the effect of climate on the economy, via damage functions, and the effect of the economy on climate, via a control of the greenhouse gas emissions. Simple functional forms of the relation between the two subsystems permit simple interpretations of the coupled effects. The CoCEB model is used to make hypotheses on the long-term effect of investment in emission abatement, and on the comparative efficacy of different approaches to abatement, in particular by investing in low carbon technology, in deforestation reduction or in carbon capture and storage (CCS). The CoCEB model is very flexible and transparent, and it allows one to easily formulate and compare different functional representations of climate change mitigation policies. Using different mitigation measures and their cost estimates, as found in the literature, one is able to compare these measures in a coherent way.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3589428','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3589428"><span>Effects of Climate Change on Range Forage Production in the San Francisco Bay Area</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Chaplin-Kramer, Rebecca; George, Melvin R.</p> <p>2013-01-01</p> <p>The San Francisco Bay Area in California, USA is a highly heterogeneous region in climate, topography, and habitats, as well as in its political and economic interests. Successful conservation strategies must consider various current and future competing demands for the land, and should pay special attention to livestock grazing, the dominant non-urban land-use. The main objective of this study was to predict changes in rangeland forage production in response to changes in temperature and precipitation projected by downscaled output from global climate models. Daily temperature and precipitation data generated by four climate models were used as input variables for an existing rangeland forage production model (linear regression) for California’s annual rangelands and projected on 244 12 km x 12 km grid cells for eight Bay Area counties. Climate model projections suggest that forage production in Bay Area rangelands may be enhanced by future conditions in most years, at least in terms of peak standing crop. However, the timing of production is as important as its peak, and altered precipitation patterns could mean delayed germination, resulting in shorter growing seasons and longer periods of inadequate forage quality. An increase in the frequency of extremely dry years also increases the uncertainty of forage availability. These shifts in forage production will affect the economic viability and conservation strategies for rangelands in the San Francisco Bay Area. PMID:23472102</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015CliPD..11.2585S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015CliPD..11.2585S"><span>Gridded climate data from 5 GCMs of the Last Glacial Maximum downscaled to 30 arc s for Europe</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schmatz, D. R.; Luterbacher, J.; Zimmermann, N. E.; Pearman, P. B.</p> <p>2015-06-01</p> <p>Studies of the impacts of historical, current and future global change require very high-resolution climate data (≤ 1 km) as a basis for modelled responses, meaning that data from digital climate models generally require substantial rescaling. Another shortcoming of available datasets on past climate is that the effects of sea level rise and fall are not considered. Without such information, the study of glacial refugia or early Holocene plant and animal migration are incomplete if not impossible. Sea level at the last glacial maximum (LGM) was approximately 125 m lower, creating substantial additional terrestrial area for which no current baseline data exist. Here, we introduce the development of a novel, gridded climate dataset for LGM that is both very high resolution (1 km) and extends to the LGM sea and land mask. We developed two methods to extend current terrestrial precipitation and temperature data to areas between the current and LGM coastlines. The absolute interpolation error is less than 1 and 0.5 °C for 98.9 and 87.8 %, respectively, of all pixels within two arc degrees of the current coastline. We use the change factor method with these newly assembled baseline data to downscale five global circulation models of LGM climate to a resolution of 1 km for Europe. As additional variables we calculate 19 "bioclimatic" variables, which are often used in climate change impact studies on biological diversity. The new LGM climate maps are well suited for analysing refugia and migration during Holocene warming following the LGM.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN31A0067K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN31A0067K"><span>Modernizing Earth and Space Science Modeling Workflows in the Big Data Era</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kinter, J. L.; Feigelson, E.; Walker, R. J.; Tino, C.</p> <p>2017-12-01</p> <p>Modeling is a major aspect of the Earth and space science research. The development of numerical models of the Earth system, planetary systems or astrophysical systems is essential to linking theory with observations. Optimal use of observations that are quite expensive to obtain and maintain typically requires data assimilation that involves numerical models. In the Earth sciences, models of the physical climate system are typically used for data assimilation, climate projection, and inter-disciplinary research, spanning applications from analysis of multi-sensor data sets to decision-making in climate-sensitive sectors with applications to ecosystems, hazards, and various biogeochemical processes. In space physics, most models are from first principles, require considerable expertise to run and are frequently modified significantly for each case study. The volume and variety of model output data from modeling Earth and space systems are rapidly increasing and have reached a scale where human interaction with data is prohibitively inefficient. A major barrier to progress is that modeling workflows isn't deemed by practitioners to be a design problem. Existing workflows have been created by a slow accretion of software, typically based on undocumented, inflexible scripts haphazardly modified by a succession of scientists and students not trained in modern software engineering methods. As a result, existing modeling workflows suffer from an inability to onboard new datasets into models; an inability to keep pace with accelerating data production rates; and irreproducibility, among other problems. These factors are creating an untenable situation for those conducting and supporting Earth system and space science. Improving modeling workflows requires investments in hardware, software and human resources. This paper describes the critical path issues that must be targeted to accelerate modeling workflows, including script modularization, parallelization, and automation in the near term, and longer term investments in virtualized environments for improved scalability, tolerance for lossy data compression, novel data-centric memory and storage technologies, and tools for peer reviewing, preserving and sharing workflows, as well as fundamental statistical and machine learning algorithms.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/53848','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/53848"><span>A statistical approach to estimate O3 uptake of ponderosa pine in a mediterranean climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>N.E. Grulke; H.K. Preisler; C.C. Fan; W.A. Retzlaff</p> <p>2002-01-01</p> <p>In highly polluted sites, stomatal behavior is sluggish with respect to light, vapor pressure deficit, and internal CO2 concentration (Ci) and poorly described by existing models. Statistical models were developed to estimate stomatal conductance (gs) of 40-year-old ponderosa pine at three sites differing in pollutant exposure for the purpose of...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1992EOSTr..73..195H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1992EOSTr..73..195H"><span>Intercomparison of land-surface parameterizations launched</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Henderson-Sellers, A.; Dickinson, R. E.</p> <p></p> <p>One of the crucial tasks for climatic and hydrological scientists over the next several years will be validating land surface process parameterizations used in climate models. There is not, necessarily, a unique set of parameters to be used. Different scientists will want to attempt to capture processes through various methods “for example, Avissar and Verstraete, 1990”. Validation of some aspects of the available (and proposed) schemes' performance is clearly required. It would also be valuable to compare the behavior of the existing schemes [for example, Dickinson et al., 1991; Henderson-Sellers, 1992a].The WMO-CAS Working Group on Numerical Experimentation (WGNE) and the Science Panel of the GEWEX Continental-Scale International Project (GCIP) [for example, Chahine, 1992] have agreed to launch the joint WGNE/GCIP Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS). The principal goal of this project is to achieve greater understanding of the capabilities and potential applications of existing and new land-surface schemes in atmospheric models. It is not anticipated that a single “best” scheme will emerge. Rather, the aim is to explore alternative models in ways compatible with their authors' or exploiters' goals and to increase understanding of the characteristics of these models in the scientific community.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B43B0460M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B43B0460M"><span>Agricultural Management Practices Explain Variation in Global Yield Gaps of Major Crops</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mueller, N. D.; Gerber, J. S.; Ray, D. K.; Ramankutty, N.; Foley, J. A.</p> <p>2010-12-01</p> <p>The continued expansion and intensification of agriculture are key drivers of global environmental change. Meeting a doubling of food demand in the next half-century will further induce environmental change, requiring either large cropland expansion into carbon- and biodiversity-rich tropical forests or increasing yields on existing croplands. Closing the “yield gaps” between the most and least productive farmers on current agricultural lands is a necessary and major step towards preserving natural ecosystems and meeting future food demand. Here we use global climate, soils, and cropland datasets to quantify yield gaps for major crops using equal-area climate analogs. Consistent with previous studies, we find large yield gaps for many crops in Eastern Europe, tropical Africa, and parts of Mexico. To analyze the drivers of yield gaps, we collected sub-national agricultural management data and built a global dataset of fertilizer application rates for over 160 crops. We constructed empirical crop yield models for each climate analog using the global management information for 17 major crops. We find that our climate-specific models explain a substantial amount of the global variation in yields. These models could be widely applied to identify management changes needed to close yield gaps, analyze the environmental impacts of agricultural intensification, and identify climate change adaptation techniques.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC41H..02P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC41H..02P"><span>Making Scientific Data Available to Adaptation Practitioners - the Wallace Initiative</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Price, J. T.; Warren, R. F.; Vanderwal, J.; Shoo, L.; Ramirez, J.; Jarvis, A.; Goswami, S.</p> <p>2010-12-01</p> <p>Conservation strategies have largely been developed under an assumption of a stationary climate. These strategies may fail with changing climates, especially when acting with existing anthropogenic pressures. The Wallace Initiative is a global effort to rapidly assess the potential impacts of climate change on nearly 50,000 plant and animal species. Climate change data from the Community Integrated Assessment System (CIAS) is then used to look at different future climate change scenarios. Governments and conservation organizations have dedicated extensive resources to protect biodiversity. These investments are at risk and efforts will need to take into account a dynamic climate. We used the species models to calculate projected changes in percent species richness - looking at areas likely to be refugia and areas likely to undergo the greatest loss. This information can provide guidance to natural resource managers on how they may need to adapt to climate change to avoid biodiversity loss. Managers will also need to take into account issues with spatial scale. While these models might project a species being “lost” in a 0.5° x 0.5° grid, thermal buffering (e.g., taking into account elevation, slope, aspect, distance to stream and canopy cover) provides guidance on areas that may allow a species to persist at more local scales (1-5 km). This approach may help alleviate the issues of downscaling climate and climate change data in data-poor areas. Understanding the vulnerability of biodiversity requires an understanding of the climate and projected climate changes. Thus, developing long term adaptation options requires robust vulnerability analyses at appropriate scales. These assessments are often hindered by data quality and availability, capacity and an understanding of appropriate scales, methods and tools. The program ClimaScope has been designed to help provide better access to climate data for modelers and practitioners, data that has also been linked to impacts. ClimaScope is a data visualization engine providing easy access to data without running the models. For a selected GCM pattern and emissions scenario, ClimaScope provides maps, charts and data on the projected climate changes with some indication of uncertainty range. Variables available include terrestrial temperature change (maximum, minimum and average), total precipitation, wet-day frequency, and sea-surface temperature. This data can be presented both as observed climate and/or projected climate for a user defined time period. Some of these data have been used in the Wallace Initiative and data from the Wallace Initiative are also available to users. So, practitioners can select family, genus, species, dispersal model, climate model, emission model, and time slice and get maps showing projected range of the species over time. These tools have been designed to help make scientific data more readily available to adaptation practitioners around the world, especially in developing countries.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=334286','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=334286"><span>Short-term forecasting tools for agricultural nutrient management</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>The advent of real time/short term farm management tools is motivated by the need to protect water quality above and beyond the general guidance offered by existing nutrient management plans. Advances in high performance computing and hydrologic/climate modeling have enabled rapid dissemination of ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27009065','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27009065"><span>A climate-driven mechanistic population model of Aedes albopictus with diapause.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jia, Pengfei; Lu, Liang; Chen, Xiang; Chen, Jin; Guo, Li; Yu, Xiao; Liu, Qiyong</p> <p>2016-03-24</p> <p>The mosquito Aedes albopitus is a competent vector for the transmission of many blood-borne pathogens. An important factor that affects the mosquitoes' development and spreading is climate, such as temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of diapause and non-diapause periods, and considering the mortality rate of diapause eggs. Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes' life-cycle. monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for model validation. The simulation results by the proposed model is validated with entomological field data by the Pearson correlation coefficient r (2) in Guangzhou (r (2) = 0.84) and in Shanghai (r (2) = 0.90). In addition, by consolidating the effect of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant over the basic model. The model highlights the importance of considering diapause in simulating Ae. albopitus population. It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics and eventually facilitating the early warning and control of the diseases.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A21F0208O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A21F0208O"><span>Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Otto, C.; Schewe, J.; Frieler, K.</p> <p>2015-12-01</p> <p>Extreme climate events such as droughts, floods, or heat waves affect agricultural production in major cropping regions and therefore impact the world market prices of staple crops. In the last decade, crop prices exhibited two very prominent price peaks in 2007-2008 and 2010-2011, threatening food security especially for poorer countries that are net importers of grain. There is evidence that these spikes in grain prices were at least partly triggered by actual supply shortages and the expectation of bad harvests. However, the response of the market to supply shocks is nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and trade policies. Quantifying the contributions of such different factors to short-term price variability remains difficult, not least because many existing models ignore the role of storage which becomes important on short timescales. This in turn impedes the assessment of future climate change impacts on food prices. Here, we present a simple model of annual world grain prices that integrates grain stocks into the supply and demand functions. This firstly allows us to model explicitly the effect of storage strategies on world market price, and thus, for the first time, to quantify the potential contribution of trade policies to price variability in a simple global framework. Driven only by reported production and by long--term demand trends of the past ca. 40 years, the model reproduces observed variations in both the global storage volume and price of wheat. We demonstrate how recent price peaks can be reproduced by accounting for documented changes in storage strategies and trade policies, contrasting and complementing previous explanations based on different mechanisms such as speculation. Secondly, we show how the integration of storage allows long-term projections of grain price variability under climate change, based on existing crop yield scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5724262','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5724262"><span>Holocene fluctuations in human population demonstrate repeated links to food production and climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Colledge, Sue; Fuller, Dorian; Fyfe, Ralph; Shennan, Stephen; Stevens, Chris</p> <p>2017-01-01</p> <p>We consider the long-term relationship between human demography, food production, and Holocene climate via an archaeological radiocarbon date series of unprecedented sampling density and detail. There is striking consistency in the inferred human population dynamics across different regions of Britain and Ireland during the middle and later Holocene. Major cross-regional population downturns in population coincide with episodes of more abrupt change in North Atlantic climate and witness societal responses in food procurement as visible in directly dated plants and animals, often with moves toward hardier cereals, increased pastoralism, and/or gathered resources. For the Neolithic, this evidence questions existing models of wholly endogenous demographic boom–bust. For the wider Holocene, it demonstrates that climate-related disruptions have been quasi-periodic drivers of societal and subsistence change. PMID:29158411</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H11H1298K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H11H1298K"><span>Are implicit policy assumptions about climate adaptation trying to push drinking water utilities down an impossible path?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klasic, M. R.; Ekstrom, J.; Bedsworth, L. W.; Baker, Z.</p> <p>2017-12-01</p> <p>Extreme events such as wildfires, droughts, and flooding are projected to be more frequent and intense under a changing climate, increasing challenges to water quality management. To protect and improve public health, drinking water utility managers need to understand and plan for climate change and extreme events. This three year study began with the assumption that improved climate projections were key to advancing climate adaptation at the local level. Through a survey (N = 259) and interviews (N = 61) with California drinking water utility managers during the peak of the state's recent drought, we found that scientific information was not a key barrier hindering adaptation. Instead, we found that managers fell into three distinct mental models based on their interaction with, perceptions, and attitudes, towards scientific information and the future of water in their system. One of the mental models, "modeled futures", is a concept most in line with how climate change scientists talk about the use of information. Drinking water utilities falling into the "modeled future" category tend to be larger systems that have adequate capacity to both receive and use scientific information. Medium and smaller utilities in California, that more often serve rural low income communities, tend to fall into the other two mental models, "whose future" and "no future". We show evidence that there is an implicit presumption that all drinking water utility managers should strive to align with "modeled future" mental models. This presentation questions this assumption as it leaves behind many utilities that need to adapt to climate change (several thousand in California alone), but may not have the technical, financial, managerial, or other capacity to do so. It is clear that no single solution or pathway to drought resilience exists for water utilities, but we argue that a more explicit understanding and definition of what it means to be a resilient drinking water utility is necessary. By highlighting, then questioning, the assumption that all utility managers should strive to have "modeled future" mentalities, this presentation seeks to foster an open dialogue around which pathway or pathways are most feasible for supporting drinking water utility managers planning for climate change.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007JGRD..11213103L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007JGRD..11213103L"><span>Does the Danube exist? Versions of reality given by various regional climate models and climatological data sets</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lucarini, Valerio; Danihlik, Robert; Kriegerova, Ida; Speranza, Antonio</p> <p>2007-07-01</p> <p>We present an auditing (intercomparison and verification) of several regional climate models (RCMs) nested into the same run of the same atmospheric global circulation model (AGCM) regarding their representation of the statistical properties of the hydrological balance of the Danube river basin for 1961-1990. We also consider the data sets produced by the driving AGCM, by the European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalyses. The hydrological balance is computed by integrating the precipitation and evaporation fields over the area of interest. Large discrepancies exist among RCMs for the monthly climatology as well as for the mean and variability of the annual balances, and only few data sets are consistent with the observed discharge values of the Danube at its Delta, even if the driving AGCM provides itself an excellent estimate. We find consistently that, for a given model, increases in the resolution do not alter the net water balance, while speeding up the hydrological cycle through the enhancement of both precipitation and evaporation by the same amount. Since the considered approach relies on the mass conservation principle and bypasses the details of the air-land interface modeling, we propose that the atmospheric components of RCMs still face difficulties in representing the water balance even on a relatively large scale. Their reliability on smaller river basins may be even more problematic. Moreover, since for some models the hydrological balance estimates obtained with the runoff fields do not agree with those obtained via precipitation and evaporation, some deficiencies of the land models are also apparent. The driving AGCM greatly overperforms the NCEP-NCAR and ECMWF 40-year (ERA-40) reanalyses, which result to be largely inadequate for representing the hydrology of the Danube river basin, both for the reconstruction of the long-term averages and of the seasonal cycle. The reanalyses cannot in any sense be used as verification. We suggest that these results should be carefully considered in the perspective of auditing climate models and assessing their ability to simulate future climate changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1399D"><span>Nudging the Arctic Ocean to quantify Arctic sea ice feedbacks</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dekker, Evelien; Severijns, Camiel; Bintanja, Richard</p> <p>2017-04-01</p> <p>It is well-established that the Arctic is warming 2 to 3 time faster than rest of the planet. One of the great uncertainties in climate research is related to what extent sea ice feedbacks amplify this (seasonally varying) Arctic warming. Earlier studies have analyzed existing climate model output using correlations and energy budget considerations in order to quantify sea ice feedbacks through indirect methods. From these analyses it is regularly inferred that sea ice likely plays an important role, but details remain obscure. Here we will take a different and a more direct approach: we will keep the sea ice constant in a sensitivity simulation, using a state-of -the-art climate model (EC-Earth), applying a technique that has never been attempted before. This experimental technique involves nudging the temperature and salinity of the ocean surface (and possibly some layers below to maintain the vertical structure and mixing) to a predefined prescribed state. When strongly nudged to existing (seasonally-varying) sea surface temperatures, ocean salinity and temperature, we force the sea ice to remain in regions/seasons where it is located in the prescribed state, despite the changing climate. Once we obtain fixed' sea ice, we will run a future scenario, for instance 2 x CO2 with and without prescribed sea ice, with the difference between these runs providing a measure as to what extent sea ice contributes to Arctic warming, including the seasonal and geographical imprint of the effects.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMED14A..06T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMED14A..06T"><span>A Model for Collaborative Learning in Undergraduate Climate Change Courses</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Teranes, J. L.</p> <p>2008-12-01</p> <p>Like several colleges and universities across the nation, the University of California, San Diego, has introduced climate change topics into many existing and new undergraduate courses. I have administered a program in this area at UCSD and have also developed and taught a new lower-division UCSD course entitled "Climate Change and Society", a general education course for non-majors. This class covers the basics of climate change, such as the science that explains it, the causes of climate change, climate change impacts, and mitigation strategies. The teaching methods for this course stress interdisciplinary approaches. I find that inquiry-based and collaborative modes of learning are particularly effective when applied to science-based climate, environmental and sustainability topics. Undergraduate education is often dominated by a competitive and individualistic approach to learning. In this approach, individual success is frequently perceived as contingent on others being less successful. Such a model is at odds with commonly stated goals of teaching climate change and sustainability, which are to equip students to contribute to the debate on global environmental change and societal adaptation strategies; and to help students become better informed citizens and decision makers. I present classroom-tested strategies for developing collaborative forms of learning in climate change and environmental courses, including team projects, group presentations and group assessment exercises. I show how critical thinking skills and long-term retention of information can benefit in the collaborative mode of learning. I find that a collaborative learning model is especially appropriate to general education courses in which the enrolled student body represents a wide diversity of majors, class level and expertise. I also connect collaborative coursework in interdisciplinary environmental topics directly to applications in the field, where so much "real-world" achievement in research, education, government and business is effectively accomplished in collaborative teams.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC22A..01N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC22A..01N"><span>Evaluating the Impacts of Climate Change on the Operations and Future Development of the U.S. Electricity System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Newmark, R. L.; Cohen, S. M.; Averyt, K.; Macknick, J.; Meldrum, J.; Sullivan, P.