Sample records for climate change simulation

  1. Changes in Seasonal and Extreme Hydrologic Conditions of the Georgia Basin/Puget Sound in an Ensemble Regional Climate Simulation for the Mid-Century

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

    Leung, Lai R.; Qian, Yun

    This study examines an ensemble of climate change projections simulated by a global climate model (GCM) and downscaled with a region climate model (RCM) to 40 km spatial resolution for the western North America. One control and three ensemble future climate simulations were produced by the GCM following a business as usual scenario for greenhouse gases and aerosols emissions from 1995 to 2100. The RCM was used to downscale the GCM control simulation (1995-2015) and each ensemble future GCM climate (2040-2060) simulation. Analyses of the regional climate simulations for the Georgia Basin/Puget Sound showed a warming of 1.5-2oC and statisticallymore » insignificant changes in precipitation by the mid-century. Climate change has large impacts on snowpack (about 50% reduction) but relatively smaller impacts on the total runoff for the basin as a whole. However, climate change can strongly affect small watersheds such as those located in the transient snow zone, causing a higher likelihood of winter flooding as a higher percentage of precipitation falls in the form of rain rather than snow, and reduced streamflow in early summer. In addition, there are large changes in the monthly total runoff above the upper 1% threshold (or flood volume) from October through May, and the December flood volume of the future climate is 60% above the maximum monthly flood volume of the control climate. Uncertainty of the climate change projections, as characterized by the spread among the ensemble future climate simulations, is relatively small for the basin mean snowpack and runoff, but increases in smaller watersheds, especially in the transient snow zone, and associated with extreme events. This emphasizes the importance of characterizing uncertainty through ensemble simulations.« less

  2. Untangling climate signals from autogenic changes in long-term peatland development

    NASA Astrophysics Data System (ADS)

    Morris, Paul J.; Baird, Andy J.; Young, Dylan M.; Swindles, Graeme T.

    2015-12-01

    Peatlands represent important archives of Holocene paleoclimatic information. However, autogenic processes may disconnect peatland hydrological behavior from climate and overwrite climatic signals in peat records. We use a simulation model of peatland development driven by a range of Holocene climate reconstructions to investigate climate signal preservation in peat records. Simulated water-table depths and peat decomposition profiles exhibit homeostatic recovery from prescribed changes in rainfall, whereas changes in temperature cause lasting alterations to peatland structure and function. Autogenic ecohydrological feedbacks provide both high- and low-pass filters for climatic information, particularly rainfall. Large-magnitude climatic changes of an intermediate temporal scale (i.e., multidecadal to centennial) are most readily preserved in our simulated peat records. Simulated decomposition signals are offset from the climatic changes that generate them due to a phenomenon known as secondary decomposition. Our study provides the mechanistic foundations for a framework to separate climatic and autogenic signals in peat records.

  3. Uncertainty in simulating wheat yields under climate change

    NASA Astrophysics Data System (ADS)

    Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

    2013-09-01

    Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

  4. Simulated hydrologic responses to climate variations and change in the Merced, Carson, and American River basins, Sierra Nevada, California, 1900-2099 *

    USGS Publications Warehouse

    Dettinger, M.D.; Cayan, D.R.; Meyer, M.K.; Jeton, A.

    2004-01-01

    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.

  5. Simulation of Climate Change Impacts on Wheat-Fallow Cropping Systems

    USDA-ARS?s Scientific Manuscript database

    Agricultural system simulation models are predictive tools for assessing climate change impacts on crop production. In this study, RZWQM2 that contains the DSSAT 4.0-CERES model was evaluated for simulating climate change impacts on wheat growth. The model was calibrated and validated using data fro...

  6. Uncertainty in Simulating Wheat Yields Under Climate Change

    NASA Technical Reports Server (NTRS)

    Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.; hide

    2013-01-01

    Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.

  7. Addressing climate change in the Forest Vegetation Simulator to assess impacts on landscape forest dynamics

    Treesearch

    Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

    2010-01-01

    To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

  8. Addressing climate change in the forest vegetation simulator to assess impacts on landscape forest dynamics

    Treesearch

    Nicholas L. Crookston; Gerald E. Rehfeldt; Gary E. Dixon; Aaron R. Weiskittel

    2010-01-01

    To simulate stand-level impacts of climate change, predictors in the widely used Forest Vegetation Simulator (FVS) were adjusted to account for expected climate effects. This was accomplished by: (1) adding functions that link mortality and regeneration of species to climate variables expressing climatic suitability, (2) constructing a function linking site index to...

  9. Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

    NASA Astrophysics Data System (ADS)

    Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe

    2016-11-01

    Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

  10. The New England Climate Adaptation Project: Enhancing Local Readiness to Adapt to Climate Change through Role-Play Simulations

    NASA Astrophysics Data System (ADS)

    Rumore, D.; Kirshen, P. H.; Susskind, L.

    2014-12-01

    Despite scientific consensus that the climate is changing, local efforts to prepare for and manage climate change risks remain limited. How we can raise concern about climate change risks and enhance local readiness to adapt to climate change's effects? In this presentation, we will share the lessons learned from the New England Climate Adaptation Project (NECAP), a participatory action research project that tested science-based role-play simulations as a tool for educating the public about climate change risks and simulating collective risk management efforts. NECAP was a 2-year effort involving the Massachusetts Institute of Technology, the Consensus Building Institute, the National Estuarine Research Reserve System, and four coastal New England municipalities. During 2012-2013, the NECAP team produced downscaled climate change projections, a summary risk assessment, and a stakeholder assessment for each partner community. Working with local partners, we used these assessments to create a tailored, science-based role-play simulation for each site. Through a series of workshops in 2013, NECAP engaged between 115-170 diverse stakeholders and members of the public in each partner municipality in playing the simulation and a follow up conversation about local climate change risks and possible adaptation strategies. Data were collected through before-and-after surveys administered to all workshop participants, follow-up interviews with 25 percent of workshop participants, public opinion polls conducted before and after our intervention, and meetings with public officials. This presentation will report our research findings and explain how science-based role-play simulations can be used to help communicate local climate change risks and enhance local readiness to adapt.