</p> <p>2014-12-01</p> <p>Climate change has the potential to exacerbate reliability concerns for the power sector through changes in water availability and air temperatures. The power sector is responsible for 41% of U.S. freshwater withdrawals, primarily for power plant cooling needs, and any changes in the water available for the power sector, given increasing competition among water users, could affect decisions about new power plant builds and reliable operations for existing generators. Similarly, increases in air temperatures can reduce power plant efficiencies, which in turn increases fuel consumption as well as water withdrawal and consumption rates. This analysis describes an initial link between climate, water, and electricity systems using the National Renewable Energy Laboratory's (NREL) Regional Energy Deployment System (ReEDS) electricity system capacity expansion model. Average surface water runoff projections from Coupled Model Intercomparison Project 5 (CMIP5) data are applied to surface water available to generating capacity in ReEDS, and electric sector growth is compared with and without climate-influenced water availability for the 134 electricity balancing regions in the ReEDS model. In addition, air temperature changes are considered for their impacts on electricity load, transmission capacity, and power plant efficiencies and water use rates. Mean climate projections have only a small impact on national or regional capacity growth and water use because most regions have sufficient unappropriated or previously retired water access to offset climate impacts. Climate impacts are notable in southwestern states, which experience reduced water access purchases and a greater share of water acquired from wastewater and other higher-cost water resources. The electric sector climate impacts demonstrated herein establish a methodology to be later exercised with more extreme climate scenarios and a more rigorous representation of legal and physical water availability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5873842','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5873842"><span>A climate-associated multispecies cryptic cline in the northwest Atlantic</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>DiBacco, Claudio; Lowen, Ben; Beiko, Robert G.; Bentzen, Paul; Brickman, David; Johnson, Catherine; Wang, Zeliang; Wringe, Brendan F.; Bradbury, Ian R.</p> <p>2018-01-01</p> <p>The spatial genetic structure of most species in the open marine environment remains largely unresolved. This information gap creates uncertainty in the sustainable management, recovery, and associated resilience of marine communities and our capacity to extrapolate beyond the few species for which such information exists. We document a previously unidentified multispecies biogeographic break aligned with a steep climatic gradient and driven by seasonal temperature minima in the northwest Atlantic. The coherence of this genetic break across our five study species with contrasting life histories suggests a pervasive macroecological phenomenon. The integration of this genetic structure with habitat suitability models and climate forecasts predicts significant variation in northward distributional shifts among populations and availability of suitable habitat in future oceans. The results of our integrated approach provide new perspective on how cryptic intraspecific diversity associated with climatic variation influences species and community response to climate change beyond simple poleward shifts. PMID:29600272</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC34A..08E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC34A..08E"><span>A Signal to Noise Paradox in Climate Predictions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Eade, R.; Scaife, A. A.; Smith, D.; Dunstone, N. J.; MacLachlan, C.; Hermanson, L.; Ruth, C.</p> <p>2017-12-01</p> <p>Recent advances in climate modelling have resulted in the achievement of skilful long-range prediction, particular that associated with the winter circulation over the north Atlantic (e.g. Scaife et al 2014, Stockdale et al 2015, Dunstone et al 2016) including impacts over Europe and North America, and further afield. However, while highly significant and potentially useful skill exists, the signal-to-noise ratio of the ensemble mean to total variability in these ensemble predictions is anomalously small (Scaife et al 2014) and the correlation between the ensemble mean and historical observations exceeds the proportion of predictable variance in the ensemble (Eade et al 2014). This means the real world is more predictable than our climate models. Here we discuss a series of hypothesis tests that have been carried out to assess issues with model mechanisms compared to the observed world, and present the latest findings in our attempt to determine the cause of the anomalously weak predicted signals in our seasonal-to-decadal hindcasts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC41B1088G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC41B1088G"><span>Comparative Assessment of a New Hydrological Modelling Approach for Prediction of Runoff in Gauged and Ungauged Basins, and Climate Change Impacts Assessment: A Case Study from Benin.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>GABA, C. O. U.; Alamou, E.; Afouda, A.; Diekkrüger, B.</p> <p>2016-12-01</p> <p>Assessing water resources is still an important challenge especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we investigate a new modelling approach based on the Physics Principle of Least Action which was first applied to the Bétérou catchment in Benin and gave very good results. The study presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODHYPMA was applied to sixteen (16) subcatchments in Bénin, West Africa. Its performance was compared to two well-known lumped conceptual models, the GR4J and HBV models. The model was successfully calibrated and validated and showed a good performance in most catchments. The analysis revealed that the three models have similar performance and timing errors. But in contrary to other models, MODHYMA is subject to a less loss of performance from calibration to validation. In order to evaluate the usefulness of our model for the prediction of runoff in ungauged basins, model parameters were estimated from the physical catchments characteristics. We relied on statistical methods applied on calibrated model parameters to deduce relationships between parameters and physical catchments characteristics. These relationships were further tested and validated on gauged basins that were considered ungauged. This regionalization was also performed for GR4J model.We obtained NSE values greater than 0.7 for MODHYPMA while the NSE values for GR4J were inferior to 0.5. In the presented study, the effects of climate change on water resources in the Ouémé catchment at the outlet of Savè (about 23 500 km2) are quantified. The output of a regional climate model was used as input to the hydrological models.Computed within the GLOWA-IMPETUS project, the future climate projections (describing a rainfall reduction of up to 15%) are derived from the regional climate model REMO driven by the global ECHAM model.The results reveal a significant decrease in future water resources (of -66% to -53% for MODHYPMA and of -59% to -46% for GR4J) for the IPCC climate scenarios A1B and B1.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA....13406H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA....13406H"><span>Climate change streamflow scenarios designed for critical period water resources planning studies</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.</p> <p>2003-04-01</p> <p>Long-range water planning in the United States is usually conducted by individual water management agencies using a critical period planning exercise based on a particular period of the observed streamflow record and a suite of internally-developed simulation tools representing the water system. In the context of planning for climate change, such an approach is flawed in that it assumes that the future climate will be like the historic record. Although more sophisticated planning methods will probably be required as time goes on, a short term strategy for incorporating climate uncertainty into long-range water planning as soon as possible is to create alternate inputs to existing planning methods that account for climate uncertainty as it affects both supply and demand. We describe a straight-forward technique for constructing streamflow scenarios based on the historic record that include the broad-based effects of changed regional climate simulated by several global climate models (GCMs). The streamflow scenarios are based on hydrologic simulations driven by historic climate data perturbed according to regional climate signals from four GCMs using the simple "delta" method. Further data processing then removes systematic hydrologic model bias using a quantile-based bias correction scheme, and lastly, the effects of random errors in the raw hydrologic simulations are removed. These techniques produce streamflow scenarios that are consistent in time and space with the historic streamflow record while incorporating fundamental changes in temperature and precipitation from the GCM scenarios. Planning model simulations based on these climate change streamflow scenarios can therefore be compared directly to planning model simulations based on the historic record of streamflows to help planners understand the potential impacts of climate uncertainty. The methods are currently being tested and refined in two large-scale planning exercises currently being conducted in the Pacific Northwest (PNW) region of the US, and the resulting streamflow scenarios will be made freely available on the internet for a large number of sites in the PNW to help defray the costs of including climate change information in other studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1613392C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1613392C"><span>Clime: analyzing and producing climate data in GIS environment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cattaneo, Luigi; Rillo, Valeria; Mercogliano, Paola</p> <p>2014-05-01</p> <p>In the last years, Impacts on Soil and Coasts Division (ISC) of CMCC (Euro-Mediterranean Center on Climate Change) had several collaboration experiences with impact communities, including IS-ENES (FP7-INF) and SafeLand (FP7-ENV) projects, which involved a study of landslide risk in Europe, and is currently active in GEMINA (FIRB) and ORIENTGATE (SEE Transnational Cooperation Programme) research projects. As a result, it has brought research activities about different impact of climate changes as flood and landslide hazards, based on climate simulation obtained from the high resolution regional climate models COSMO CLM, developed at CMCC as member of the consortium CLM Assembly. ISC-Capua also collaborates with local institutions interested in atmospherical climate change and also of their impacts on the soil, such as river basin authorities in the Campania region, ARPA Emilia Romagna and ARPA Calabria. Impact models (e.g. hydraulic or stability models) are usually developed in a GIS environment, since they need an accurate territory description, so Clime has been designed to bridge the usually existing gap between climate data - both observed and simulated - gathered from different sources, and impact communities. The main goal of Clime, special purpose Geographic Information System (GIS) software integrated in ESRI ArcGIS Desktop 10, is to easily evaluate multiple climate features and study climate changes over specific geographical domains with their related effects on environment, including impacts on soil. Developed as an add-in tool, this software has been conceived for research activities of ISC Division in order to provide a substantial contribution during post-processing and validation phase. Therefore, it is possible to analyze and compare multiple datasets (observations, climate simulations, etc.) through processes involving statistical functions, percentiles, trends test and evaluation of extreme events with a flexible system of temporal and spatial filtering, and to represent results as maps, temporal and statistic plots (time series, seasonal cycles, PDFs, scatter plots, Taylor diagrams) or Excel tables; in addition, it features bias correction techniques for climate model results. Summarizing, Clime is able to provide users a simple and fast way to retrieve analysis over simulated climate data and observations within any geographical site of interest (provinces, regions, countries, etc.).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/circ/1989/1030/report.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/circ/1989/1030/report.pdf"><span>Water resources in the twenty-first century; a study of the implications of climate uncertainty</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Moss, Marshall E.; Lins, Harry F.</p> <p>1989-01-01</p> <p>The interactions of the water resources on and within the surface of the Earth with the atmosphere that surrounds it are exceedingly complex. Increased uncertainty can be attached to the availability of water of usable quality in the 21st century, therefore, because of potential anthropogenic changes in the global climate system. For the U.S. Geological Survey to continue to fulfill its mission with respect to assessing the Nation's water resources, an expanded program to study the hydrologic implications of climate uncertainty will be required. The goal for this program is to develop knowledge and information concerning the potential water-resources implications for the United States of uncertainties in climate that may result from both anthropogenic and natural changes of the Earth's atmosphere. Like most past and current water-resources programs of the Geological Survey, the climate-uncertainty program should be composed of three elements: (1) research, (2) data collection, and (3) interpretive studies. However, unlike most other programs, the climate-uncertainty program necessarily will be dominated by its research component during its early years. Critical new concerns to be addressed by the research component are (1) areal estimates of evapotranspiration, (2) hydrologic resolution within atmospheric (climatic) models at the global scale and at mesoscales, (3) linkages between hydrology and climatology, and (4) methodology for the design of data networks that will help to track the impacts of climate change on water resources. Other ongoing activities in U.S. Geological Survey research programs will be enhanced to make them more compatible with climate-uncertainty research needs. The existing hydrologic data base of the Geological Survey serves as a key element in assessing hydrologic and climatologic change. However, this data base has evolved in response to other needs for hydrologic information and probably is not as sensitive to climate change as is desirable. Therefore, as measurement and network-design methodologies are improved to account for climate-change potential, new data-collection activities will be added to the existing programs. One particular area of data-collection concern pertains to the phenomenon of evapotranspiration. Interpretive studies of the hydrologic implications of climate uncertainty will be initiated by establishing several studies at the river-basin scale in diverse hydroclimatic and demographic settings. These studies will serve as tests of the existing methodologies for studying the impacts of climate change and also will help to define subsequent research priorities. A prototype for these studies was initiated in early 1988 in the Delaware River basin.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC33F1145T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC33F1145T"><span>Changes in mountain glacier systems and the distribution of main climatic parameters on the territory of Russia (second part of the XX -beginning of the XXI century).</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tatiana, K.; Nosenko, G.; Popova, V.; Muraviev, A.; Nikitin, S.; Chernova, L.</p> <p>2017-12-01</p> <p>Mountain glaciers are vital sources of water worldwide to many densely-populated regions. Most glaciers are now shrinking, resulting in variable water supplies and sustained sea level rise. Rapid glacier change threatens water, energy and food security. Further glacier mass loss is likely in response to recent climate change, driven by global increases in air temperatures and the production of atmospheric pollutants. However, high altitudes and rugged topography generate regional weather systems that complicate the investigation of the relationship between climate and glacier change. Predictive models need to move beyond the state-of-the-art to couple advanced climate models with accurate representations of glacier processes, and more detailed and reliable data describing the state of mountain glaciers are required to constrain these models, both from monitoring individual glaciers and regional remote-sensing observations. Glaciation exists on the territory of Russia for thousands of years. At present both mountain glaciers and continental ice sheets are present there. Continental ice sheets are located on islands and archipelagoes of Russian Arctic region and mountain glaciers are wide-spread on continental part of the country where it currently covers the area of about 3,480,000 km². Now there are 18 mountain glacier regions on the territory of Russia. We present recent data on glaciers state and changes in mountain regions of Russia based on remote sensing and in situ studies and distribution of main climatic parameters that affect the existence of glaciers: summer air temperature, winter precipitations and maximum value of snow thickness. Acknowledgements. This presentation includes the results of research project № 0148-2014-0007 of the Research Plan of the Institute of Geography, RAS and research project supported by the Russian Geographical Society (grant number 05/2017/RGS-RFBR).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMED11E..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMED11E..08B"><span>Through the minefield: teaching climate change in a misinformation-rich environment</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bedford, D. P.; Cook, J.; Schuenemann, K. C.; Mandia, S. A.; Cowtan, K.; Nuccitelli, D.</p> <p>2016-12-01</p> <p>It is now widely accepted that students enter science classrooms with their own, often erroneous, pre-existing models of basic scientific concepts. These misconceptions can interfere with student learning. However, the science of climate change is perhaps distinctive in that a deliberate effort has been undertaken by a variety of individuals and institutions to promulgate and perpetuate misconceptions. Both formal and informal efforts to communicate the science of climate change must therefore contend with the effects of these misconceptions, which may be passionately held and in strong opposition to the findings of peer-reviewed research. This presentation reports on the current state of research on misinformation and misconceptions; identifies common mistakes made in attempting to address misconceptions; and details a model which can help to avoid making most, if not all, of these common mistakes. In sum, research in cognitive psychology has shown that misconceptions are extraordinarily difficult to remove, with individuals commonly rejecting information that does not fit with their existing mental models. Attempts to address misconceptions directly can backfire if too much emphasis is placed on the misconception (i.e. leading with the myth) or by reinforcing the misconception at the expense of more accurate explanations (the familiarity backfire effect). Thus, a preferred approach involves a "myth sandwich" of facts followed by myth, followed by an explanation of how the myth distorts the facts. The misconception is therefore sandwiched between facts. This approach has been tested in a widely subscribed MOOC (Denial 101X, by Cook et al., 2015), and a textbook (Bedford and Cook, 2016). This presentation provides fundamental background on effective climate change myth debunking, and will include preliminary data regarding the efficacy of the "myth sandwich" approach.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23560987','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23560987"><span>Energy technologies evaluated against climate targets using a cost and carbon trade-off curve.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Trancik, Jessika E; Cross-Call, Daniel</p> <p>2013-06-18</p> <p>Over the next few decades, severe cuts in emissions from energy will be required to meet global climate-change mitigation goals. These emission reductions imply a major shift toward low-carbon energy technologies, and the economic cost and technical feasibility of mitigation are therefore highly dependent upon the future performance of energy technologies. However, existing models do not readily translate into quantitative targets against which we can judge the dynamic performance of technologies. Here, we present a simple, new model for evaluating energy-supply technologies and their improvement trajectories against climate-change mitigation goals. We define a target for technology performance in terms of the carbon intensity of energy, consistent with emission reduction goals, and show how the target depends upon energy demand levels. Because the cost of energy determines the level of adoption, we then compare supply technologies to one another and to this target based on their position on a cost and carbon trade-off curve and how the position changes over time. Applying the model to U.S. electricity, we show that the target for carbon intensity will approach zero by midcentury for commonly cited emission reduction goals, even under a high demand-side efficiency scenario. For Chinese electricity, the carbon intensity target is relaxed and less certain because of lesser emission reductions and greater variability in energy demand projections. Examining a century-long database on changes in the cost-carbon space, we find that the magnitude of changes in cost and carbon intensity that are required to meet future performance targets is not unprecedented, providing some evidence that these targets are within engineering reach. The cost and carbon trade-off curve can be used to evaluate the dynamic performance of existing and new technologies against climate-change mitigation goals.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43D1681Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43D1681Z"><span>An Analytic Equation Partitioning Climate Variation and Human Impacts on River Sediment Load</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, J.; Gao, G.; Fu, B.</p> <p>2017-12-01</p> <p>Spatial or temporal patterns and process-based equations could co-exist in hydrologic model. Yet, existing approaches quantifying the impacts of those variables on river sediment load (RSL) changes are found to be severely limited, and new ways to evaluate the contribution of these variables are thus needed. Actually, the Newtonian modeling is hardly achievable for this process due to the limitation of both observations and knowledge of mechanisms, whereas laws based on the Darwinian approach could provide one component of a developed hydrologic model. Since that streamflow is the carrier of suspended sediment, sediment load changes are documented in changes of streamflow and suspended sediment concentration (SSC) - water discharge relationships. Consequently, an analytic equation for river sediment load changes are proposed to explicitly quantify the relative contributions of climate variation and direct human impacts on river sediment load changes. Initially, the sediment rating curve, which is of great significance in RSL changes analysis, was decomposed as probability distribution of streamflow and the corresponding SSC - water discharge relationships at equally spaced discharge classes. Furthermore, a proposed segmentation algorithm based on the fractal theory was used to decompose RSL changes attributed to these two portions. Additionally, the water balance framework was utilized and the corresponding elastic parameters were calculated. Finally, changes in climate variables (i.e. precipitation and potential evapotranspiration) and direct human impacts on river sediment load could be figured out. By data simulation, the efficiency of the segmentation algorithm was verified. The analytic equation provides a superior Darwinian approach partitioning climate and human impacts on RSL changes, as only data series of precipitation, potential evapotranspiration and SSC - water discharge are demanded.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP53D..04E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP53D..04E"><span>Connecting medieval megadroughts and surface climate in the Last Millennium Reanalysis</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Erb, M. P.; Emile-Geay, J.; Anderson, D. M.; Hakim, G. J.; Horlick, K. A.; Noone, D.; Perkins, W. A.; Steig, E. J.; Tardif, R.</p> <p>2016-12-01</p> <p>The North American Drought Atlas shows severe, long-lasting droughts during the Medieval Climate Anomaly. Because drought frequency and severity over the coming century is an area of vital interest, better understanding the causes of these historic droughts is crucial. A variety of research has suggested that a La Niña state was important for producing medieval megadroughts [1], and other work has indicated the potential roles of the Atlantic Multidecadal Oscillation [2] and internal atmospheric variability [3]. Correlations between drought and large-scale climate patterns also exist in the instrumental record [4], but understanding these relationships is far from complete. To investigate these relationships further, a data assimilation approach is employed. Proxy records - including tree rings, corals, and ice cores - are used to constrain climate states over the Common Era. By using general circulation model (GCM) output to quantify the covariances in the climate system, climate can be constrained not just at proxy sites but for all covarying locations and climate fields. Multiple GCMs will be employed to offset the limitations of imperfect model physics. This "Last Millennium Reanalysis" will be used to quantify relationships between North American medieval megadroughts and sea surface temperature patterns in the Atlantic and Pacific. 1. Cook, E. R., et al., Earth-Sci. Rev. 81, 93 (2007). 2. Oglesby, R., et al., Global Planet. Change 84-85, 56 (2012). 3. Stevenson, S., et al., J. Climate 28, 1865 (2015). 4. Cook, B. I., et al., J. Climate 27, 383 (2014).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001AGUFM.H21G..04D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001AGUFM.H21G..04D"><span>Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900-2099</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.</p> <p>2001-12-01</p> <p>Sensitivities of river basins in the Sierra Nevada of California to historical and future climate variations and changes are analyzed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-year period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th Century until about 1975, when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st Century with an attendant +2.5ºC warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. In contrast, a control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995, yields climate and streamflow-timing conditions much like the 1980s and 1990s throughout its duration. Long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. The various projected trends in the business-as-usual simulations become readily visible above simulated natural climatic and hydrologic variability by about 2020.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20150008317&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bchange%2Banthropogenic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150008317&hterms=climate+change+anthropogenic&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dclimate%2Bchange%2Banthropogenic"><span>The Green Sahara: Climate Change, Hydrologic History and Human Occupation</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blom, Ronald G.; Farr, Tom G.; Feynmann, Joan; Ruzmaikin, Alexander; Paillou, Philippe</p> <p>2009-01-01</p> <p>Archaeology can provide insight into interactions of climate change and human activities in sensitive areas such as the Sahara, to the benefit of both disciplines. Such analyses can help set bounds on climate change projections, perhaps identify elements of tipping points, and provide constraints on models. The opportunity exists to more precisely constrain the relationship of natural solar and climate interactions, improving understanding of present and future anthropogenic forcing. We are beginning to explore the relationship of human occupation of the Sahara and long-term solar irradiance variations synergetic with changes in atmospheric-ocean circulation patterns. Archaeological and climate records for the last 12 K years are gaining adequate precision to make such comparisons possible. We employ a range of climate records taken over the globe (e.g. Antarctica, Greenland, Cariaco Basin, West African Ocean cores, records from caves) to identify the timing and spatial patterns affecting Saharan climate to compare with archaeological records. We see correlation in changing ocean temperature patterns approx. contemporaneous with drying of the Sahara approx. 6K years BP. The role of radar images and other remote sensing in this work includes providing a geographically comprehensive geomorphic overview of this key area. Such coverage is becoming available from the Japanese PALSAR radar system, which can guide field work to collect archaeological and climatic data to further constrain the climate change chronology and link to models. Our initial remote sensing efforts concentrate on the Gilf Kebir area of Egypt.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC22A..02M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC22A..02M"><span>A Multi-Sector Assessment of the Effects of Climate Change at the Energy-Water-Land Nexus in the US</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McFarland, J.; Sarofim, M. C.; Martinich, J.</p> <p>2017-12-01</p> <p>Rising temperatures and changing precipitation patterns due to climate change are projected to alter many sectors of the US economy. A growing body of research has examined these effects in the energy, water, and agricultural sectors. Rising summer temperatures increase the demand for electricity. Changing precipitation patterns effect the availability of water for hydropower generation, thermo-electric cooling, irrigation, and municipal and industrial consumption. A combination of changes to temperature and precipitation alter crop yields and cost-effective farming practices. Although a significant body of research exists on analyzing impacts to individual sectors, fewer studies examine the effects using a common set of assumptions (e.g., climatic and socio-economic) within a coupled modeling framework. The present analysis uses a multi-sector, multi-model framework with common input assumptions to assess the projected effects of climate change on energy, water, and land-use in the United States. The analysis assesses the climate impacts for across 5 global circulation models for representative concentration pathways (RCP) of 8.5 and 4.5 W/m2. The energy sector models - Pacific Northwest National Lab's Global Change Assessment Model (GCAM) and the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) - show the effects of rising temperature on energy and electricity demand. Electricity supply in ReEDS is also affected by the availability of water for hydropower and thermo-electric cooling. Water availability is calculated from the GCM's precipitation using the US Basins model. The effects on agriculture are estimated using both a process-based crop model (EPIC) and an agricultural economic model (FASOM-GHG), which adjusts water supply curves based on information from US Basins. The sectoral models show higher economic costs of climate change under RCP 8.5 than RCP 4.5 averaged across the country and across GCM's.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC13A1066A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC13A1066A"><span>Climate change impact on the annual water balance in the northwest Florida coastal</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alizad, K.; Wang, D.; Alimohammadi, N.; Hagen, S. C.</p> <p>2012-12-01</p> <p>As the largest tributary to the Apalachicola River, the Chipola River originates in southern Alabama, flows through Florida Panhandle and ended to Gulf of Mexico. The Chipola watershed is located in an intermediate climate environment with aridity index around one. Watershed provides habitat for a number of threatened and endangered animal and plant species. However, climate change affects hydrologic cycle of Chipola River watershed at various temporal and spatial scales. Studying the effects of climate variations is of great importance for water and environmental management purposes in this catchment. This research is mainly focuses on assessing climate change impact on the partitioning pattern of rainfall from mean annual to inter-annual and to seasonal scales. At the mean annual scale, rainfall is partitioned into runoff and evaporation assuming negligible water storage changes. Mean annual runoff is controlled by both mean annual precipitation and potential evaporation. Changes in long term mean runoff caused by variations of long term mean precipitation and potential evaporation will be evaluated based on Budyko hypothesis. At the annual scale, rainfall is partitioned into runoff, evaporation, and storage change. Inter-annual variability of runoff and evaporation are mainly affected by the changes of mean annual climate variables as well as their inter-annual variability. In order to model and evaluate each component of water balance at the annual scale, parsimonious but reliable models, are developed. Budyko hypothesis on the existing balance between available water and energy supply is reconsidered and redefined for the sub-annual time scale and reconstructed accordingly in order to accurately model seasonal hydrologic balance of the catchment. Models are built in the seasonal time frame with a focus on the role of storage change in water cycle. Then for Chipola catchment, models are parameterized based on a sufficient time span of historical data and the their coefficients are quantified. For necessary future predictions, data obtained from climate regional models starting 2040 to 2069 will be utilized. To accommodate the inherent uncertainty of climate projections, an ensemble of regional climate models will be used to assess changes of rainfall and potential evaporation. Then, the climate change impact on seasonal and annual runoff, evaporation, and water storage changes will be projected.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..120.9965N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..120.9965N"><span>Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John</p> <p>2015-10-01</p> <p>As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A33H..01M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A33H..01M"><span>Impacts of past and future climate change on wind energy resources in the United States</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McCaa, J. R.; Wood, A.; Eichelberger, S.; Westrick, K.</p> <p>2009-12-01</p> <p>The links between climate change and trends in wind energy resources have important potential implications for the wind energy industry, and have received significant attention in recent studies. We have conducted two studies that provide insights into the potential for climate change to affect future wind power production. In one experiment, we projected changes in power capacity for a hypothetical wind farm located near Kennewick, Washington, due to greenhouse gas-induced climate change, estimated using a set of regional climate model simulations. Our results show that the annual wind farm power capacity is projected to decrease 1.3% by 2050. In a wider study focusing on wind speed instead of power, we analyzed projected changes in wind speed from 14 different climate simulations that were performed in support of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). Our results show that the predicted ensemble mean changes in annual mean wind speeds are expected to be modest. However, seasonal changes and changes predicted by individual models are large enough to affect the profitability of existing and future wind projects. The majority of the model simulations reveal that near-surface wind speed values are expected to shift poleward in response to the IPCC A2 emission scenario, particularly during the winter season. In the United States, most models agree that the mean annual wind speed values will increase in a region extending from the Great Lakes southward across the Midwest and into Texas. Decreased values, though, are predicted across most of the western United States. However, these predicted changes have a strong seasonal dependence, with wind speed increases over most of the United States during the winter and decreases over the northern United States during the summer.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29656409','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29656409"><span>Investigating Impacts of Climate Change on Irrigation Water Demands and Its Resulting Consequences on Groundwater Using CMIP5 Models.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Goodarzi, Mustafa; Abedi-Koupai, Jahangir; Heidarpour, Manouchehr</p> <p>2018-04-15</p> <p>In this study, the impacts of climate change on crop water requirements and irrigation water requirements on the regional cropping pattern were evaluated using two climate change scenarios and combinations of 20 GCM models. Different models including CROPWAT, MODFLOW, and statistical models were used to evaluate the climate change impacts. The results showed that in the future period (2017 to 2046) the temperature in all months of the year will increase at all stations. The average annual precipitation decline in Isfahan, Tiran, Flavarjan, and Lenj stations for RCP 4.5 and RCP 8.5 scenarios are 18.6 and 27.6%, 15.2 and 18%, 22.5 and 31.5%, and 10.5 and 12.1%, respectively. The average increase in the evapotranspiration for RCP 4.5 and RCP 8.5 scenarios are about 2.5 and 4.1%, respectively. The irrigation water demands increases considerably and for some crops, on average 18%. Among the existing crops in the cropping pattern, barley, cumin, onion, wheat, and forage crops are more sensitive and their water demand will increase significantly. Results indicate that climate change could have a significant impact on water resources consumption. By considering irrigation efficiency in the region, climate change impacts will result in about 35 to 50 million m 3 /year, over-extraction from the aquifer. This additional exploitation causes an extra drop of 0.4 to 0.8 m in groundwater table per year in the aquifer. Therefore, with regard to the critical condition of the aquifer, management and preventive measures to deal with climate change in the future is absolutely necessary. © 2018, National Ground Water Association.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814833T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814833T"><span>The volcanic double event at the dawn of the Dark Ages</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Toohey, Matthew; Sigl, Michael; Krüger, Kirstin; Stordal, Frode; Svensen, Henrik</p> <p>2016-04-01</p> <p>Documentary records report dimming of the sun by a mysterious dust cloud covering Europe for 12-18 months in 536-537 CE, which was followed by a general climatic downturn and global societal decline. Tree rings and other climate proxies have corroborated the occurrence of this event as well as characterized its extent and duration, but failed to trace its origin. New volcanic timeseries, based on a multi-disciplinary approach that integrates novel, global-scale time markers with state-of-the-art continuous ice core aerosol measurements, automated objective ice-core layer counting, tephra analyses, and detailed examination of historical archives, show unequivocally that the 536-540 climate anomaly was concurrent with two or more major volcanic eruptions, with the largest eruptions likely occurring in the years 536 and 540 CE. Using a coupled aerosol-climate model, with eruption parameters constrained by ice core records and historical observations of the aerosol cloud, we reconstruct the radiative forcing resulting from the 536/540 CE eruption sequence. Comparing with existing reconstructions of the volcanic forcing over the past 1200 years, we estimate that the decadal-scale Northern Hemisphere (NH) extra-tropical radiative forcing from this volcanic "double event" was larger than that of any known period. Earth system model simulations including the volcanic forcing are used to explore the temperature and precipitation anomalies associated with the eruptions, and compared to available proxy records, including maximum latewood density (MXD) temperature reconstructions. Special attention is placed on the decadal persistence of the cooling signal in tree rings, and whether the climate model simulations reproduce such long-term climate anomalies. Finally, the climate model results are used to explore the probability of socioeconomic crisis resulting directly from the volcanic radiative forcing in different regions of the world.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5288658','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5288658"><span>Fewer clouds in the Mediterranean: consistency of observations and climate simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.</p> <p>2017-01-01</p> <p>Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009CliPa...5..147H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009CliPa...5..147H"><span>Climate reconstruction from pollen and δ13C records using inverse vegetation modeling - Implication for past and future climates</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hatté, C.; Rousseau, D.-D.; Guiot, J.</p> <p>2009-04-01</p> <p>An improved inverse vegetation model has been designed to better specify both temperature and precipitation estimates from vegetation descriptions. It is based on the BIOME4 vegetation model and uses both vegetation δ13C and biome as constraints. Previous inverse models based on only one of the two proxies were already improvements over standard reconstruction methods such as the modern analog since these did not take into account some external forcings, for example CO2 concentration. This new approach makes it possible to describe a potential "isotopic niche" defined by analogy with the "climatic niche" theory. Boreal and temperate biomes simulated by BIOME4 are considered in this study. We demonstrate the impact of CO2 concentration on biome existence domains by replacing a "most likely biome" with another with increased CO2 concentration. Additionally, the climate imprint on δ13C between and within biomes is shown: the colder the biome, the lighter its potential isotopic niche; and the higher the precipitation, the lighter the δ13C. For paleoclimate purposes, previous inverse models based on either biome or δ13C did not allow informative paleoclimatic reconstructions of both precipitation and temperature. Application of the new approach to the Eemian of La Grande Pile palynological and geochemical records reduces the range in precipitation values by more than 50% reduces the range in temperatures by about 15% compared to previous inverse modeling approaches. This shows evidence of climate instabilities during Eemian period that can be correlated with independent continental and marine records.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009CliPD...5...73H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009CliPD...5...73H"><span>Climate reconstruction from pollen and δ13C using inverse vegetation modeling. Implication for past and future climates</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hatté, C.; Rousseau, D.-D.; Guiot, J.</p> <p>2009-01-01</p> <p>An improved inverse vegetation model has been designed to better specify both temperature and precipitation estimates from vegetation descriptions. It is based on the BIOME4 vegetation model and uses both vegetation δ13C and biome as constraints. Previous inverse models based on only one of the two proxies were already improvements over standard reconstruction methods such as the modern analog since these did not take into account some external forcings, for example CO2 concentration. This new approach makes it possible to describe a potential "isotopic niche" defined by analogy with the "climatic niche" theory. Boreal and temperate biomes simulated by BIOME4 are considered in this study. We demonstrate the impact of CO2 concentration on biome existence domains by replacing a "most likely biome" with another with increased CO2 concentration. Additionally, the climate imprint on δ13C between and within biomes is shown: the colder the biome, the lighter its potential isotopic niche; and the higher the precipitation, the lighter the δ13C. For paleoclimate purposes, previous inverse models based on either biome or δ13C did not allow informative paleoclimatic reconstructions of both precipitation and temperature. Application of the new approach to the Eemian of La Grande Pile palynological and geochemical records reduces the range in precipitation values by more than 50% reduces the range in temperatures by about 15% compared to previous inverse modeling approaches. This shows evidence of climate instabilities during Eemian period that can be correlated with independent continental and marine records.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.H33D1344P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.H33D1344P"><span>Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, C.; Lee, J.; Koo, M.</p> <p>2011-12-01</p> <p>Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110005664','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110005664"><span>Constraints and Opportunities in GCM Model Development</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schmidt, Gavin; Clune, Thomas</p> <p>2010-01-01</p> <p>Over the past 30 years climate models have evolved from relatively simple representations of a few atmospheric processes to complex multi-disciplinary system models which incorporate physics from bottom of the ocean to the mesopause and are used for seasonal to multi-million year timescales. Computer infrastructure over that period has gone from punchcard mainframes to modern parallel clusters. Constraints of working within an ever evolving research code mean that most software changes must be incremental so as not to disrupt scientific throughput. Unfortunately, programming methodologies have generally not kept pace with these challenges, and existing implementations now present a heavy and growing burden on further model development as well as limiting flexibility and reliability. Opportunely, advances in software engineering from other disciplines (e.g. the commercial software industry) as well as new generations of powerful development tools can be incorporated by the model developers to incrementally and systematically improve underlying implementations and reverse the long term trend of increasing development overhead. However, these methodologies cannot be applied blindly, but rather must be carefully tailored to the unique characteristics of scientific software development. We will discuss the need for close integration of software engineers and climate scientists to find the optimal processes for climate modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008JGRD..113.5103R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008JGRD..113.5103R"><span>Predicting the response of seven Asian glaciers to future climate scenarios using a simple linear glacier model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ren, Diandong; Karoly, David J.</p> <p>2008-03-01</p> <p>Observations from seven Central Asian glaciers (35-55°N; 70-95°E) are used, together with regional temperature data, to infer uncertain parameters for a simple linear model of the glacier length variations. The glacier model is based on first order glacier dynamics and requires the knowledge of reference states of forcing and glacier perturbation magnitude. An adjoint-based variational method is used to optimally determine the glacier reference states in 1900 and the uncertain glacier model parameters. The simple glacier model is then used to estimate the glacier length variations until 2060 using regional temperature projections from an ensemble of climate model simulations for a future climate change scenario (SRES A2). For the period 2000-2060, all glaciers are projected to experience substantial further shrinkage, especially those with gentle slopes (e.g., Glacier Chogo Lungma retreats ˜4 km). Although nearly one-third of the year 2000 length will be reduced for some small glaciers, the existence of the glaciers studied here is not threatened by year 2060. The differences between the individual glacier responses are large. No straightforward relationship is found between glacier size and the projected fractional change of its length.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70171088','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70171088"><span>Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Foster, Jane R.; Finley, Andrew O.; D'Amato, Anthony W.; Bradford, John B.; Banerjee, Sudipto</p> <p>2016-01-01</p> <p>As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26717889','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26717889"><span>Predicting tree biomass growth in the temperate-boreal ecotone: Is tree size, age, competition, or climate response most important?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Foster, Jane R; Finley, Andrew O; D'Amato, Anthony W; Bradford, John B; Banerjee, Sudipto</p> <p>2016-06-01</p> <p>As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2 and thereby slow rising CO2 concentrations. Forests' ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals' size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92-95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone. © 2015 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA13A2177S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA13A2177S"><span>Uncertainty in Driftless Area Cold-Water Fishery Decision Making and a Framework for Stakeholder-Based Science</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schuster, Z.</p> <p>2015-12-01</p> <p>The paradigm of stakeholder-based science is becoming more popular as organizations such as the U.S. Department of the Interior Climate Science Centers adopt it as a way of providing practicable climate change information to practitioners. One of the key issues stakeholders face in adopting climate change information into their decision processes is how uncertainty is addressed and communicated. In this study, we conducted a series of semi-structured interviews with managers and scientists working on stream habitat restoration of cold-water fisheries in the Driftless Area of Wisconsin that were focused on how they interpret and manage uncertainty and what types of information they need to make better decisions. One of the important lessons we learned from the interviews is that if researchers are going to provide useful climate change information to stakeholders, they need to understand where and how decisions are made and what adaptation measures are actually available in a given decision arena. This method of incorporating social science methods into climate science production can provide a framework for researchers from the Climate Science Centers and others who are interested in pursuing stakeholder-based science. By indentifying a specific ecological system and conducting interviews with actors who work on that system, researchers will be able to gain a better understanding of how their climate change science can fit into existing or shape new decision processes. We also interpreted lessons learned from our interviews via existing literature in areas such as stakeholder-based modeling and the decision sciences to provide guidance specific to the stakeholder-based science process.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017DSRII.140..290A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017DSRII.140..290A"><span>Developing a climate adaptation strategy for vulnerable seabirds based on prioritisation of intervention options</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alderman, Rachael; Hobday, Alistair J.</p> <p>2017-06-01</p> <p>Conservation of marine species typically focuses on monitoring and mitigating demonstrated stressors where possible. Evidence is accumulating that some species will be negatively affected in the future by climate change and that reduction of existing stressors may not be sufficient to offset these impacts. Recent work suggests the shy albatross (Thalassarche cauta) will be adversely affected by projected changes in environmental conditions under plausible climate change scenarios. Furthermore, modelling shows that elimination of the principal present-day threat to albatrosses, fisheries bycatch, an achievable and critical priority, may not be sufficient to reverse projected population declines due to climate impacts, which cannot be directly eliminated. Here, a case study is presented in which a range of intervention options, in preparation for predicted climate change impacts, are identified and evaluated. A suite of 24 plausible climate adaptation options is first assessed using a semi-quantitative cost-benefit-risk tool, leading to a relative ranking of actions. Of these options, increasing chick survival via reduction of disease prevalence through control of vectors, was selected for field trials. Avian insecticide was applied to chicks' mid-way through their development and the effect on subsequent survival was evaluated. Survival of treated chicks after six weeks was significantly higher (92.7%) than those in control areas (82.1%). This approach shows that options to enhance albatross populations exist and we argue that testing interventions prior to serious impacts can formalise institutional processes and allow refinement of actions that offer some chance of mitigating the impacts of climate change on iconic marine species.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=sol&pg=4&id=ED567490','ERIC'); return false;" href="https://eric.ed.gov/?q=sol&pg=4&id=ED567490"><span>The Impact of School Climate on Student Achievement in the Middle Schools of the Commonwealth of Virginia: A Quantitative Analysis of Existing Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Bergren, David Alexander</p> <p>2014-01-01</p> <p>This quantitative study was designed to be an analysis of the relationship between school climate and student achievement through the creation of an index of climate-factors (SES, discipline, attendance, and school size) for which publicly available data existed. The index that was formed served as a proxy measure of climate; it was analyzed…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017IJBm...61.1593P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017IJBm...61.1593P"><span>Comparing mechanistic and empirical approaches to modeling the thermal niche of almond</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Parker, Lauren E.; Abatzoglou, John T.</p> <p>2017-09-01</p> <p>Delineating locations that are thermally viable for cultivating high-value crops can help to guide land use planning, agronomics, and water management. Three modeling approaches were used to identify the potential distribution and key thermal constraints on on almond cultivation across the southwestern United States (US), including two empirical species distribution models (SDMs)—one using commonly used bioclimatic variables (traditional SDM) and the other using more physiologically relevant climate variables (nontraditional SDM)—and a mechanistic model (MM) developed using published thermal limitations from field studies. While models showed comparable results over the majority of the domain, including over existing croplands with high almond density, the MM suggested the greatest potential for the geographic expansion of almond cultivation, with frost susceptibility and insufficient heat accumulation being the primary thermal constraints in the southwestern US. The traditional SDM over-predicted almond suitability in locations shown by the MM to be limited by frost, whereas the nontraditional SDM showed greater agreement with the MM in these locations, indicating that incorporating physiologically relevant variables in SDMs can improve predictions. Finally, opportunities for geographic expansion of almond cultivation under current climatic conditions in the region may be limited, suggesting that increasing production may rely on agronomical advances and densifying current almond plantations in existing locations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H24B..02Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H24B..02Y"><span>Impacts of Climate Change on Stream Temperatures in the Clearwater River, Idaho</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yearsley, J. R.; Chegwidden, O.; Nijssen, B.</p> <p>2016-12-01</p> <p>Dworshak Dam in northern Idaho impounds the waters of the North Fork of the Clearwater River, creating a reservoir of approximately 4.278 km3 at full pool elevation. The dam's primary purpose is for flood control and hydroelectric power generation. It also provides important water quality benefits by releasing cold water into the Clearwater River during the summer when conditions become critical for migrating endangered species of salmon. Changes in the climate may have an impact on the ability of Dworshak Dam and Reservoir to provide these benefits. To investigate the potential for extreme outcomes that would limit cold water releases from Dworshak Reservoir and compromise the fishery, we implemented a system of hydrologic and water temperature models that simulate daily-averaged water temperatures in both the riverine and reservoir environments. We used the macroscale hydrologic model, VIC, to simulate land surface water and energy fluxes, the one-dimensional, time-dependent stream temperature model, RBM, to simulate river temperatures and a modified version of CEQUAL-W2 to simulate water temperatures in Dworshak Reservoir. A long-term hydrologically based gridded data set of meteorological forcing provided the input for comparing model results with available observations of flow and water temperature. For purposes of investigating the impacts of climate change, we used the results from ten of the most recent Climate Model Intercomparison Project (CMIP5) climate change models scenarios in conjunction with the estimates of anthropogenic inputs of climate change gases from two representative concentration pathways (RCP). We compared the simulated results associated with a range of outcomes at critical river locations from the climate scenarios with existing conditions assuming that the reservoir would be operated under a rule curve based on the average reservoir elevation for the period 2006-2015 rule curve and for power demands represented by that same period.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC13H0761G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC13H0761G"><span>Persistent Cold Air Outbreaks over North America Under Climate Warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gao, Y.; Leung, L. R.; Lu, J.</p> <p>2014-12-01</p> <p>This study evaluates the change of cold air outbreaks (CAO) over North America using Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble of global climate simulations as well as regional high resolution climate simulations. In future, while robust decrease of CAO duration dominates in most of the North America, the decrease over northwestern U.S. was found to have much smaller magnitude than the surrounding regions. We found statistically significant increase of the sea level pressure over gulf of Alaska, leading to the advection of cold air to northwestern U.S.. By shifting the probability distribution of present temperature towards future warmer conditions, we identified the changes in large scale circulation contribute to about 50% of the enhanced sea level pressure. Using the high resolution regional climate model results, we found that increases of existing snowpack could potentially trigger the increase of CAO in the near future over the southwestern U.S. and Rocky Mountain through surface albedo effects. By the end of this century, the top 5 most extreme historical CAO events may still occur and wind chill warning will continue to have societal impacts over North America in particular over northwestern United States.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017GPC...148...96R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017GPC...148...96R"><span>Ensemble climate projections of mean and extreme rainfall over Vietnam</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Raghavan, S. V.; Vu, M. T.; Liong, S. Y.</p> <p>2017-01-01</p> <p>A systematic ensemble high resolution climate modelling study over Vietnam has been performed using the PRECIS model developed by the Hadley Center in UK. A 5 member subset of the 17-member Perturbed Physics Ensembles (PPE) of the Quantifying Uncertainty in Model Predictions (QUMP) project were simulated and analyzed. The PRECIS model simulations were conducted at a horizontal resolution of 25 km for the baseline period 1961-1990 and a future climate period 2061-2090 under scenario A1B. The results of model simulations show that the model was able to reproduce the mean state of climate over Vietnam when compared to observations. The annual cycles and seasonal averages of precipitation over different sub-regions of Vietnam show the ability of the model in also reproducing the observed peak and magnitude of monthly rainfall. The climate extremes of precipitation were also fairly well captured. Projections of future climate show both increases and decreases in the mean climate over different regions of Vietnam. The analyses of future extreme rainfall using the STARDEX precipitation indices show an increase in 90th percentile precipitation (P90p) over the northern provinces (15-25%) and central highland (5-10%) and over southern Vietnam (up to 5%). The total number of wet days (Prcp) indicates a decrease of about 5-10% all over Vietnam. Consequently, an increase in the wet day rainfall intensity (SDII), is likely inferring that the projected rainfall would be much more severe and intense which have the potential to cause flooding in some regions. Risks due to extreme drought also exist in other regions where the number of wet days decreases. In addition, the maximum 5 day consecutive rainfall (R5d) increases by 20-25% over northern Vietnam but decreases in a similar range over the central and southern Vietnam. These results have strong implications for the management water resources, agriculture, bio diversity and economy and serve as some useful findings to be considered by the policy makers within a wider range of climate uncertainties.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1395035-ensemble-based-parameter-estimation-coupled-gcm-using-adaptive-spatial-average-method','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1395035-ensemble-based-parameter-estimation-coupled-gcm-using-adaptive-spatial-average-method"><span>Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Liu, Y.; Liu, Z.; Zhang, S.; ...</p> <p>2014-05-29</p> <p>Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.H13A1050W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.H13A1050W"><span>Modeling groundwater quality in an arid agricultural environment in the face of an uncertain climate: the case of Mewat District, India</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Weber, M. C.; Ward, A. S.; Muste, M.</p> <p>2014-12-01</p> <p>The salinization of groundwater resources is a widespread problem in arid agricultural environments. In Mewat District (Haryana, India), groundwater salinity has rendered much of the accessible supply unfit for human consumption or agriculture. Historically, this closed basin retained fresh pockets of water at the foothills of the Aravalli Hills, where monsoonal precipitation runoff from the mountains was recharged through infiltration or facilitated by man-made structures. To date, an increasing number of pumps supply the region with fresh water for consumption and agriculture leading to shrinking the freshwater zone at an accelerated pace. The potential for increased human consumption corroborated with the effects of climate change bring uncertainty about the future of water security for the Mewat communities, most of them critically bound to the existence of local water. This study addresses the sustainability of the freshwater supply under a range of land interventions and climate scenarios, using a 2-D groundwater flow and transport model. Our results quantify potential futures for this arid, groundwater-dependent location, using numerical groundwater modeling to quantify interactions between human water use, infrastructure, and climate. Outcomes of this modeling study will inform an NGO active in the area on sustainable management of groundwater resources.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JAMES..10..245D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JAMES..10..245D"><span>Can We Use Single-Column Models for Understanding the Boundary Layer Cloud-Climate Feedback?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dal Gesso, S.; Neggers, R. A. J.</p> <p>2018-02-01</p> <p>This study explores how to drive Single-Column Models (SCMs) with existing data sets of General Circulation Model (GCM) outputs, with the aim of studying the boundary layer cloud response to climate change in the marine subtropical trade wind regime. The EC-EARTH SCM is driven with the large-scale tendencies and boundary conditions as derived from two different data sets, consisting of high-frequency outputs of GCM simulations. SCM simulations are performed near Barbados Cloud Observatory in the dry season (January-April), when fair-weather cumulus is the dominant low-cloud regime. This climate regime is characterized by a near equilibrium in the free troposphere between the long-wave radiative cooling and the large-scale advection of warm air. In the SCM, this equilibrium is ensured by scaling the monthly mean dynamical tendency of temperature and humidity such that it balances that of the model physics in the free troposphere. In this setup, the high-frequency variability in the forcing is maintained, and the boundary layer physics acts freely. This technique yields representative cloud amount and structure in the SCM for the current climate. Furthermore, the cloud response to a sea surface warming of 4 K as produced by the SCM is consistent with that of the forcing GCM.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4583544','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4583544"><span>Climate Change-Induced Range Expansion of a Subterranean Rodent: Implications for Rangeland Management in Qinghai-Tibetan Plateau</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Su, Junhu; Aryal, Achyut; Nan, Zhibiao; Ji, Weihong</p> <p>2015-01-01</p> <p>Disturbances, both human-induced and natural, may re-shape ecosystems by influencing their composition, structure, and functional processes. Plateau zokor (Eospalax baileyi) is a typical subterranean rodent endemic to Qinghai-Tibetan Plateau (QTP), which are considered ecosystem engineers influencing the alpine ecosystem function. It is also regarded as a pest aggravating the degradation of overgrazed grassland and subject to regular control in QTP since 1950s. Climate change has been predicted in this region but little research exists exploring its impact on such subterranean rodent populations. Using plateau zokor as a model, through maximum entropy niche-based modeling (Maxent) and sustainable habitat models, we investigate zokor habitat dynamics driven by the future climate scenarios. Our models project that zokor suitable habitat will increase by 6.25% in 2050 in QTP. The predication indicated more threats in terms of grassland degradation as zokor suitable habitat will increase in 2050. Distribution of zokors will shift much more in their southern range with lower elevation compare to northern range with higher elevation. The estimated distance of shift ranges from 1 km to 94 km from current distribution. Grassland management should take into account such predictions in order to design mitigation measures to prevent further grassland degradation in QTP under climate change scenarios. PMID:26406891</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910001143','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910001143"><span>The effects of cloud radiative forcing on an ocean-covered planet</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Randall, David A.</p> <p>1990-01-01</p> <p>Cumulus anvil clouds, whose importance has been emphasized by observationalists in recent years, exert a very powerful influence on deep tropical convection by tending to radiatively destabilize the troposphere. In addition, they radiatively warm the column in which they reside. Their strong influence on the simulated climate argues for a much more refined parameterization in the General Circulation Model (GCM). For Seaworld, the atmospheric cloud radiative forcing (ACRF) has a powerful influence on such basic climate parameters as the strength of the Hadley circulation, the existence of a single narrow InterTropical Convergence Zone (ITCZ), and the precipitable water content of the atmosphere. It seems likely, however, that in the real world the surface CRF feeds back negatively to suppress moist convection and the associated cloudiness, and so tends to counteract the effects of the ACRF. Many current climate models have fixed sea surface temperatures but variable land-surface temperatures. The tropical circulations of such models may experience a position feedback due to ACRF over the oceans, and a negative or weak feedback due to surface CRF over the land. The overall effects of the CRF on the climate system can only be firmly established through much further analysis, which can benefit greatly from the use of a coupled ocean-atmospheric model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMPP23E..06M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMPP23E..06M"><span>North Siberian Permafrost reveals Holocene Arctic Winter Warming</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meyer, H.; Opel, T.; Laepple, T.; Alexander, D.; Hoffmann, K.; Werner, M.</p> <p>2014-12-01</p> <p>The Arctic climate has experienced a major warming over the past decades, which is unprecedented in the last 2000 yrs. There are, however, still major uncertainties about the temperature evolution during the Holocene. Most proxy reconstructions suggest a cooling in mid-and late Holocene (e.g. Wanner, 2008), whereas climate model simulations show only weak changes or even a moderate warming (e.g. Lohmann et al., 2013). In this study, we used ice wedges as promising permafrost climate archive studied by stable water isotope methods. Ice wedges may be identified by vertically oriented foliations, and they form by the repeated filling of winter thermal contraction cracks by snow melt water in spring. Therefore, the isotopic composition of wedge ice may be attributed to the climate conditions of the cold season (i.e. winter and spring). 42 samples of organic material enclosed in ice wedges have been directly dated by Radiocarbon methods. Here, we present the first terrestrial stable oxygen isotope record of Holocene winter temperatures in up to centennial-scale resolution based on permafrost ice wedges (Lena River Delta; Siberian Arctic). The Lena ice-wedge record shows that the recent isotopic temperatures are the highest of the past 7000 years. Despite similarities to Arctic temperature reconstructions of the last two millennia (Kaufman et al., 2009), it suggests a winter warming throughout the mid and late Holocene, opposite to most existing other proxy records (Wanner, 2008). This apparent contradiction can be explained by the seasonality of the ice-wedge genesis in combination with orbital and greenhouse gas forcing and is consistent with climate model simulations. We conclude that the present model-data mismatch might be an artefact of the summer bias of the existing proxy records and thus, our record helps to reconcile the understanding of the northern hemisphere Holocene temperature evolution. This is particular true for the Russian Arctic significantly underrepresented in Arctic-wide climate reconstructions. Kaufman, D. S. et al. Science 325, 1236-1239 (2009).Wanner, H. et al. Quat. Sci. Rev. 27, 1791-1828, (2008).Lohmann, G., Pfeiffer, M., Laepple, T., Leduc, G. & Kim, J. H. Clim. Past 9, 1807-1839, (2013).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..533..250W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..533..250W"><span>Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron</p> <p>2016-02-01</p> <p>Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.9449A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.9449A"><span>Adaptation Strategies to Climate Change and the Role of Planning Instruments - The Example of the Dresden Region (Saxony/Germany)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Albrecht, J.; Juta, K.; Nobis, A.</p> <p>2009-04-01</p> <p>In the past, identifying anthropogenic influences on climate change, scenario analyses and issues of climate change mitigation were predominant approaches in climate change research (IPCC 2007). Currently, for instance in Germany, climate impact research on regional level comes to the forefront of research and policy making. Climate change has become an important topic on the agenda of politicians, administration and planning. In order to counteract the (unavoidable) climate change and its impacts it is necessary to develop adaptation strategies. At present, such strategies and guidelines are formulated on international, supranational and national level. The initial point was the United Nations Framework Convention on Climate Change in 1992 where the contracting states obligated themselves to develop national (and regional) programmes for adaptation. In 2007 the European Commission published its Green Paper called Adaptation to Climate Change in Europe. The paper states that adaptation efforts have to be intensified at different (spatial) levels (local, regional, national, and so forth). Furthermore, coordinating these efforts is of high importance. With the recent agreement on the German Adaptation Strategy to Climate Change (DAS 2008) in December 2008, federal government tries to accomplish this task. The German strategy mainly focuses on two elements: decreasing vulnerability and increasing adaptability. While the above mentioned strategies have presented information and policies concerning climate change and adaptation on international, supranational and national level, such documents dońt yet exist on regional level. However, because of their close link to the local level the regions are of high importance for adaptation strategies. Therefore, the Leibniz-Institute of Ecological and Regional Development developed a transdisciplinary project to formulate and implement the so-called Integrated Regional Climate Adaptation Programme (IRCAP) for the Model Region of Dresden (project REGKLAM). The REGKLAM-project is based on regionalised scenarios of climate change and includes measures of climate change adaptation to change for instance, urban form, infrastructure assets (e.g., reservoirs) and land use. Various institutions from politics, administration, economy, and research as well as civil society are involved in the project (the city of Dresden, several ministries and authorities of Saxony, the Dresden Chamber of Industry and Commerce and the University of Dresden). The IRCAP is planned to be an informal, cross-sectoral instrument of adaptation to climate change. As a regional programme, the IRCAP is addressed to decision-makers of the region of Dresden (defined, for instance, as planning region). Its function is to complement and coordinate existing instruments and measures. These instruments also include instruments of environmental and spatial planning on the regional level. Spatial and environmental planning can rely on a wide range of formal and informal instruments on different spatial, administrative, and sectoral levels, e.g. land use and landscape plans. Our contribution to the EGU conference aims to clear the role and relevance of the existing formal and informal planning instruments in the region of Dresden for the process of developing the IRCAP. Firstly, a survey is conducted for the purpose of identifying all relevant planning instruments. The identification process is based on specific criteria, for example: reference to the region, contents relating to the topic of climate change respectively climate adaptation. Secondly, the presentation argues for a selection of those planning instruments which seem to be most relevant for the process of developing an IRCAP. This selection process is based on specific criteria which include, for instance, complexity of expected effects, reference to regional and sectoral vulnerability, opportunity for future change of the existing planning instruments (e.g., current process of updating), interests of project partners and stakeholders. Thirdly, as a result, an overview of relevant planning instruments in the region of Dresden is shown, including their current status and statements about their relevance for the topic of climate adaptation strategies. Finally it is derived that this procedure provides a basis for the following possibilities: Adapting existing planning instruments, integrate contents of existing planning instruments in the IRCAP process, or develop and define new strategies or measures on the way to an IRCAP.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810017V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810017V"><span>A review on regional convection permitting climate modeling</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin</p> <p>2016-04-01</p> <p>With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4199630','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4199630"><span>Modeling the Evolution of Riparian Woodlands Facing Climate Change in Three European Rivers with Contrasting Flow Regimes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Rivaes, Rui P.; Rodríguez-González, Patricia M.; Ferreira, Maria Teresa; Pinheiro, António N.; Politti, Emilio; Egger, Gregory; García-Arias, Alicia; Francés, Felix</p> <p>2014-01-01</p> <p>Global circulation models forecasts indicate a future temperature and rainfall pattern modification worldwide. Such phenomena will become particularly evident in Europe where climate modifications could be more severe than the average change at the global level. As such, river flow regimes are expected to change, with resultant impacts on aquatic and riparian ecosystems. Riparian woodlands are among the most endangered ecosystems on earth and provide vital services to interconnected ecosystems and human societies. However, they have not been the object of many studies designed to spatially and temporally quantify how these ecosystems will react to climate change-induced flow regimes. Our goal was to assess the effects of climate-changed flow regimes on the existing riparian vegetation of three different European flow regimes. Cases studies were selected in the light of the most common watershed alimentation modes occurring across European regions, with the objective of appraising expected alterations in the riparian elements of fluvial systems due to climate change. Riparian vegetation modeling was performed using the CASiMiR-vegetation model, which bases its computation on the fluvial disturbance of the riparian patch mosaic. Modeling results show that riparian woodlands may undergo not only at least moderate changes for all flow regimes, but also some dramatic adjustments in specific areas of particular vegetation development stages. There are circumstances in which complete annihilation is feasible. Pluvial flow regimes, like the ones in southern European rivers, are those likely to experience more pronounced changes. Furthermore, regardless of the flow regime, younger and more water-dependent individuals are expected to be the most affected by climate change. PMID:25330151</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JHyd..560..202T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JHyd..560..202T"><span>Optimal Interpolation scheme to generate reference crop evapotranspiration</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tomas-Burguera, Miquel; Beguería, Santiago; Vicente-Serrano, Sergio; Maneta, Marco</p> <p>2018-05-01</p> <p>We used an Optimal Interpolation (OI) scheme to generate a reference crop evapotranspiration (ETo) grid, forcing meteorological variables, and their respective error variance in the Iberian Peninsula for the period 1989-2011. To perform the OI we used observational data from the Spanish Meteorological Agency (AEMET) and outputs from a physically-based climate model. To compute ETo we used five OI schemes to generate grids for the five observed climate variables necessary to compute ETo using the FAO-recommended form of the Penman-Monteith equation (FAO-PM). The granularity of the resulting grids are less sensitive to variations in the density and distribution of the observational network than those generated by other interpolation methods. This is because our implementation of the OI method uses a physically-based climate model as prior background information about the spatial distribution of the climatic variables, which is critical for under-observed regions. This provides temporal consistency in the spatial variability of the climatic fields. We also show that increases in the density and improvements in the distribution of the observational network reduces substantially the uncertainty of the climatic and ETo estimates. Finally, a sensitivity analysis of observational uncertainties and network densification suggests the existence of a trade-off between quantity and quality of observations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29712795','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29712795"><span>Transmission of climate risks across sectors and borders.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Challinor, Andy J; Adger, W Neil; Benton, Tim G; Conway, Declan; Joshi, Manoj; Frame, Dave</p> <p>2018-06-13</p> <p>Systemic climate risks, which result from the potential for cascading impacts through inter-related systems, pose particular challenges to risk assessment, especially when risks are transmitted across sectors and international boundaries. Most impacts of climate variability and change affect regions and jurisdictions in complex ways, and techniques for assessing this transmission of risk are still somewhat limited. Here, we begin to define new approaches to risk assessment that can account for transboundary and trans-sector risk transmission, by presenting: (i) a typology of risk transmission that distinguishes clearly the role of climate versus the role of the social and economic systems that distribute resources; (ii) a review of existing modelling, qualitative and systems-based methods of assessing risk and risk transmission; and (iii) case studies that examine risk transmission in human displacement, food, water and energy security. The case studies show that policies and institutions can attenuate risks significantly through cooperation that can be mutually beneficial to all parties. We conclude with some suggestions for assessment of complex risk transmission mechanisms: use of expert judgement; interactive scenario building; global systems science and big data; innovative use of climate and integrated assessment models; and methods to understand societal responses to climate risk. These approaches aim to inform both research and national-level risk assessment. © 2018 The Author(s).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018RSPTA.37670301C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018RSPTA.37670301C"><span>Transmission of climate risks across sectors and borders</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Challinor, Andy J.; Adger, W. Neil; Benton, Tim G.; Conway, Declan; Joshi, Manoj; Frame, Dave</p> <p>2018-06-01</p> <p>Systemic climate risks, which result from the potential for cascading impacts through inter-related systems, pose particular challenges to risk assessment, especially when risks are transmitted across sectors and international boundaries. Most impacts of climate variability and change affect regions and jurisdictions in complex ways, and techniques for assessing this transmission of risk are still somewhat limited. Here, we begin to define new approaches to risk assessment that can account for transboundary and trans-sector risk transmission, by presenting: (i) a typology of risk transmission that distinguishes clearly the role of climate versus the role of the social and economic systems that distribute resources; (ii) a review of existing modelling, qualitative and systems-based methods of assessing risk and risk transmission; and (iii) case studies that examine risk transmission in human displacement, food, water and energy security. The case studies show that policies and institutions can attenuate risks significantly through cooperation that can be mutually beneficial to all parties. We conclude with some suggestions for assessment of complex risk transmission mechanisms: use of expert judgement; interactive scenario building; global systems science and big data; innovative use of climate and integrated assessment models; and methods to understand societal responses to climate risk. These approaches aim to inform both research and national-level risk assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.B53F0739B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.B53F0739B"><span>Has climate change shifted US maize planting times?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Butler, E.; Stine, A.; Huybers, P.</p> <p>2012-12-01</p> <p>Global warming has been accompanied by an earlier onset of spring phenological events across a range of ecosystems. However, the degree to which humans have adapted planting schedules to a changing climate remains an open question; the leading hypotheses for earlier planting are improved hardiness of cultivars and farming equipment. Here we examine the relationship between historical temperature and precipitation from 549 weather stations from the United States Historical Climatology Network (USHCN) with planting schedules from 20 states in the United States Department of Agriculture/National Agriculture Statistics Service (USDA/NASS) database. We construct an empirical model to relate yearly weather conditions to predict planting dates and compare this to the spatial distribution of climate conditions and mean planting times. Evidence for a relationship between climate and planting schedules indicates that planting schedules for US maize have been adapted to yearly variations and overall changes in climatology. As one might expect, hotter temperatures lead to earlier plantings while greater precipitation leads to later planting. These findings serve to indicate extant adaptation between US farmers and climate change, and will aid in forecasting future shifts to planting schedules as climate continues to change. Furthermore, the statistical model should also be useful for estimating planting times for states and years for which records do not otherwise exist.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28250442','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28250442"><span>On the key role of droughts in the dynamics of summer fires in Mediterranean Europe.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Turco, Marco; von Hardenberg, Jost; AghaKouchak, Amir; Llasat, Maria Carmen; Provenzale, Antonello; Trigo, Ricardo M</p> <p>2017-03-06</p> <p>Summer fires frequently rage across Mediterranean Europe, often intensified by high temperatures and droughts. According to the state-of-the-art regional fire risk projections, in forthcoming decades climate effects are expected to become stronger and possibly overcome fire prevention efforts. However, significant uncertainties exist and the direct effect of climate change in regulating fuel moisture (e.g. warmer conditions increasing fuel dryness) could be counterbalanced by the indirect effects on fuel structure (e.g. warmer conditions limiting fuel amount), affecting the transition between climate-driven and fuel-limited fire regimes as temperatures increase. Here we analyse and model the impact of coincident drought and antecedent wet conditions (proxy for the climatic factor influencing total fuel and fine fuel structure) on the summer Burned Area (BA) across all eco-regions in Mediterranean Europe. This approach allows BA to be linked to the key drivers of fire in the region. We show a statistically significant relationship between fire and same-summer droughts in most regions, while antecedent climate conditions play a relatively minor role, except in few specific eco-regions. The presented models for individual eco-regions provide insights on the impacts of climate variability on BA, and appear to be promising for developing a seasonal forecast system supporting fire management strategies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013SJCE...21a...1P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013SJCE...21a...1P"><span>Developments in Climate and Soil Water Storage in the Locality of Poiplie</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pásztorová, Mária</p> <p>2013-03-01</p> <p>Climate change is one of the largest threats to the modern world. It is primarily experienced via changes and extreme weather events, including air temperature changes, the uneven distribution of precipitation and an increase in the alteration of torrential short-term precipitation and longer non-precipitation periods. However climate change is not only a change in the weather; it also has a much larger impact on an ecosystem. As a result of expected climate change, a lack of either surface water or groundwater could occur within wetlands; thus, the existence of wetlands and their flora and fauna could be threatened. This submitted work analyses the impact of climate change on the wetland ecosystems of Poiplie, which is situated in the south of Slovakia in the Ipeľ river basin. The area is an important wetland biotope with rare plant and animal species, which mainly live in open water areas, marshes, wet meadows and alluvial forests. To evaluate any climate change, the CGCM 3.1 model, two emission scenarios, the A2 emission scenario (pessimistic) and the B1 emission scenario (optimistic), were used within the regionalization. For simulating the soil water storage, which is one of the components of a soil water regime, the GLOBAL mathematical model was used.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1011064','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1011064"><span>Gregarious Convection and Radiative Feedbacks in Idealized Worlds</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2016-08-29</p> <p>exist neither on the globe nor within the cloud model. Since mesoscales impose great computational costs on atmosphere models, as well as inconven...Atmospheric Science, University of Miami, Miami, Florida, USA Abstract What role does convection play in cloud feedbacks? What role does convective... cloud fields depends systematically on global temperature, then convective organization could be a climate system feedback. How reconcilable and how</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.V43C3163M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.V43C3163M"><span>Reconciling the Observed and Modeled Southern Hemisphere Circulation Response to Volcanic Eruptions</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>McGraw, M. C.; Barnes, E. A.; Deser, C.</p> <p>2016-12-01</p> <p>Confusion exists regarding the tropospheric circulation response to volcanic eruptions, with models and observations seeming to disagree on the sign of the response. The forced Southern Hemisphere circulation response to the eruptions of Pinatubo and El Chichon is shown to be a robust positive annular mode, using over 200 ensemble members from 38 climate models. It is demonstrated that the models and observations are not at odds, but rather, internal climate variability is large and can overwhelm the forced response. It is further argued that the state of ENSO can at least partially explain the sign of the observed anomalies, and may account for the perceived discrepancy between model and observational studies. The eruptions of both El Chichon and Pinatubo occurred during El Nino events, and it is demonstrated that the SAM anomalies following volcanic eruptions are weaker during El Nino events compared to La Nina events.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29185661','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29185661"><span>Is U.S. climatic diversity well represented within the existing federal protection network?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A</p> <p></p> <p>Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27801532','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27801532"><span>Response of Sierra Nevada forests to projected climate-wildfire interactions.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liang, Shuang; Hurteau, Matthew D; Westerling, Anthony LeRoy</p> <p>2017-05-01</p> <p>Climate influences forests directly and indirectly through disturbance. The interaction of climate change and increasing area burned has the potential to alter forest composition and community assembly. However, the overall forest response is likely to be influenced by species-specific responses to environmental change and the scale of change in overstory species cover. In this study, we sought to quantify how projected changes in climate and large wildfire size would alter forest communities and carbon (C) dynamics, irrespective of competition from nontree species and potential changes in other fire regimes, across the Sierra Nevada, USA. We used a species-specific, spatially explicit forest landscape model (LANDIS-II) to evaluate forest response to climate-wildfire interactions under historical (baseline) climate and climate projections from three climate models (GFDL, CCSM3, and CNRM) forced by a medium-high emission scenario (A2) in combination with corresponding climate-specific large wildfire projections. By late century, we found modest changes in the spatial distribution of dominant species by biomass relative to baseline, but extensive changes in recruitment distribution. Although forest recruitment declined across much of the Sierra, we found that projected climate and wildfire favored the recruitment of more drought-tolerant species over less drought-tolerant species relative to baseline, and this change was greatest at mid-elevations. We also found that projected climate and wildfire decreased tree species richness across a large proportion of the study area and transitioned more area to a C source, which reduced landscape-level C sequestration potential. Our study, although a conservative estimate, suggests that by late century, forest community distributions may not change as intact units as predicted by biome-based modeling, but are likely to trend toward simplified community composition as communities gradually disaggregate and the least tolerant species are no longer able to establish. The potential exists for substantial community composition change and forest simplification beyond this century. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910748C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910748C"><span>Active learning innovative for the study of climatic variations in Sicily (Italy) and micro-climates in confined environments. Digitized construction of agro-meteorological laboratory and entrepreneurial development of methodical home automation systems</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crimi, Pietro</p> <p>2017-04-01</p> <p>In education to issues of environmental sustainability and the use of renewable energy resources, there are the existing laboratory teaching methodologies in Superior School "A. Volta" in Palermo (Italy) for acquisition, processing and control network of agro-meteorological data on the local area. This station was planned to allow students practical multidisciplinary learning experiences in the field of agro-meteorological applications. The School started a few months ago a project of MIUR (Italian Ministry of Education) that updates the lab through the most innovative digital technologies in the field of mechatronics, domotic and sustainable energy, that are supported by the latest needs of scientific-educational multimedia. It is an educational training that intends to implement a data collection center agro-meteorological on "digital platforms," informational purposes and applications, on current issues of climate changes and their consequences in Sicily (Italy). This active learning will interconnect the data collected from the station weather and climate of the school with those locally and regionally, with "weather-climatic patterns" correlations that are implemented in the Mediterranean area (International Program "GAW-Global Atmosphere Watch"). For this reason were enabled synergies with two major public scientific research and acquisition services-data disclosure (ENEA and SIAS-Agrometeorological Information Service, Sicily Region), both to energy efficiency of the School Station, both to support data and digital applications in GIS, with agro-meteorological services to companies operating in the agricultural and environmental sustainability, high consideration themes in European Programming. A branch of this training course is the entrepreneurship education, carried out by a few years in School with the development of "experimental models" for the creation of "innovation clusters" to make entrepreneurial experience since school, creating/managing mini-companies. In the European educational program (Erasmus + KA3) called "Innovation Cluster for Entrepreneurship Education (ICEE)", aimed at enhancing the students' creativity and entrepreneurship, one of the mini-companies, created by students at the Institute, has developed and produced with innovative software a prototype automated system, a mini-greenhouse powered by solar energy, capable of recreating the habitat suitable for house plants, through the automated control of numerous agricultural micro-climatic parameters. Creating multimedia systems such as web platforms, advanced software and app/QR-code for mobile devices, defines the most innovative tools in computer science outreach phases. This experimental approach incorporates the teaching methods that are defined by the curriculum of the "Liceo delle Scienze Applicate" that exists in the School, with the proposition of experimental models that besides being "learning models" can switch into "knowledge models" correlated with scientific and technical-scientific models that exist in the world of research. La Natura non distrugge, che per creare, e non crea, che per distruggere (Storia dell'Astronomia, 1813 - Giacomo Leopardi)</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1715318R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1715318R"><span>Visualization and Analysis of Climate Simulation Performance Data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg</p> <p>2015-04-01</p> <p>Visualization is the key process of transforming abstract (scientific) data into a graphical representation, to aid in the understanding of the information hidden within the data. Climate simulation data sets are typically quite large, time varying, and consist of many different variables sampled on an underlying grid. A large variety of climate models - and sub models - exist to simulate various aspects of the climate system. Generally, one is mainly interested in the physical variables produced by the simulation runs, but model developers are also interested in performance data measured along with these simulations. Climate simulation models are carefully developed complex software systems, designed to run in parallel on large HPC systems. An important goal thereby is to utilize the entire hardware as efficiently as possible, that is, to distribute the workload as even as possible among the individual components. This is a very challenging task, and detailed performance data, such as timings, cache misses etc. have to be used to locate and understand performance problems in order to optimize the model implementation. Furthermore, the correlation of performance data to the processes of the application and the sub-domains of the decomposed underlying grid is vital when addressing communication and load imbalance issues. High resolution climate simulations are carried out on tens to hundreds of thousands of cores, thus yielding a vast amount of profiling data, which cannot be analyzed without appropriate visualization techniques. This PICO presentation displays and discusses the ICON simulation model, which is jointly developed by the Max Planck Institute for Meteorology and the German Weather Service and in partnership with DKRZ. The visualization and analysis of the models performance data allows us to optimize and fine tune the model, as well as to understand its execution on the HPC system. We show and discuss our workflow, as well as present new ideas and solutions that greatly aided our understanding. The software employed is based on Avizo Green, ParaView and SimVis, as well as own developed software extensions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.4605M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.4605M"><span>Plant Nitrogen Uptake in Terrestrial Biogeochemical Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marti, Alejandro; Cox, Peter; Sitch, Stephen; Jones, Chris; Liddicoat, spencer</p> <p>2013-04-01</p> <p>Most terrestrial biogeochemical models featured in the last Intergovernmental Panel on Climate Change (IPPC) Assessment Report highlight the importance of the terrestrial Carbon sequestration and feedbacks between the terrestrial Carbon cycle and the climate system. However, these models have been criticized for overestimating predicted Carbon sequestration and its potential climate feedback when calculating the rate of future climate change because they do not account for the Carbon sequestration constraints caused by nutrient limitation, particularly Nitrogen (N). This is particularly relevant considering the existence of a substantial deficit of Nitrogen for plants in most areas of the world. To date, most climate models assume that plants have access to as much Nitrogen as needed, but ignore the nutrient requirements for new vegetation growth. Determining the natural demand and acquisition for Nitrogen and its associated resource optimization is key when accounting for the Carbon sequestration constrains caused by nutrient limitation. The few climate models that include C-N dynamics have illustrated that the stimulation of plant growth over the coming century may be two to three times smaller than previously predicted. This reduction in growth is partially offset by an increase in the availability of nutrients resulting from an accelerated rate of decomposition of dead plants and other organic matter that occurring with a rise in temperature. However, this offset does not counterbalance the reduced level of plant growth calculated by natural nutrient limitations. Additionally, Nitrogen limitation is also expected to become more pronounced in some ecosystems as atmospheric CO2 concentration increases; resulting in less new growth and higher atmospheric CO2 concentrations than originally expected. This study compares alternative models of plant N uptake as found in different terrestrial biogeochemical models against field measurements, and introduces a new N-uptake model to the Joint UK Land Environment Simulator (JULES).. Acknowledgements This work has been funded by the European Commission FP7-PEOPLE-ITN-2008 Marie Curie Action: "Greencycles II: FP7-PEOPLE-ITN-2008 Marie Curie Action: "Networks for Initial Training"</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4261715','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4261715"><span>Constructing a framework for risk analyses of climate change effects on the water budget of differently sloped vineyards with a numeric simulation using the Monte Carlo method coupled to a water balance model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Hofmann, Marco; Lux, Robert; Schultz, Hans R.</p> <p>2014-01-01</p> <p>Grapes for wine production are a highly climate sensitive crop and vineyard water budget is a decisive factor in quality formation. In order to conduct risk assessments for climate change effects in viticulture models are needed which can be applied to complete growing regions. We first modified an existing simplified geometric vineyard model of radiation interception and resulting water use to incorporate numerical Monte Carlo simulations and the physical aspects of radiation interactions between canopy and vineyard slope and azimuth. We then used four regional climate models to assess for possible effects on the water budget of selected vineyard sites up 2100. The model was developed to describe the partitioning of short-wave radiation between grapevine canopy and soil surface, respectively, green cover, necessary to calculate vineyard evapotranspiration. Soil water storage was allocated to two sub reservoirs. The model was adopted for steep slope vineyards based on coordinate transformation and validated against measurements of grapevine sap flow and soil water content determined down to 1.6 m depth at three different sites over 2 years. The results showed good agreement of modeled and observed soil water dynamics of vineyards with large variations in site specific soil water holding capacity (SWC) and viticultural management. Simulated sap flow was in overall good agreement with measured sap flow but site-specific responses of sap flow to potential evapotranspiration were observed. The analyses of climate change impacts on vineyard water budget demonstrated the importance of site-specific assessment due to natural variations in SWC. The improved model was capable of describing seasonal and site-specific dynamics in soil water content and could be used in an amended version to estimate changes in the water budget of entire grape growing areas due to evolving climatic changes. PMID:25540646</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20808442','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20808442"><span>Projected loss of a salamander diversity hotspot as a consequence of projected global climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Milanovich, Joseph R; Peterman, William E; Nibbelink, Nathan P; Maerz, John C</p> <p>2010-08-16</p> <p>Significant shifts in climate are considered a threat to plants and animals with significant physiological limitations and limited dispersal abilities. The southern Appalachian Mountains are a global hotspot for plethodontid salamander diversity. Plethodontids are lungless ectotherms, so their ecology is strongly governed by temperature and precipitation. Many plethodontid species in southern Appalachia exist in high elevation habitats that may be at or near their thermal maxima, and may also have limited dispersal abilities across warmer valley bottoms. We used a maximum-entropy approach (program Maxent) to model the suitable climatic habitat of 41 plethodontid salamander species inhabiting the Appalachian Highlands region (33 individual species and eight species included within two species complexes). We evaluated the relative change in suitable climatic habitat for these species in the Appalachian Highlands from the current climate to the years 2020, 2050, and 2080, using both the HADCM3 and the CGCM3 models, each under low and high CO(2) scenarios, and using two-model thresholds levels (relative suitability thresholds for determining suitable/unsuitable range), for a total of 8 scenarios per species. While models differed slightly, every scenario projected significant declines in suitable habitat within the Appalachian Highlands as early as 2020. Species with more southern ranges and with smaller ranges had larger projected habitat loss. Despite significant differences in projected precipitation changes to the region, projections did not differ significantly between global circulation models. CO(2) emissions scenario and model threshold had small effects on projected habitat loss by 2020, but did not affect longer-term projections. Results of this study indicate that choice of model threshold and CO(2) emissions scenario affect short-term projected shifts in climatic distributions of species; however, these factors and choice of global circulation model have relatively small affects on what is significant projected loss of habitat for many salamander species that currently occupy the Appalachian Highlands.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC41B0551B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC41B0551B"><span>Elk River Watershed - Flood Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barnes, C. C.; Byrne, J. M.; MacDonald, R. J.; Lewis, D.</p> <p>2014-12-01</p> <p>Flooding has the potential to cause significant impacts to economic activities as well as to disrupt or displace populations. Changing climate regimes such as extreme precipitation events increase flood vulnerability and put additional stresses on infrastructure. Potential flooding from just under 100 (2009 NPRI Reviewed Facility Data Release, Environment Canada) toxic tailings ponds located in Canada increase risk to human safety and the environment. One such geotechnical failure spilt billions of litres of toxic tailings into the Fraser River watershed, British Columbia, when a tailings pond dam breach occurred in August 2014. Damaged and washed out roadways cut access to essential services as seen by the extensive floods that occurred in Saskatchewan and Manitoba in July 2014, and in Southern Alberta in 2013. Recovery efforts from events such as these can be lengthy, and have substantial social and economic impacts both in loss of revenue and cost of repair. The objective of this study is to investigate existing conditions in the Elk River watershed and model potential future hydrological changes that can increase flood risk hazards. By analyzing existing hydrology, meteorology, land cover, land use, economic, and settlement patterns a baseline is established for existing conditions in the Elk River watershed. Coupling the Generate Earth Systems Science (GENESYS) high-resolution spatial hydrometeorological model with flood hazard analysis methodology, high-resolution flood vulnerability base line maps are created using historical climate conditions. Further work in 2015 will examine possible impacts for a range of climate change and land use change scenarios to define changes to future flood risk and vulnerability.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25914206','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25914206"><span>Quantifying surface albedo and other direct biogeophysical climate forcings of forestry activities.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bright, Ryan M; Zhao, Kaiguang; Jackson, Robert B; Cherubini, Francesco</p> <p>2015-09-01</p> <p>By altering fluxes of heat, momentum, and moisture exchanges between the land surface and atmosphere, forestry and other land-use activities affect climate. Although long recognized scientifically as being important, these so-called biogeophysical forcings are rarely included in climate policies for forestry and other land management projects due to the many challenges associated with their quantification. Here, we review the scientific literature in the fields of atmospheric science and terrestrial ecology in light of three main objectives: (i) to elucidate the challenges associated with quantifying biogeophysical climate forcings connected to land use and land management, with a focus on the forestry sector; (ii) to identify and describe scientific approaches and/or metrics facilitating the quantification and interpretation of direct biogeophysical climate forcings; and (iii) to identify and recommend research priorities that can help overcome the challenges of their attribution to specific land-use activities, bridging the knowledge gap between the climate modeling, forest ecology, and resource management communities. We find that ignoring surface biogeophysics may mislead climate mitigation policies, yet existing metrics are unlikely to be sufficient. Successful metrics ought to (i) include both radiative and nonradiative climate forcings; (ii) reconcile disparities between biogeophysical and biogeochemical forcings, and (iii) acknowledge trade-offs between global and local climate benefits. We call for more coordinated research among terrestrial ecologists, resource managers, and coupled climate modelers to harmonize datasets, refine analytical techniques, and corroborate and validate metrics that are more amenable to analyses at the scale of an individual site or region. © 2015 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1712180B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1712180B"><span>New challenges of the ARISE project</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Blanc, Elisabeth</p> <p>2015-04-01</p> <p>It has been robustly demonstrated that variations in the circulation of the middle atmosphere influence weather and climate throughout the troposphere all the way to the Earth's surface. A key part of the coupling between the troposphere and stratosphere occurs through the propagation and breaking of planetary-scale Rossby waves and gravity waves. Limited observation of the middle atmosphere and these waves in particular limits the ability to faithfully reproduce the dynamics of the middle atmosphere in numerical weather prediction and climate models. The ARISE project combines for the first time international networks with complementary technologies such as infrasound, lidar and airglow. This joint network provided advanced data products that started to be used as benchmarks for weather forecast models. The ARISE network also allows enhanced and detailed monitoring of other extreme events in the Earth system such as erupting volcanoes, magnetic storms, tornadoes and tropical thunderstorms. In order to improve the ability of the network to monitor atmospheric dynamics, ARISE proposes to extend i) the existing network coverage in Africa and the high latitudes, ii) the altitude range in the stratosphere and mesosphere, iii) the observation duration using routine observation modes, and to use complementary existing infrastructures and innovative instrumentations. Data will be collected over the long term to improve weather forecasting to monthly or seasonal timescales, to monitor atmospheric extreme events and climate change. ARISE focuses on the link between models and observations for future assimilation of data by operational weather forecasting models. Among the applications, ARISE2 proposes infrasound remote volcano monitoring to provide notifications to civil aviation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B21F2024S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B21F2024S"><span>Simulating topographic controls on the abundance of larch forest in eastern Siberia, and its consequences under changing climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sato, H.; Kobayashi, H.</p> <p>2017-12-01</p> <p>In eastern Siberia, larches (Larix spp.) often exist in pure stands, constructing the world's largest coniferous forest, of which changes can significantly affect the earth's albedo and the global carbon balance. Our previous studies tried to reconstruct this vegetation, aiming to forecast its structures and functions under changing climate (1, 2). In previous studies of simulating vegetation at large geographical scales, the examining area is divided into coarse grid cells such as 0.5 × 0.5 degree resolution, and topographical heterogeneities within each grid cell are just ignored. However, in Siberian larch area, which is located on the environmental edge of existence of forest ecosystem, abundance of larch trees largely depends on topographic condition at the scale of tens to hundreds meters. In our preliminary analysis, we found a quantitative pattern that topographic properties controls the abundance of larch forest via both drought and flooding stresses in eastern Siberia. We, therefore, refined the hydrological sub-model of our dynamic vegetation model SEIB-DGVM, and validated whether the modified model can reconstruct the pattern, examined its impact on the estimation of biomass and vegetation productivity under the current and forecasted future climatic conditions. -- References --1. Sato, H., et al. (2010). "Simulation study of the vegetation structure and function in eastern Siberian larch forests using the individual-based vegetation model SEIB-DGVM." Forest Ecology and Management 259(3): 301-311. 2. Sato, H., et al. (2016). "Endurance of larch forest ecosystems in eastern Siberia under warming trends." Ecology and Evolution</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010E%26PSL.298...57S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010E%26PSL.298...57S"><span>Modeling the influence of a reduced equator-to-pole sea surface temperature gradient on the distribution of water isotopes in the Early/Middle Eocene</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Speelman, Eveline N.; Sewall, Jacob O.; Noone, David; Huber, Matthew; von der Heydt, Anna; Damsté, Jaap Sinninghe; Reichart, Gert-Jan</p> <p>2010-09-01</p> <p>Proxy-based climate reconstructions suggest the existence of a strongly reduced equator-to-pole temperature gradient during the Azolla interval in the Early/Middle Eocene, compared to modern. Changes in the hydrological cycle, as a consequence of a reduced temperature gradient, are expected to be reflected in the isotopic composition of precipitation (δD, δ 18O). The interpretation of water isotopic records to quantitatively reconstruct past precipitation patterns is, however, hampered by a lack of detailed information on changes in their spatial and temporal distribution. Using the isotope-enabled version of the National Center for Atmospheric Research (NCAR) atmospheric general circulation model, Community Atmosphere Model v.3 (isoCAM3), relationships between water isotopes and past climates can be simulated. Here we examine the influence of an imposed reduced meridional sea surface temperature gradient on the spatial distribution of precipitation and its isotopic composition in an Early/Middle Eocene setting. As a result of the applied forcings, the Eocene simulation predicts the occurrence of less depleted high latitude precipitation, with δD values ranging only between 0 and -140‰ (compared to Present-day 0 to -300‰). Comparison with Early/Middle Eocene-age isotopic proxy data shows that the simulation accurately captures the main features of the spatial distribution of the isotopic composition of Early/Middle Eocene precipitation over land in conjunction with the aspects of the modeled Early/Middle Eocene climate. Hence, the included stable isotope module quantitatively supports the existence of a reduced meridional temperature gradient during this interval.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003EAEJA....13178A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003EAEJA....13178A"><span>Reliability of regional climate simulations</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.</p> <p>2003-04-01</p> <p>Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H33L..04Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H33L..04Z"><span>Water-ecosystem-economy nexus under human intervention and climate change: a study in the Heihe River Basin (China)</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zheng, Y.; Tian, Y.; Wu, X.; Feng, D.</p> <p>2017-12-01</p> <p>Recently, "One Belt and One Road" initiative, namely, building the "Silk Road Economic Belt" and "21st Century Maritime Silk Road", has become a global strategy of China and has been discussed as China's "Marshall Plan". The overland route of "One Belt" comes across vast arid lands, where the local population and ecosystem compete keenly for limited water resources. Water and environmental securities represent an important constraint of the "One Belt" development, and therefore understanding the complex water-ecosystem-economy nexus in the arid inland areas is very important. One typical case is Heihe River Basin (HRB), the second largest inland river basin of China, where the croplands in its middle part sucked up the river flow and groundwater, causing serious ecological problems in its lower part (Gobi Desert). We have developed an integrated hydrological-ecological model for the middle and lower HRB (the modeling domain has an area of 90,589 km2), which served as a platform to fuse multi-source data and provided a coherent understanding on the regional water cycle. With this physically based model, we quantitatively investigated how the nexus would be impacted by human intervention, mainly the existing and potential water regulations, and what would be the uncertainty of the nexus under the climate change. In studying the impact of human intervention, simulation-optimization analyses based on surrogate modeling were performed. In studying the uncertainty resulted from the climate change, outputs of multiple GCMs were downscaled for this river basin to drive ecohydrological simulations. Our studies have demonstrated the significant tradeoffs among the crop production in the middle HRB, the water and environmental securities of the middle HRB, and the ecological health of the lower HRB. The underlying mechanisms of the tradeoffs were also systematically addressed. The climate change would cause notable uncertainty of the nexus, which makes the water resources management more challenging. Overall, our studies suggest that the existing water allocation regulation in HRB could be improved if the complex nexus can be appropriately accounted for, and adaptive management is highly desired to cope with the uncertainty of future climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmEn.154..129L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmEn.154..129L"><span>Particulate matter air pollution in Europe in a +2 °C warming world</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lacressonnière, Gwendoline; Watson, Laura; Gauss, Michael; Engardt, Magnuz; Andersson, Camilla; Beekmann, Matthias; Colette, Augustin; Foret, Gilles; Josse, Béatrice; Marécal, Virginie; Nyiri, Agnes; Siour, Guillaume; Sobolowski, Stefan; Vautard, Robert</p> <p>2017-04-01</p> <p>In the framework of the IMPACT2C project, we have evaluated the future European particulate matter concentrations under the influence of climate change and anthropogenic emission reductions. To do so, 30-year simulations for present and future scenarios were performed with an ensemble of four regional Chemical Transport Models. +2 °C scenarios were issued from different regional climate simulations belonging to the CORDEX experiment (RCP4.5 scenario). Comparing present day simulations to observations shows that these simulations meet the requested quality criteria even if some biases do exist. Also, we showed that using regional climate models instead of meteorological reanalysis was not critical for the quality of our simulations. Present day as well as future scenarios show the large variability between models associated with different meteorology and process parameterizations. Future projections of PM concentrations show a large reduction of PM10 and PM2.5 concentrations in a +2 °C climate over the European continent (especially over Benelux), which can be mostly attributed to emission reduction policies. Under a current legislation scenario, annual PM10 could be reduced by between 1.8 and 2.9 μg m-3 (14.1-20.4%). If maximum technologically feasible emission reductions were implemented, further reductions of 1.4-1.9 μg m-3 (18.6-20.9%) are highlighted. Changes due to a +2 °C warming, in isolation from emission changes, are in general much weaker (-1.1 to +0.4 μg m-3,-0.3 to +5.1% for annual PM10 averaged over the European domain). Even if large differences exist between models, we have determined that the decrease of PM over Europe associated with emission reduction is a robust result. The patterns of PM changes resulting from climate change (for example the increase of PM over Spain and southern France and the decrease of PM10 over eastern Europe) are also robustly predicted even if its amplitude remains weak compared to changes associated with emission reductions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.tmp..176L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.tmp..176L"><span>Vertical climatic belts in the Tatra Mountains in the light of current climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Łupikasza, Ewa; Szypuła, Bartłomiej</p> <p>2018-04-01</p> <p>The paper discusses temporal changes in the configuration of vertical climatic belts in the Tatra Mountains as a result of current climate change. Meteorological stations are scarce in the Tatra Mountains; therefore, we modelled decadal air temperatures using existing data from 20 meteorological stations and the relationship between air temperature and altitude. Air temperature was modelled separately for northern and southern slopes and for convex and concave landforms. Decadal air temperatures were additionally used to delineate five climatic belts previously distinguished by Hess on the basis of threshold values of annual air temperature. The spatial extent and location of the borderline isotherms of 6, 4, 2, 0, and - 2 °C for four decades, including 1951-1960, 1981-1990, 1991-2000, and 2001-2010, were compared. Significant warming in the Tatra Mountains, uniform in the vertical profile, started at the beginning of the 1980s and led to clear changes in the extent and location of the vertical climatic belts delineated on the basis of annual air temperature. The uphill shift of the borderline isotherms was more prominent on southern than on northern slopes. The highest rate of changes in the extent of the climatic belts was found above the isotherm of 0 °C (moderately cold and cold belts). The cold belt dramatically diminished in extent over the research period.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A51E3089R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A51E3089R"><span>Precipitation Organization in a Warmer Climate</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rickenbach, T. M.; Nieto Ferreira, R.; Nissenbaum, M.</p> <p>2014-12-01</p> <p>This study will investigate changes in precipitation organization in a warmer climate using the Weather Research and Forecasting (WRF) model and CMIP-5 ensemble climate simulations. This work builds from an existing four-year NEXRAD radar-based precipitation climatology over the southeastern U.S. that uses a simple two-category framework of precipitation organization based on instantaneous precipitating feature size. The first category - mesoscale precipitation features (MPF) - dominates winter precipitation and is linked to the more predictable large-scale forcing provided by the extratropical cyclones. In contrast, the second category - isolated precipitation - dominates the summer season precipitation in the southern coastal and inland regions but is linked to less predictable mesoscale circulations and to local thermodynamics more crudely represented in climate models. Most climate modeling studies suggest that an accelerated water cycle in a warmer world will lead to an overall increase in precipitation, but few studies have addressed how precipitation organization may change regionally. To address this, WRF will simulate representative wintertime and summertime precipitation events in the Southeast US under the current and future climate. These events will be simulated in an environment resembling the future climate of the 2090s using the pseudo-global warming (PGW) approach based on an ensemble of temperature projections. The working hypothesis is that the higher water vapor content in the future simulation will result in an increase in the number of isolated convective systems, while MPFs will be more intense and longer-lasting. In the context of the seasonal climatology of MPF and isolated precipitation, these results have implications for assessing the predictability of future regional precipitation in the southeastern U.S.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70194465','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70194465"><span>Grand challenges in understanding the interplay of climate and land changes</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Liu, Shuguang; Bond-Lamberty, Ben; Boysen, Lena R.; Ford, James D.; Fox, Andrew; Gallo, Kevin; Hatfield, Jerry L.; Henebry, Geoffrey M.; Huntington, Thomas G.; Liu, Zhihua; Loveland, Thomas R.; Norby, Richard J.; Sohl, Terry L.; Steiner, Allison L.; Yuan, Wenping; Zhang, Zhao; Zhao, Shuqing</p> <p>2017-01-01</p> <p>Half of Earth’s land surface has been altered by human activities, creating various consequences on the climate and weather systems at local to global scales, which in turn affect a myriad of land surface processes and the adaptation behaviors. This study reviews the status and major knowledge gaps in the interactions of land and atmospheric changes and present 11 grand challenge areas for the scientific research and adaptation community in the coming decade. These land-cover and land-use change (LCLUC)-related areas include 1) impacts on weather and climate, 2) carbon and other biogeochemical cycles, 3) biospheric emissions, 4) the water cycle, 5) agriculture, 6) urbanization, 7) acclimation of biogeochemical processes to climate change, 8) plant migration, 9) land-use projections, 10) model and data uncertainties, and, finally, 11) adaptation strategies. Numerous studies have demonstrated the effects of LCLUC on local to global climate and weather systems, but these putative effects vary greatly in magnitude and even sign across space, time, and scale and thus remain highly uncertain. At the same time, many challenges exist toward improved understanding of the consequences of atmospheric and climate change on land process dynamics and services. Future effort must improve the understanding of the scale-dependent, multifaceted perturbations and feedbacks between land and climate changes in both reality and models. To this end, one critical cross-disciplinary need is to systematically quantify and better understand measurement and model uncertainties. Finally, LCLUC mitigation and adaptation assessments must be strengthened to identify implementation barriers, evaluate and prioritize opportunities, and examine how decision-making processes work in specific contexts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4154771','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4154771"><span>Incorporating Cold-Air Pooling into Downscaled Climate Models Increases Potential Refugia for Snow-Dependent Species within the Sierra Nevada Ecoregion, CA</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.</p> <p>2014-01-01</p> <p>We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist. PMID:25188379</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70123449','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70123449"><span>Incorporating cold-air pooling into downscaled climate models increases potential refugia for snow-dependent species within the Sierra Nevada Ecoregion, CA</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Curtis, Jennifer A.; Flint, Lorraine E.; Flint, Alan L.; Lundquist, Jessica D.; Hudgens, Brian; Boydston, Erin E.; Young, Julie K.</p> <p>2014-01-01</p> <p>We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.2943L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.2943L"><span>Uncertainties in assessing climate change impacts on the hydrology of Mediterranean basins</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ludwig, Ralf</p> <p>2013-04-01</p> <p>There is substantial evidence in historical and recent observations that the Mediterranean and neighboring regions are especially vulnerable to the impacts of climate change. Numerous climate projections, stemming from ensembles of global and regional climate models, agree on severe changes in the climate forcing which are likely to exacerbate subsequent ecological, economic and social impacts. Many of these causal connections are closely linked to the general expectation that water availability will decline in the already water-stressed basins of Africa, the Mediterranean region and the Near East, even though considerable regional variances must be expected. Consequently, climate change impacts on water resources are raising concerns regarding their possible management and security implications. Decreasing access to water resources and other related factors could be a cause or a 'multiplier' of tensions within and between countries. Whether security threats arise from climate impacts or options for cooperation evolve does not depend only on the severity of the impacts themselves, but on social, economic, and institutional vulnerabilities or resilience as well as factors that influence local, national and international relations. However, an assessment of vulnerability and risks hinges on natural, socio-economic, and political conditions and responses, all of which are uncertain. Multidisciplinary research is needed to tackle the multi-facet complexity of climate change impacts on water resources in the Mediterranean and neighboring countries. This is particularly true in a region of overall data scarcity and poor data management and exchange structures. The current potential to develop appropriate regional adaptation measures towards climate change impacts suffers heavily from large uncertainties. These spread along a long chain of components, starting from the definition of emission scenarios to global and regional climate modeling to impact models and a subsequent variety of management options and adaptation strategies. Therefore, the 4-year FP7-project CLIMB (Climate induced changes on the hydrology of Mediterranean basins, GA: 244151) includes a major focus on the assessment and quantification of uncertainties. First, CLIMB employs a rigorous climate change model analysis, auditing the Global and Regional Climate Model data available through the ENSEMBLES and PRUDENCE initiatives. The audits lead to select the best regional performers as compared to observed values during the climatic reference period (1971- 2000). Specific bias correction and downscaling procedures are applied to provide the driving inputs and meet the demands of the subsequent impact models, transferring a future climate signal (2041-2070) into hydrological quantities at the catchment or landscape scale. However, very limited quantitative knowledge is as yet available about the role of hydrological model complexity for climate change impact assessment, where predictive power becomes more and more important and raises the demand for process-based and spatially explicit model types. Thus, CLIMB uses hydrological model ensembles to analyze the performance of existing models and works to identify the appropriate level of model complexity, and thus to determine the data specifications required to provide robust results in a climate change context. The presentation focuses on the CLIMB multi-level strategy to uncertainty assessment and highlights latest findings in some of the seven CLIMB case studies. In particular, the presentation will demonstrate the current constraints of hydro-meteorological data availability and processing and searches for solutions that can eventually be provided by integrating hydro-meteorology and ICT research communities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA584110','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA584110"><span>Using Geographic Information Systems to Evaluate Energy Initiatives in Austere Environments</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-03-01</p> <p>conducting economic analysis of energy reduction initiatives. This research examined the energy savings potential of improving the thermal properties...shelter improvements in any climate and location in the world. Specifically, solar flies developed through Solar Integrated Power Shelter System...94 Improvements to the Existing Model</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43K1792G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43K1792G"><span>Determining the effect of key climate drivers on global hydropower production</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.</p> <p>2017-12-01</p> <p>Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1512904J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512904J"><span>A climate robust integrated modelling framework for regional impact assessment of climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Janssen, Gijs; Bakker, Alexander; van Ek, Remco; Groot, Annemarie; Kroes, Joop; Kuiper, Marijn; Schipper, Peter; van Walsum, Paul; Wamelink, Wieger; Mol, Janet</p> <p>2013-04-01</p> <p>Decision making towards climate proofing the water management of regional catchments can benefit greatly from the availability of a climate robust integrated modelling framework, capable of a consistent assessment of climate change impacts on the various interests present in the catchments. In the Netherlands, much effort has been devoted to developing state-of-the-art regional dynamic groundwater models with a very high spatial resolution (25x25 m2). Still, these models are not completely satisfactory to decision makers because the modelling concepts do not take into account feedbacks between meteorology, vegetation/crop growth, and hydrology. This introduces uncertainties in forecasting the effects of climate change on groundwater, surface water, agricultural yields, and development of groundwater dependent terrestrial ecosystems. These uncertainties add to the uncertainties about the predictions on climate change itself. In order to create an integrated, climate robust modelling framework, we coupled existing model codes on hydrology, agriculture and nature that are currently in use at the different research institutes in the Netherlands. The modelling framework consists of the model codes MODFLOW (groundwater flow), MetaSWAP (vadose zone), WOFOST (crop growth), SMART2-SUMO2 (soil-vegetation) and NTM3 (nature valuation). MODFLOW, MetaSWAP and WOFOST are coupled online (i.e. exchange information on time step basis). Thus, changes in meteorology and CO2-concentrations affect crop growth and feedbacks between crop growth, vadose zone water movement and groundwater recharge are accounted for. The model chain WOFOST-MetaSWAP-MODFLOW generates hydrological input for the ecological prediction model combination SMART2-SUMO2-NTM3. The modelling framework was used to support the regional water management decision making process in the 267 km2 Baakse Beek-Veengoot catchment in the east of the Netherlands. Computations were performed for regionalized 30-year climate change scenarios developed by KNMI for precipitation and reference evapotranspiration according to Penman-Monteith. Special focus in the project was on the role of uncertainty. How valid is the information that is generated by this modelling framework? What are the most important uncertainties of the input data, how do they affect the results of the model chain and how can the uncertainties of the data, results, and model concepts be quantified and communicated? Besides these technical issues, an important part of the study was devoted to the perception of stakeholders. Stakeholder analysis and additional working sessions yielded insight into how the models, their results and the uncertainties are perceived, how the modelling framework and results connect to the stakeholders' information demands and what kind of additional information is needed for adequate support on decision making.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20030091492','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20030091492"><span>A Numerical Climate Observing Network Design Study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stammer, Detlef</p> <p>2003-01-01</p> <p>This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682750','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3682750"><span>Towards a climate-dependent paradigm of ammonia emission and deposition</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Sutton, Mark A.; Reis, Stefan; Riddick, Stuart N.; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R.; Tang, Y. Sim; Braban, Christine F.; Vieno, Massimo; Dore, Anthony J.; Mitchell, Robert F.; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D.; Milford, Celia; Flechard, Chris R.; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F.; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J.; Pinder, Robert W.; Bash, Jesse O.; Walker, John T.; Simpson, David; Horváth, László; Misselbrook, Tom H.; Bleeker, Albert; Dentener, Frank; de Vries, Wim</p> <p>2013-01-01</p> <p>Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100. PMID:23713128</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23713128','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23713128"><span>Towards a climate-dependent paradigm of ammonia emission and deposition.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sutton, Mark A; Reis, Stefan; Riddick, Stuart N; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R; Tang, Y Sim; Braban, Christine F; Vieno, Massimo; Dore, Anthony J; Mitchell, Robert F; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D; Milford, Celia; Flechard, Chris R; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J; Pinder, Robert W; Bash, Jesse O; Walker, John T; Simpson, David; Horváth, László; Misselbrook, Tom H; Bleeker, Albert; Dentener, Frank; de Vries, Wim</p> <p>2013-07-05</p> <p>Existing descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016LatJP..53f..12K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016LatJP..53f..12K"><span>Introduction of Energy and Climate Mitigation Policy Issues in Energy - Environment Model of Latvia</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klavs, G.; Rekis, J.</p> <p>2016-12-01</p> <p>The present research is aimed at contributing to the Latvian national climate policy development by projecting total GHG emissions up to 2030, by evaluating the GHG emission reduction path in the non-ETS sector at different targets set for emissions reduction and by evaluating the obtained results within the context of the obligations defined by the EU 2030 policy framework for climate and energy. The method used in the research was bottom-up, linear programming optimisation model MARKAL code adapted as the MARKAL-Latvia model with improvements for perfecting the integrated assessment of climate policy. The modelling results in the baseline scenario, reflecting national economic development forecasts and comprising the existing GHG emissions reduction policies and measures, show that in 2030 emissions will increase by 19.1 % compared to 2005. GHG emissions stabilisation and reduction in 2030, compared to 2005, were researched in respective alternative scenarios. Detailed modelling and analysis of the Latvian situation according to the scenario of non-ETS sector GHG emissions stabilisation and reduction in 2030 compared to 2005 have revealed that to implement a cost effective strategy of GHG emissions reduction first of all a policy should be developed that ensures effective absorption of the available energy efficiency potential in all consumer sectors. The next group of emissions reduction measures includes all non-ETS sectors (industry, services, agriculture, transport, and waste management).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040090304&hterms=carbon+balance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcarbon%2Bbalance','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040090304&hterms=carbon+balance&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcarbon%2Bbalance"><span>Modelling the Phanerozoic carbon cycle and climate: constraints from the 87Sr/86Sr isotopic ratio of seawater</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Francois, L. M.; Walker, J. C.</p> <p>1992-01-01</p> <p>A numerical model describing the coupled evolution of the biogeochemical cycles of carbon, sulfur, calcium, magnesium, phosphorus, and strontium has been developed to describe the long-term changes of atmospheric carbon dioxide and climate during the Phanerozoic. The emphasis is on the effects of coupling the cycles of carbon and strontium. Various interpretations of the observed Phanerozoic history of the seawater 87Sr/86Sr ratio are investigated with the model. More specifically, the abilities of continental weathering, volcanism, and surface lithology in generating that signal are tested and compared. It is suggested that the observed fluctuations are mostly due to a changing weatherability over time. It is shown that such a conclusion is very important for the modelling of the carbon cycle. Indeed, it implies that the conventional belief that the evolution of atmospheric carbon dioxide and climate on a long time scale is governed by the balance between the volcanic input of CO2 and the rate of silicate weathering is not true. Rather carbon exchanges between the mantle and the exogenic system are likely to have played a key role too. Further, the increase of the global weathering rates with increasing surface temperature and/or atmospheric CO2 pressure usually postulated in long-term carbon cycle and climate modelling is also inconsistent with the new model. Other factors appear to have modulated the weatherability of the continents through time, such as mountain building and the existence of glaciers and ice sheets. Based on these observations, a history of atmospheric carbon dioxide and climate during Phanerozoic time, consistent with the strontium isotopic data, is reconstructed with the model and is shown to be compatible with paleoclimatic indicators, such as the timing of glaciation and the estimates of Cretaceous paleotemperatures.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMPP43A2309K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMPP43A2309K"><span>Testing the Millennial-Scale Holocene Solar-Climate Connection in the Indo-Pacific Warm Pool</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khider, D.; Emile-Geay, J.; McKay, N.; Jackson, C. S.; Routson, C.</p> <p>2016-12-01</p> <p>The existence of 1000 and 2500-year periodicities found in reconstructions of total solar irradiance (TSI) and a number of Holocene climate records has led to the hypothesis of a causal relationship. However, attributing Holocene millennial-scale variability to solar forcing requires a mechanism by which small changes in total irradiance can influence a global climate response. One possible amplifier within the climate system is the ocean. If this is the case, then we need to know more about where and how this may be occurring. On the other hand, the similarity in spectral peaks could be merely coincidental, and this should be made apparent by a lack of coherence in how that power and phasing are distributed in time and space. The plausibility of the solar forcing hypothesis is assessed through a Bayesian model of the age uncertainties affecting marine sedimentary records that is propagated through spectral analysis of the climate and forcing signals at key frequencies. Preliminary work on Mg/Ca and alkenone records from the Indo-Pacific Warm Pool suggests that despite large uncertainties in the location of the spectral peaks within each individual record arising from age model uncertainty, sea surface variability on timescales of 1025±36 years and 2427±133 years (±standard error of the mean of the median periodicity in each record) are present in at least 95% and 70% of the ensemble spectra, respectively. However, we find a long phase delay between the peak in forcing and the maximum response in at least one of the records, challenging the solar forcing hypothesis and requiring further investigation between low- and high-latitude signals. Remarkably, all records suggest a periodicity near 1470±85 years, reminiscent of the cycles characteristic of Marine Isotope Stage 3; these cycles are absent from existing records of TSI, further questioning the millennial solar-climate connection.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMPA13B..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMPA13B..04S"><span>Climate Contrarianism: Conspiracies, Movable Goalposts, Cherry Picking, and the Galileo Complex</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Somerville, R. C.</p> <p>2012-12-01</p> <p>How can two well-qualified climate scientists, with similar educational backgrounds and professional careers, come to diametrically opposed conclusions on important research issues that have been the subjects of extensive scientific investigation? This question is illuminated by examining the attitudes and practices that separate mainstream climate researchers and credentialed contrarian scientists. The existence of contrarians, scientists who reject the findings of mainstream researchers, is not confined to climate science. Indeed, in many fields of science, rhetorical arguments have been made by contrarians in order to create the impression that the expert scientific community is divided, and that genuine scientific controversy exists, where in fact there is none. The frequent objective underlying this practice is not to advance the science, but rather to cast doubt on scientific findings because of opposition to policies that might be implemented because of trust in these scientific results. Thus, opposition to cap-and-trade systems, or to carbon taxes, or to government interference with markets, or to ceding national sovereignty via treaties, can all be reasons for calling into question the mainstream scientific result that climate change due to human activities is real and has significant adverse effects. Contrarian scientists in many fields have alleged that they are victims of secretive conspiracies by mainstream scientists. They have also created unrealistic expectations of what research ought to provide, such as by pointing out that all climate models have uncertainties and weaknesses, and therefore no model results deserve serious consideration. They have emphasized weaknesses in papers supporting mainstream findings, and have exaggerated the importance of isolated results, and they have attacked the methods and credibility of mainstream scientists, all in the hope of undermining mainstream findings. They have often sought to portray themselves as independent thinkers and courageous victims of the dominant orthodoxy, reminiscent of Galileo. Understanding the characteristics of scientific contrarianism, and being familiar with its manifestations in many scientific fields, can help to recognize it and to distinguish it from legitimate scientific dissent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29158411','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29158411"><span>Holocene fluctuations in human population demonstrate repeated links to food production and climate.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bevan, Andrew; Colledge, Sue; Fuller, Dorian; Fyfe, Ralph; Shennan, Stephen; Stevens, Chris</p> <p>2017-12-05</p> <p>We consider the long-term relationship between human demography, food production, and Holocene climate via an archaeological radiocarbon date series of unprecedented sampling density and detail. There is striking consistency in the inferred human population dynamics across different regions of Britain and Ireland during the middle and later Holocene. Major cross-regional population downturns in population coincide with episodes of more abrupt change in North Atlantic climate and witness societal responses in food procurement as visible in directly dated plants and animals, often with moves toward hardier cereals, increased pastoralism, and/or gathered resources. For the Neolithic, this evidence questions existing models of wholly endogenous demographic boom-bust. For the wider Holocene, it demonstrates that climate-related disruptions have been quasi-periodic drivers of societal and subsistence change. Copyright © 2017 the Author(s). Published by PNAS.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC21A0713D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC21A0713D"><span>Nevada Infrastructure for Climate Change Science, Education, and Outreach</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dana, G. L.; Lancaster, N.; Mensing, S. A.; Piechota, T.</p> <p>2008-12-01</p> <p>The Great Basin is characterized by complex basin and range topography, arid to semiarid climate, and a history of sensitivity to climate change. Mountain areas comprise about 10% of the landscape, yet are the areas of highest precipitation and generate 85% of groundwater recharge and most surface runoff. These characteristics provide an ideal natural laboratory to study the effects of climate change. The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision "to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders." Six major strategies are proposed to develop infrastructure needs and attain our vision: 1) Develop a capability to model climate change at a regional and sub-regional scale(Climate Modeling Component) 2) Analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Assess effects on human systems and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Train teachers and students at all levels and provide public outreach in climate change issues (Education Component). Two new climate observational transects will be established across Great Basin Ranges, one anticipated on a mountain range in southern Nevada and the second to be located in north-central Nevada. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions key to understanding the effects of future climate change on Great Basin mountain ecosystems and the potential management strategies for responding to these changes: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems? Infrastructure developed through this project will provide new interdisciplinary capability to detect, analyze, and model effects of regional climate change in mountainous regions of the west and provide a major contribution to existing climate change research and monitoring networks.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27490439','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27490439"><span>Informing climate models with rapid chamber measurements of forest carbon uptake.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Metcalfe, Daniel B; Ricciuto, Daniel; Palmroth, Sari; Campbell, Catherine; Hurry, Vaughan; Mao, Jiafu; Keel, Sonja G; Linder, Sune; Shi, Xiaoying; Näsholm, Torgny; Ohlsson, Klas E A; Blackburn, M; Thornton, Peter E; Oren, Ram</p> <p>2017-05-01</p> <p>Models predicting ecosystem carbon dioxide (CO 2 ) exchange under future climate change rely on relatively few real-world tests of their assumptions and outputs. Here, we demonstrate a rapid and cost-effective method to estimate CO 2 exchange from intact vegetation patches under varying atmospheric CO 2 concentrations . We find that net ecosystem CO 2 uptake (NEE) in a boreal forest rose linearly by 4.7 ± 0.2% of the current ambient rate for every 10 ppm CO 2 increase, with no detectable influence of foliar biomass, season, or nitrogen (N) fertilization. The lack of any clear short-term NEE response to fertilization in such an N-limited system is inconsistent with the instantaneous downregulation of photosynthesis formalized in many global models. Incorporating an alternative mechanism with considerable empirical support - diversion of excess carbon to storage compounds - into an existing earth system model brings the model output into closer agreement with our field measurements. A global simulation incorporating this modified model reduces a long-standing mismatch between the modeled and observed seasonal amplitude of atmospheric CO 2 . Wider application of this chamber approach would provide critical data needed to further improve modeled projections of biosphere-atmosphere CO 2 exchange in a changing climate. © 2016 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70192624','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70192624"><span>Do we need demographic data to forecast plant population dynamics?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Tredennick, Andrew T.; Hooten, Mevin B.; Adler, Peter B.</p> <p>2017-01-01</p> <p>Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts.Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction.In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types.In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMED13C0944O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMED13C0944O"><span>Development of a Permafrost Modeling Cyberinfrastructure</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Overeem, I.; Jafarov, E. E.; Piper, M.; Schaefer, K. M.</p> <p>2016-12-01</p> <p>Permafrost is seen as an essential Arctic climate indicator, and feedback of thawing permafrost to the global climate system through the impacts on the global carbon cycle remain an important research topic. Observations can assess the current state of permafrost, but models are eventually essential to make predictions of future permafrost extent. The purpose of our project, which we call PermaModel, is to develop an easy-to-access and comprehensive cyberinfrastructure aimed at promoting and improving permafrost modeling. The PermaModel Integrated Modeling Toolbox (IMT) includes three permafrost models of increasing complexity. The IMT will be housed within the existing cyberinfrastructure of the Community Surface Dynamics Modeling System (CSDMS), and made publically accessible through the CSDMS Web Modeling Tool (WMT). The WMT will provide easy online access to students, scientists, and stakeholders who want to use permafrost models, but lack the expertise. We plan to include multiple sets of sample inputs, representing a variety of conditions and locations, to enable immediate use of the IMT. We present here the first permafrost model, which is envisioned to be the most suitable for teaching purposes. The model promotes understanding of a 1D heat equation and permafrost active layer dynamics under monthly temperature/climate drivers in an online environment. Modeling labs are presented through the CSDMS Educational Repository and we solicit feedback from faculty for further design of these resources.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70022274','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70022274"><span>Simulated influences of Lake Agassiz on the climate of central North America 11,000 years ago</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Hostetler, S.W.; Bartlein, P.J.; Clark, P.U.; Small, E.E.; Solomon, A.M.</p> <p>2000-01-01</p> <p>Eleven thousand years ago, large lakes existed in central and eastern North America along the margin of the Laurentide Ice Sheet. The large-scale North American climate at this time has been simulated with atmospheric general circulation models, but these relatively coarse global models do not resolve potentially important features of the mesoscale circulation that arise from interactions among the atmosphere, ice sheet, and proglacial lakes. Here we present simulations of the climate of central and eastern North America 11,000 years ago with a high-resolution, regional climate model nested within a general circulation model. The simulated climate is in general agreement with that inferred from palaeoecological evidence. Our experiments indicate that through mesoscale atmospheric feedbacks, the annual delivery of moisture to the Laurentide Ice Sheet was diminished at times of a large, cold Lake Agassiz relative to periods of lower lake stands. The resulting changes in the mass balance of the ice sheet may have contributed to fluctuations of the ice margin, thus affecting the routing of fresh water to the North Atlantic Ocean. A retreating ice margin during periods of high lake level may have opened an outlet for discharge of Lake Agassiz into the North Atlantic. A subsequent advance of the ice margin due to greater moisture delivery associated with a low lake level could have dammed the outlet, thereby reducing discharge to the North Atlantic. These variations may have been decisive in causing the Younger Dryas cold even.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFM.U41D0036C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFM.U41D0036C"><span>Physical-Socio-Economic Modeling of Climate Change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chamberlain, R. G.; Vatan, F.</p> <p>2008-12-01</p> <p>Because of the global nature of climate change, any assessment of the effects of plans, policies, and response to climate change demands a model that encompasses the entire Earth System, including socio- economic factors. Physics-based climate models of the factors that drive global temperatures, rainfall patterns, and sea level are necessary but not sufficient to guide decision making. Actions taken by farmers, industrialists, environmentalists, politicians, and other policy makers may result in large changes to economic factors, international relations, food production, disease vectors, and beyond. These consequences will not be felt uniformly around the globe or even across a given region. Policy models must comprehend all of these considerations. Combining physics-based models of the Earth's climate and biosphere with societal models of population dynamics, economics, and politics is a grand challenge with high stakes. We propose to leverage our recent advances in modeling and simulation of military stability and reconstruction operations to models that address all these areas of concern. Following over twenty years' experience of successful combat simulation, JPL has started developing Minerva, which will add demographic, economic, political, and media/information models to capabilities that already exist. With these new models, for which we have design concepts, it will be possible to address a very wide range of potential national and international problems that were previously inaccessible. Our climate change model builds on Minerva and expands the geographical horizon from playboxes containing regions and neighborhoods to the entire globe. This system consists of a collection of interacting simulation models that specialize in different aspects of the global situation. They will each contribute to and draw from a pool of shared data. The basic models are: the physical model; the demographic model; the political model; the economic model; and the media/information operations model. Each of these models focuses on part of the overall picture while; each contributes information about its area of expertise to a common pool and draws from that pool and the feedbacks from the other models as needed. Existing high-quality physical models are based on analysis of the dynamic interactions of atmospheric, land, and ocean processes. The demographic model tracks the civilian demographics needed by the other models. The populations of neighborhood group age-gender cohorts are affected by births, deaths, aging, and migration. This model provides labor supply and product demand curves to the economic model. The political model focuses on political actors and describes how they use their clout to seek their goals. Clout is derived from civilian support, the formal and informal alliances that actors make with each other, military strength, wealth, and control of information. It considers how they are constrained by their cultural heritage. It deals with shifting alliances. The economic model determines local and international prices and production quantities for a small number of products, including imports and exports and black markets; wages, jobs, and unemployment for a small number of labor categories; capital, growth, and inflation; resource usage and pollution. The media/information operations model addresses the effects of the control and content of inter- group and intra-group communications-and the side effects of these on other groups. This model will consist of rules (probably a large number of them) detailing the effects of media/information operations of various kinds on civilian parameters used in the other models, such as political goals, concern saliencies, and shapes of supply and demand curves.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUFMGC43C0756B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUFMGC43C0756B"><span>Climate Change in Colorado: Findings and Scientific Challenges</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Barsugli, J.; Ray, A.; Averyt, K.; Wolter, K.; Hoerling, M. P.</p> <p>2008-12-01</p> <p>In response to the risks associated with anthropogenic climate change, Governor Ritter issued the Colorado Climate Action Plan (CCAP) in 2007. In support of the adaptation component of the CCAP, the Colorado Water Conservation Board commissioned the Western Water Assessment at the University of Colorado to prepare the report "Climate Change in Colorado: A Synthesis to Support Water Resources Management and Adaptation." The objective of "Climate Change in Colorado" is to communicate the state of the science regarding the physical aspects of climate change that are important for evaluating impacts on Colorado's water resources. Accordingly, the document focuses on observed trends, modeling, attribution, and projections of hydroclimatic variables that are important for Colorado's water supply. Although many published datasets include information about Colorado, there are few climate studies that focus on the state. Consequently, many important analyses for Colorado are lacking. The report summarizes Colorado-specific findings from peer-reviewed regional studies, and presents new analyses derived from existing datasets. Here we will summarize the findings of the report, discuss the extent to which conclusions from West-wide studies hold in Colorado, and highlight the many scientific challenges that were faced in the preparation of the report. These challenges include interpreting observed and projected precipitation and temperature variability and trends, dealing with attribution and uncertainty at the state level, and justifying the relevance of climate model projections in a topographically complex state. A second presentation (Ray et al.) discusses the process of developing the report.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27557093','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27557093"><span>Climate Change and Future Pollen Allergy in Europe.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lake, Iain R; Jones, Natalia R; Agnew, Maureen; Goodess, Clare M; Giorgi, Filippo; Hamaoui-Laguel, Lynda; Semenov, Mikhail A; Solomon, Fabien; Storkey, Jonathan; Vautard, Robert; Epstein, Michelle M</p> <p>2017-03-01</p> <p>Globally, pollen allergy is a major public health problem, but a fundamental unknown is the likely impact of climate change. To our knowledge, this is the first study to quantify the consequences of climate change upon pollen allergy in humans. We produced quantitative estimates of the potential impact of climate change upon pollen allergy in humans, focusing upon common ragweed ( Ambrosia artemisiifolia ) in Europe. A process-based model estimated the change in ragweed's range under climate change. A second model simulated current and future ragweed pollen levels. These findings were translated into health burdens using a dose-response curve generated from a systematic review and from current and future population data. Models considered two different suites of regional climate/pollen models, two greenhouse gas emissions scenarios [Representative Concentration Pathways (RCPs) 4.5 and 8.5], and three different plant invasion scenarios. Our primary estimates indicated that sensitization to ragweed will more than double in Europe, from 33 to 77 million people, by 2041-2060. According to our projections, sensitization will increase in countries with an existing ragweed problem (e.g., Hungary, the Balkans), but the greatest proportional increases will occur where sensitization is uncommon (e.g., Germany, Poland, France). Higher pollen concentrations and a longer pollen season may also increase the severity of symptoms. Our model projections were driven predominantly by changes in climate (66%) but were also influenced by current trends in the spread of this invasive plant species. Assumptions about the rate at which ragweed spreads throughout Europe had a large influence upon the results. Our quantitative estimates indicate that ragweed pollen allergy will become a common health problem across Europe, expanding into areas where it is currently uncommon. Control of ragweed spread may be an important adaptation strategy in response to climate change. Citation: Lake IR, Jones NR, Agnew M, Goodess CM, Giorgi F, Hamaoui-Laguel L, Semenov MA, Solomon F, Storkey J, Vautard R, Epstein MM. 2017. Climate change and future pollen allergy in Europe. Environ Health Perspect 125:385-391; http://dx.doi.org/10.1289/EHP173.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015GMDD....8.4851M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015GMDD....8.4851M"><span>Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Melton, J. R.; Arora, V. K.</p> <p>2015-06-01</p> <p>The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016GMD.....9..323M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016GMD.....9..323M"><span>Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Melton, J. R.; Arora, V. K.</p> <p>2016-01-01</p> <p>The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC43F1123D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC43F1123D"><span>Regional warming of hot extremes accelerated by surface energy fluxes consistent with drying soils</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Donat, M.; Pitman, A.; Seneviratne, S. I.</p> <p>2017-12-01</p> <p>Strong regional differences exist in how hot temperature extremes increase under global warming. Using an ensemble of coupled climate models, we examine the regional warming rates of hot extremes relative to annual average warming rates in the same regions. We identify hotspots of accelerated warming of model-simulated hot extremes in Europe, North America, South America and Southeast China. These hotspots indicate where the warm tail of a distribution of temperatures increases faster than the average and are robust across most CMIP5 models. Exploring the conditions on the specific day the hot extreme occurs demonstrates the hotspots are explained by changes in the surface energy fluxes consistent with drying soils. Furthermore, in these hotspot regions we find a relationship between the temperature - heat flux correlation under current climate conditions and the magnitude of future projected changes in hot extremes, pointing to a potential emergent constraint for simulations of future hot extremes. However, the model-simulated accelerated warming of hot extremes appears inconsistent with observations of the past 60 years, except over Europe. The simulated acceleration of hot extremes may therefore be unreliable, a result that necessitates a re-evaluation of how climate models resolve the relevant terrestrial processes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ThApC.124.1079F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ThApC.124.1079F"><span>Westerly jet stream and past millennium climate change in Arid Central Asia simulated by COSMO-CLM model</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fallah, Bijan; Sodoudi, Sahar; Cubasch, Ulrich</p> <p>2016-05-01</p> <p>This study tackles one of the most debated questions around the evolution of Central Asian climate: the "Puzzle" of moisture changes in Arid Central Asia (ACA) throughout the past millennium. A state-of-the-art Regional Climate Model (RCM) is subsequently employed to investigate four different 31-year time slices of extreme dry and wet spells, chosen according to changes in the driving data, in order to analyse the spatio-temporal evolution of the moisture variability in two different climatological epochs: Medieval Climate Anomaly (MCA) and Little Ice Age (LIA). There is a clear regime behavior and bimodality in the westerly Jet phase space throughout the past millennium in ACA. The results indicate that the regime changes during LIA show a moist ACA and a dry East China. During the MCA, the Kazakhstan region shows a stronger response to the westerly jet equatorward shift than during the LIA. The out-of-phase pattern of moisture changes between India and ACA exists during both the LIA and the MCA. However, the pattern is more pronounced during the LIA.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H21I1499R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H21I1499R"><span>Long Term Ground Based Precipitation Data Analysis in California's 7 Climate Divisions: Spatial and Temporal Variability</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rodriguez, L.; El-Askary, H. M.; Rakovski, C.; Allai, M.</p> <p>2015-12-01</p> <p>California is an area of diverse topography and has what many scientists call a Mediterranean climate. Various precipitation patterns exist due to El Niño Southern Oscillation (ENSO) which can cause abnormal precipitation or droughts. As temperature increases mainly due to the increase of CO2 in the atmosphere, it is rapidly changing the climate of not only California but the world. An increase in temperature is leading to droughts in certain areas as other areas are experiencing heavy rainfall/flooding. Droughts in return are providing a foundation for fires harming the ecosystem and nearby population. Various natural hazards can be induced due to the coupling effects from inconsistent precipitation patterns and vice versa. Using wavelets and ARIMA modeling, we were able to identify anomalies of high precipitation and droughts within California's 7 climate divisions using NOAA's hourly precipitation data from rain gauges and compared the results with modeled data, SOI, PDO, and AMO. The identification of anomalies can be used to compare and correct remote sensing measurements of precipitation and droughts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017QSRv..174...63G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017QSRv..174...63G"><span>A modern pollen-climate dataset from the Darjeeling area, eastern Himalaya: Assessing its potential for past climate reconstruction</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ghosh, Ruby; Bruch, Angela A.; Portmann, Felix; Bera, Subir; Paruya, Dipak Kumar; Morthekai, P.; Ali, Sheikh Nawaz</p> <p>2017-10-01</p> <p>Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130-3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman-Olff-Fresco (HOF) models. A series of pollen-climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.7093T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.7093T"><span>Resilience, rapid transitions and regime shifts: fingerprinting the responses of Lake Żabińskie (NE Poland) to climate variability and human disturbance since 1000 AD</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tylmann, Wojciech; Hernández-Almeida, Iván; Grosjean, Martin; José Gómez Navarro, Juan; Larocque-Tobler, Isabelle; Bonk, Alicja; Enters, Dirk; Ustrzycka, Alicja; Piotrowska, Natalia; Przybylak, Rajmund; Wacnik, Agnieszka; Witak, Małgorzata</p> <p>2016-04-01</p> <p>Rapid ecosystem transitions and adverse effects on ecosystem services as responses to combined climate and human impacts are of major concern. Yet few quantitative observational data exist, particularly for ecosystems that have a long history of human intervention. Here, we combine quantitative summer and winter climate reconstructions, climate model simulations and proxies for three major environmental pressures (land use, nutrients and erosion) to explore the system dynamics, resilience, and the role of disturbance regimes in varved eutrophic Lake Żabińskie since AD 1000. Comparison between regional and global climate simulations and quantitative climate reconstructions indicate that proxy data capture noticeably natural forced climate variability, while internal variability appears as the dominant source of climate variability in the climate model simulations during most parts of the last millennium. Using different multivariate analyses and change point detection techniques, we identify ecosystem changes through time and shifts between rather stable states and highly variable ones, as expressed by the proxies for land-use, erosion and productivity in the lake. Prior to AD 1600, the lake ecosystem was characterized by a high stability and resilience against considerable observed natural climate variability. In contrast, lake-ecosystem conditions started to fluctuate at high frequency across a broad range of states after AD 1600. The period AD 1748-1868 represents the phase with the strongest human disturbance of the ecosystem. Analyses of the frequency of change points in the multi-proxy dataset suggests that the last 400 years were highly variable and flickering with increasing vulnerability of the ecosystem to the combined effects of climate variability and anthropogenic disturbances. This led to significant rapid ecosystem transformations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PrOce.152...15T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PrOce.152...15T"><span>Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.</p> <p>2017-03-01</p> <p>Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70027790','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70027790"><span>Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099 *</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.</p> <p>2004-01-01</p> <p>Hydrologic responses of river basins in the Sierra Nevada of California to historical and future climate variations and changes are assessed by simulating daily streamflow and water-balance responses to simulated climate variations over a continuous 200-yr period. The coupled atmosphere-ocean-ice-land Parallel Climate Model provides the simulated climate histories, and existing hydrologic models of the Merced, Carson, and American Rivers are used to simulate the basin responses. The historical simulations yield stationary climate and hydrologic variations through the first part of the 20th century until about 1975 when temperatures begin to warm noticeably and when snowmelt and streamflow peaks begin to occur progressively earlier within the seasonal cycle. A future climate simulated with business-as-usual increases in greenhouse-gas and aerosol radiative forcings continues those recent trends through the 21st century with an attendant +2.5??C warming and a hastening of snowmelt and streamflow within the seasonal cycle by almost a month. The various projected trends in the business-as-usual simulations become readily visible despite realistic simulated natural climatic and hydrologic variability by about 2025. In contrast to these changes that are mostly associated with streamflow timing, long-term average totals of streamflow and other hydrologic fluxes remain similar to the historical mean in all three simulations. A control simulation in which radiative forcings are held constant at 1995 levels for the 50 years following 1995 yields climate and streamflow timing conditions much like the 1980s and 1990s throughout its duration. The availability of continuous climate-change projection outputs and careful design of initial conditions and control experiments, like those utilized here, promise to improve the quality and usability of future climate-change impact assessments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf','USGSPUBS'); return false;" href="https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf"><span>Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Wood, Tamara M.; Wherry, Susan A.; Piccolroaz, Sebastiano; Girdner, Scott F</p> <p>2016-05-04</p> <p>The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21539736','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21539736"><span>Current models broadly neglect specific needs of biodiversity conservation in protected areas under climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sieck, Mungla; Ibisch, Pierre L; Moloney, Kirk A; Jeltsch, Florian</p> <p>2011-05-03</p> <p>Protected areas are the most common and important instrument for the conservation of biological diversity and are called for under the United Nations' Convention on Biological Diversity. Growing human population densities, intensified land-use, invasive species and increasing habitat fragmentation threaten ecosystems worldwide and protected areas are often the only refuge for endangered species. Climate change is posing an additional threat that may also impact ecosystems currently under protection. Therefore, it is of crucial importance to include the potential impact of climate change when designing future nature conservation strategies and implementing protected area management. This approach would go beyond reactive crisis management and, by necessity, would include anticipatory risk assessments. One avenue for doing so is being provided by simulation models that take advantage of the increase in computing capacity and performance that has occurred over the last two decades.Here we review the literature to determine the state-of-the-art in modeling terrestrial protected areas under climate change, with the aim of evaluating and detecting trends and gaps in the current approaches being employed, as well as to provide a useful overview and guidelines for future research. Most studies apply statistical, bioclimatic envelope models and focus primarily on plant species as compared to other taxa. Very few studies utilize a mechanistic, process-based approach and none examine biotic interactions like predation and competition. Important factors like land-use, habitat fragmentation, invasion and dispersal are rarely incorporated, restricting the informative value of the resulting predictions considerably. The general impression that emerges is that biodiversity conservation in protected areas could benefit from the application of modern modeling approaches to a greater extent than is currently reflected in the scientific literature. It is particularly true that existing models have been underutilized in testing different management options under climate change. Based on these findings we suggest a strategic framework for more effectively incorporating the impact of climate change in models exploring the effectiveness of protected areas.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUOSPC44B2208R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUOSPC44B2208R"><span>Constraints on Oceanic Meridional Transport of Heat and Carbon from Combined Oceanic and Atmospheric Measurements.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Resplandy, L.; Keeling, R. F.; Stephens, B. B.; Bent, J. D.; Jacobson, A. R.; Rödenbeck, C.; Khatiwala, S.</p> <p>2016-02-01</p> <p>The global ocean transports heat northward. The magnitude of this asymmetry between the two hemispheres is a key factor of the climate system through the displacement of tropical precipitation north of the equator and its influence on Arctic temperature and sea-ice extent. These asymmetric influences on heat are however not well constrained by observations or models. We identify a robust link between the ocean heat asymmetry and the large-scale distribution in atmospheric oxygen, using both atmospheric and oceanic observations and a suite of models (oceanic, climate and inverse). Novel aircraft observations from the pole-to-pole HIPPO campaign reveal that the ocean northward heat transport necessary to explain the atmospheric oxygen distribution is in the upper range of previous estimates from hydrographic sections and atmospheric reanalyses. Finally, we evidence a strong link between the oceanic transports of heat and natural carbon. This supports the existence of a strong southward transport of natural carbon at the global scale, a feature present at pre-industrial times and still underlying the anthropogenic signal today. We find that current climate models systematically underestimate these natural large-scale ocean meridional transports of heat and carbon, which bears on future climate projections, in particular concerning Arctic climate, possible shifts in rainfall and carbon sinks partition between the land and the ocean.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFMIN11D1070E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFMIN11D1070E"><span>Fostering Team Awareness in Earth System Modeling Communities</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Easterbrook, S. M.; Lawson, A.; Strong, S.</p> <p>2009-12-01</p> <p>Existing Global Climate Models are typically managed and controlled at a single site, with varied levels of participation by scientists outside the core lab. As these models evolve to encompass a wider set of earth systems, this central control of the modeling effort becomes a bottleneck. But such models cannot evolve to become fully distributed open source projects unless they address the imbalance in the availability of communication channels: scientists at the core site have access to regular face-to-face communication with one another, while those at remote sites have access to only a subset of these conversations - e.g. formally scheduled teleconferences and user meetings. Because of this imbalance, critical decision making can be hidden from many participants, their code contributions can interact in unanticipated ways, and the community loses awareness of who knows what. We have documented some of these problems in a field study at one climate modeling centre, and started to develop tools to overcome these problems. We report on one such tool, TracSNAP, which analyzes the social network of the scientists contributing code to the model by extracting the data in an existing project code repository. The tool presents the results of this analysis to modelers and model users in a number of ways: recommendation for who has expertise on particular code modules, suggestions for code sections that are related to files being worked on, and visualizations of team communication patterns. The tool is currently available as a plugin for the Trac bug tracking system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC23A0899J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC23A0899J"><span>Coupling Climate Models and Forward-Looking Economic Models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Judd, K.; Brock, W. A.</p> <p>2010-12-01</p> <p>Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward-looking economic modules, and the initial models will help guide the construction of more refined models that can effectively use more powerful computational environments to analyze economic policies related to climate change. REFERENCES Brock, W., Xepapadeas, A., 2010, “An Integration of Simple Dynamic Energy Balance Climate Models and Ramsey Growth Models,” Department of Economics, University of Wisconsin, Madison, and University of Athens. Golub, A., Hertel, T., etal., 2009, “The opportunity cost of land use and the global potential for greenhouse gas mitigation in agriculture and forestry,” RESOURCE AND ENERGY ECONOMICS, 31, 299-319. Judd, K., 1992, “Projection methods for solving aggregate growth models,” JOURNAL OF ECONOMIC THEORY, 58: 410-52. Judd, K., 1998, NUMERICAL METHODS IN ECONOMICS, MIT Press, Cambridge, Mass. Nordhaus, W., 2007, A QUESTION OF BALANCE: ECONOMIC MODELS OF CLIMATE CHANGE, Yale University Press, New Haven, CT. North, G., R., Cahalan, R., Coakely, J., 1981, “Energy balance climate models,” REVIEWS OF GEOPHYSICS AND SPACE PHYSICS, Vol. 19, No. 1, 91-121, February Wu, W., North, G. R., 2007, “Thermal decay modes of a 2-D energy balance climate model,” TELLUS, 59A, 618-626.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24299088','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24299088"><span>Incorporating climate science in applications of the US endangered species act for aquatic species.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>McClure, Michelle M; Alexander, Michael; Borggaard, Diane; Boughton, David; Crozier, Lisa; Griffis, Roger; Jorgensen, Jeffrey C; Lindley, Steven T; Nye, Janet; Rowland, Melanie J; Seney, Erin E; Snover, Amy; Toole, Christopher; VAN Houtan, Kyle</p> <p>2013-12-01</p> <p>Aquatic species are threatened by climate change but have received comparatively less attention than terrestrial species. We gleaned key strategies for scientists and managers seeking to address climate change in aquatic conservation planning from the literature and existing knowledge. We address 3 categories of conservation effort that rely on scientific analysis and have particular application under the U.S. Endangered Species Act (ESA): assessment of overall risk to a species; long-term recovery planning; and evaluation of effects of specific actions or perturbations. Fewer data are available for aquatic species to support these analyses, and climate effects on aquatic systems are poorly characterized. Thus, we recommend scientists conducting analyses supporting ESA decisions develop a conceptual model that links climate, habitat, ecosystem, and species response to changing conditions and use this model to organize analyses and future research. We recommend that current climate conditions are not appropriate for projections used in ESA analyses and that long-term projections of climate-change effects provide temporal context as a species-wide assessment provides spatial context. In these projections, climate change should not be discounted solely because the magnitude of projected change at a particular time is uncertain when directionality of climate change is clear. Identifying likely future habitat at the species scale will indicate key refuges and potential range shifts. However, the risks and benefits associated with errors in modeling future habitat are not equivalent. The ESA offers mechanisms for increasing the overall resilience and resistance of species to climate changes, including establishing recovery goals requiring increased genetic and phenotypic diversity, specifying critical habitat in areas not currently occupied but likely to become important, and using adaptive management. Incorporación de las Ciencias Climáticas en las Aplicaciones del Acta Estadunidense de Especies en Peligro para Especies Acuáticas. © 2013 Society for Conservation Biology No claim to original US government works.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015HESSD..12.8853W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015HESSD..12.8853W"><span>Adaptation of water resource systems to an uncertain future</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Walsh, C. L.; Blenkinsop, S.; Fowler, H. J.; Burton, A.; Dawson, R. J.; Glenis, V.; Manning, L. J.; Kilsby, C. G.</p> <p>2015-09-01</p> <p>Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days, and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth the median number of drought order occurrences may increase five-fold. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence a portfolio of measures are required.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1406716-recent-changes-county-level-corn-yield-variability-united-states-from-observations-crop-models','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1406716-recent-changes-county-level-corn-yield-variability-united-states-from-observations-crop-models"><span>Recent changes in county-level corn yield variability in the United States from observations and crop models</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Leng, Guoyong</p> <p></p> <p>The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially underestimated the change trend of corn yield variability, in projecting its future changes.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27110979','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27110979"><span>Flood projections within the Niger River Basin under future land use and climate change.</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Aich, Valentin; Liersch, Stefan; Vetter, Tobias; Fournet, Samuel; Andersson, Jafet C M; Calmanti, Sandro; van Weert, Frank H A; Hattermann, Fred F; Paton, Eva N</p> <p>2016-08-15</p> <p>This study assesses future flood risk in the Niger River Basin (NRB), for the first time considering the simultaneous effects of both projected climate change and land use changes. For this purpose, an ecohydrological process-based model (SWIM) was set up and validated for past climate and land use dynamics of the entire NRB. Model runs for future flood risks were conducted with an ensemble of 18 climate models, 13 of them dynamically downscaled from the CORDEX Africa project and five statistically downscaled Earth System Models. Two climate and two land use change scenarios were used to cover a broad range of potential developments in the region. Two flood indicators (annual 90th percentile and the 20-year return flood) were used to assess the future flood risk for the Upper, Middle and Lower Niger as well as the Benue. The modeling results generally show increases of flood magnitudes when comparing a scenario period in the near future (2021-2050) with a base period (1976-2005). Land use effects are more uncertain, but trends and relative changes for the different catchments of the NRB seem robust. The dry areas of the Sahelian and Sudanian regions of the basin show a particularly high sensitivity to climatic and land use changes, with an alarming increase of flood magnitudes in parts. A scenario with continuing transformation of natural vegetation into agricultural land and urbanization intensifies the flood risk in all parts of the NRB, while a "regreening" scenario can reduce flood magnitudes to some extent. Yet, land use change effects were smaller when compared to the effects of climate change. In the face of an already existing adaptation deficit to catastrophic flooding in the region, the authors argue for a mix of adaptation and mitigation efforts in order to reduce the flood risk in the NRB. Copyright © 2016 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018E%26PSL.493..174M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018E%26PSL.493..174M"><span>Mountain ranges, climate and weathering. Do orogens strengthen or weaken the silicate weathering carbon sink?</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Maffre, Pierre; Ladant, Jean-Baptiste; Moquet, Jean-Sébastien; Carretier, Sébastien; Labat, David; Goddéris, Yves</p> <p>2018-07-01</p> <p>The role of mountains in the geological evolution of the carbon cycle has been intensively debated for the last decades. Mountains are thought to increase the local physical erosion, which in turns promotes silicate weathering, organic carbon transport and burial, and release of sulfuric acid by dissolution of sulfides. In this contribution, we explore the impact of mountain ranges on silicate weathering. Mountains modify the global pattern of atmospheric circulation as well as the local erosion conditions. Using an IPCC-class climate model, we first estimate the climatic impact of mountains by comparing the present day climate with the climate when all the continents are assumed to be flat. We then use these climate output to calculate weathering changes when mountains are present or absent, using standard expression for physical erosion and a 1D vertical model for rock weathering. We found that large-scale climate changes and enhanced rock supply by erosion due to mountain uplift have opposite effect, with similar orders of magnitude. A thorough testing of the weathering model parameters by data-model comparison shows that best-fit parameterizations lead to a decrease of weathering rate in the absence of mountain by about 20%. However, we demonstrate that solutions predicting an increase in weathering in the absence of mountain cannot be excluded. A clear discrimination between the solutions predicting an increase or a decrease in global weathering is pending on the improvement of the existing global databases for silicate weathering. Nevertheless, imposing a constant and homogeneous erosion rate for models without relief, we found that weathering decrease becomes unequivocal for very low erosion rates (below 10 t/km2/yr). We conclude that further monitoring of continental silicate weathering should be performed with a spatial distribution allowing to discriminate between the various continental landscapes (mountains, plains …).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ems..confE.788H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ems..confE.788H"><span>Urban impact on air quality in RegCM/CAMx couple for MEGAPOLI project - high resolution sensitivity study</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Halenka, T.; Huszar, P.; Belda, M.</p> <p>2010-09-01</p> <p>Recent studies show considerable effect of atmospheric chemistry and aerosols on climate on regional and local scale. For the purpose of qualifying and quantifying the magnitude of climate forcing due to atmospheric chemistry/aerosols on regional scale, the development of coupling of regional climate model and chemistry/aerosol model was started on the Department of Meteorology and Environmental Protection, Charles University, Prague, for the EC FP6 Project QUANTIFY and EC FP6 Project CECILIA. For this coupling, existing regional climate model and chemistry transport model have been used at very high resolution of 10km grid. Climate is calculated using RegCM while chemistry is solved by CAMx. The experiments with the couple have been prepared for EC FP7 project MEGAPOLI assessing the impact of the megacities and industrialized areas on climate. Meteorological fields generated by RCM drive CAMx transport, chemistry and a dry/wet deposition. A preprocessor utility was developed for transforming RegCM provided fields to CAMx input fields and format. New domain have been settled for MEGAPOLI purpose in 10km resolution including all the European "megacities" regions, i.e. London metropolitan area, Paris region, industrialized Ruhr area, Po valley etc. There is critical issue of the emission inventories available for 10km resolution including the urban hot-spots, TNO emissions are adopted for this sensitivity study in 10km resolution for comparison of the results with the simulation based on merged TNO emissions, i.e. basically original EMEP emissions at 50 km grid. The sensitivity test to switch on/off Paris area emissions is analysed as well. Preliminary results for year 2005 are presented and discussed to reveal whether the concept of effective emission indices could help to parameterize the urban plume effects in lower resolution models. Interactive coupling is compared to study the potential of possible impact of urban air-pollution to the urban area climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.H23F1639D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.H23F1639D"><span>Improving the Statistical Modeling of the TRMM Extreme Precipitation Monitoring System</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Demirdjian, L.; Zhou, Y.; Huffman, G. J.</p> <p>2016-12-01</p> <p>This project improves upon an existing extreme precipitation monitoring system based on the Tropical Rainfall Measuring Mission (TRMM) daily product (3B42) using new statistical models. The proposed system utilizes a regional modeling approach, where data from similar grid locations are pooled to increase the quality and stability of the resulting model parameter estimates to compensate for the short data record. The regional frequency analysis is divided into two stages. In the first stage, the region defined by the TRMM measurements is partitioned into approximately 27,000 non-overlapping clusters using a recursive k-means clustering scheme. In the second stage, a statistical model is used to characterize the extreme precipitation events occurring in each cluster. Instead of utilizing the block-maxima approach used in the existing system, where annual maxima are fit to the Generalized Extreme Value (GEV) probability distribution at each cluster separately, the present work adopts the peak-over-threshold (POT) method of classifying points as extreme if they exceed a pre-specified threshold. Theoretical considerations motivate the use of the Generalized-Pareto (GP) distribution for fitting threshold exceedances. The fitted parameters can be used to construct simple and intuitive average recurrence interval (ARI) maps which reveal how rare a particular precipitation event is given its spatial location. The new methodology eliminates much of the random noise that was produced by the existing models due to a short data record, producing more reasonable ARI maps when compared with NOAA's long-term Climate Prediction Center (CPC) ground based observations. The resulting ARI maps can be useful for disaster preparation, warning, and management, as well as increased public awareness of the severity of precipitation events. Furthermore, the proposed methodology can be applied to various other extreme climate records.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1165163','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1165163"><span></span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Branstator, Grant</p> <p></p> <p>The overall aim of our project was to quantify and characterize predictability of the climate as it pertains to decadal time scale predictions. By predictability we mean the degree to which a climate forecast can be distinguished from the climate that exists at initial forecast time, taking into consideration the growth of uncertainty that occurs as a result of the climate system being chaotic. In our project we were especially interested in predictability that arises from initializing forecasts from some specific state though we also contrast this predictability with predictability arising from forecasting the reaction of the system to externalmore » forcing – for example changes in greenhouse gas concentration. Also, we put special emphasis on the predictability of prominent intrinsic patterns of the system because they often dominate system behavior. Highlights from this work include: • Development of novel methods for estimating the predictability of climate forecast models. • Quantification of the initial value predictability limits of ocean heat content and the overturning circulation in the Atlantic as they are represented in various state of the art climate models. These limits varied substantially from model to model but on average were about a decade with North Atlantic heat content tending to be more predictable than North Pacific heat content. • Comparison of predictability resulting from knowledge of the current state of the climate system with predictability resulting from estimates of how the climate system will react to changes in greenhouse gas concentrations. It turned out that knowledge of the initial state produces a larger impact on forecasts for the first 5 to 10 years of projections. • Estimation of the predictability of dominant patterns of ocean variability including well-known patterns of variability in the North Pacific and North Atlantic. For the most part these patterns were predictable for 5 to 10 years. • Determination of especially predictable patterns in the North Atlantic. The most predictable of these retain predictability substantially longer than generic patterns, with some being predictable for two decades.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.H34C..06G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.H34C..06G"><span>Reconciling Scale Mismatch in Water Governance, Hydro-climatic Processes and Infrastructure Systems of Water Supply in Las Vegas</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Garcia, M. E.; Alarcon, T.; Portney, K.; Islam, S.</p> <p>2013-12-01</p> <p>Water resource systems are a classic example of a common pool resource due to the high cost of exclusion and the subtractability of the resource; for common pool resources, the performance of governance systems primarily depends on how well matched the institutional arrangements and rules are to the biophysical conditions and social norms. Changes in water governance, hydro-climatic processes and infrastructure systems occur on disparate temporal and spatial scales. A key challenge is the gap between current climate change model resolution, and the spatial and temporal scale of urban water supply decisions. This gap will lead to inappropriate management policies if not mediated through a carefully crafted decision making process. Traditional decision support and planning methods (DSPM) such as classical decision analysis are not equipped to deal with a non-static climate. While emerging methods such as decision scaling, robust decision making and real options are designed to deal with a changing climate, governance systems have evolved under the assumption of a static climate and it is not clear if these methods are well suited to the existing governance regime. In our study, these questions are contextualized by examining an urban water utility that has made significant changes in policy to adapt to changing conditions: the Southern Nevada Water Authority (SNWA) which serves metropolitan Las Vegas. Like most desert cities, Las Vegas exists because of water; the artesian springs of the Las Vegas Valley once provided an ample water supply for Native Americans, ranchers and later a small railroad city. However, population growth has increased demands far beyond local supplies. The area now depends on the Colorado River for the majority of its water supply. Natural climate variability with periodic droughts has further challenged water providers; projected climate changes and further population growth will exacerbate these challenges. Las Vegas is selected as a case study due to the combined challenges of population growth and climate change, common in the arid west, and due its cooperative institutional response to these challenges, unprecedented in the arid west. To begin to disentangle this question we have analyzed the institutional arrangements and rules which govern water decision making in the Las Vegas Valley and evaluated the existing DSPM used by the SNWA and partner utilities. Presented here are the preliminary results from an ongoing project.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1714726C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1714726C"><span>Modeling tools for the assessment of microbiological risks during floods: a review</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Collender, Philip; Yang, Wen; Stieglitz, Marc; Remais, Justin</p> <p>2015-04-01</p> <p>Floods are a major, recurring source of harm to global economies and public health. Projected increases in the frequency and intensity of heavy precipitation events under future climate change, coupled with continued urbanization in areas with high risk of floods, may exacerbate future impacts of flooding. Improved flood risk management is essential to support global development, poverty reduction and public health, and is likely to be a crucial aspect of climate change adaptation. Importantly, floods can facilitate the transmission of waterborne pathogens by changing social conditions (overcrowding among displaced populations, interruption of public health services), imposing physical challenges to infrastructure (sewerage overflow, reduced capacity to treat drinking water), and altering fate and transport of pathogens (transport into waterways from overland flow, resuspension of settled contaminants) during and after flood conditions. Hydrological and hydrodynamic models are capable of generating quantitative characterizations of microbiological risks associated with flooding, while accounting for these diverse and at times competing physical and biological processes. Despite a few applications of such models to the quantification of microbiological risks associated with floods, there exists limited guidance as to the relative capabilities, and limitations, of existing modeling platforms when used for this purpose. Here, we review 17 commonly used flood and water quality modeling tools that have demonstrated or implicit capabilities of mechanistically representing and quantifying microbial risk during flood conditions. We compare models with respect to their capabilities of generating outputs that describe physical and microbial conditions during floods, such as concentration or load of non-cohesive sediments or pathogens, and the dynamics of high flow conditions. Recommendations are presented for the application of specific modeling tools for assessing particular flood-related microbial risks, and model improvements are suggested that may better characterize key microbial risks during flood events. The state of current tools are assessed in the context of a changing climate where the frequency, intensity and duration of flooding are shifting in some areas.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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