  11. Losing the Lake: Simulations to Promote Gains in Student Knowledge and Interest about Climate Change

    ERIC Educational Resources Information Center

    Nussbaum, E. Michael; Owens, Marissa C.; Sinatra, Gale M.; Rehmat, Abeera P.; Cordova, Jacqueline R.; Ahmad, Sajjad; Harris, Fred C., Jr.; Dascalu, Sergiu M.

    2015-01-01

    Climate change literacy plays a key role in promoting sound political decisions and promoting sustainable consumption patterns. Based on evidence suggesting that student understanding and interest in climate change is best accomplished through studying local effects, we developed a simulation/game exploring the impact of climate change on the…

  12. Impacts of Irrigation on Daily Extremes in the Coupled Climate System

    NASA Technical Reports Server (NTRS)

    Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

    2014-01-01

    Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

  13. Untangling climatic and autogenic signals in peat records

    NASA Astrophysics Data System (ADS)

    Morris, Paul J.; Baird, Andrew J.; Young, Dylan M.; Swindles, Graeme T.

    2016-04-01

    Raised bogs contain potentially valuable information about Holocene climate change. However, autogenic processes may disconnect peatland hydrological behaviour from climate, and overwrite and degrade climatic signals in peat records. How can genuine climate signals be separated from autogenic changes? What level of detail of climatic information should we expect to be able to recover from peat-based reconstructions? We used an updated version of the DigiBog model to simulate peatland development and response to reconstructed Holocene rainfall and temperature reconstructions. The model represents key processes that are influential in peatland development and climate signal preservation, and includes a network of feedbacks between peat accumulation, decomposition, hydraulic structure and hydrological processes. It also incorporates the effects of temperature upon evapotranspiration, plant (litter) productivity and peat decomposition. Negative feedbacks in the model cause simulated water-table depths and peat humification records to exhibit homeostatic recovery from prescribed changes in rainfall, chiefly through changes in drainage. However, the simulated bogs show less resilience to changes in temperature, which cause lasting alterations to peatland structure and function and may therefore be more readily detectable in peat records. The network of feedbacks represented in DigiBog also provide both high- and low-pass filters for climatic information, meaning that the fidelity with which climate signals are preserved in simulated peatlands is determined by both the magnitude and the rate of climate change. Large-magnitude climatic events of an intermediate frequency (i.e., multi-decadal to centennial) are best preserved in the simulated bogs. We found that simulated humification records are further degraded by a phenomenon known as secondary decomposition. Decomposition signals are consistently offset from the climatic events that generate them, and decomposition records of dry-wet-dry climate sequences appear to be particularly vulnerable to overwriting. Our findings have direct implications not only for the interpretation of peat-based records of past climates, but also for understanding the likely vulnerability of peatland ecosystems and carbon stocks to future climate change.

  14. Using multiple climate projections for assessing hydrological response to climate change in the Thukela River Basin, South Africa

    NASA Astrophysics Data System (ADS)

    Graham, L. Phil; Andersson, Lotta; Horan, Mark; Kunz, Richard; Lumsden, Trevor; Schulze, Roland; Warburton, Michele; Wilk, Julie; Yang, Wei

    This study used climate change projections from different regional approaches to assess hydrological effects on the Thukela River Basin in KwaZulu-Natal, South Africa. Projecting impacts of future climate change onto hydrological systems can be undertaken in different ways and a variety of effects can be expected. Although simulation results from global climate models (GCMs) are typically used to project future climate, different outcomes from these projections may be obtained depending on the GCMs themselves and how they are applied, including different ways of downscaling from global to regional scales. Projections of climate change from different downscaling methods, different global climate models and different future emissions scenarios were used as input to simulations in a hydrological model to assess climate change impacts on hydrology. A total of 10 hydrological change simulations were made, resulting in a matrix of hydrological response results. This matrix included results from dynamically downscaled climate change projections from the same regional climate model (RCM) using an ensemble of three GCMs and three global emissions scenarios, and from statistically downscaled projections using results from five GCMs with the same emissions scenario. Although the matrix of results does not provide complete and consistent coverage of potential uncertainties from the different methods, some robust results were identified. In some regards, the results were in agreement and consistent for the different simulations. For others, particularly rainfall, the simulations showed divergence. For example, all of the statistically downscaled simulations showed an annual increase in precipitation and corresponding increase in river runoff, while the RCM downscaled simulations showed both increases and decreases in runoff. According to the two projections that best represent runoff for the observed climate, increased runoff would generally be expected for this basin in the future. Dealing with such variability in results is not atypical for assessing climate change impacts in Africa and practitioners are faced with how to interpret them. This work highlights the need for additional, well-coordinated regional climate downscaling for the region to further define the range of uncertainties involved.

  15. A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

    NASA Astrophysics Data System (ADS)

    Komurcu, M.; Huber, M.

    2016-12-01

    Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

  16. Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²

    NASA Astrophysics Data System (ADS)

    Goldenson, N. L.

    2014-12-01

    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.

  17. LPJ-GUESS Simulated Western North America Mid-latitude Vegetation Changes for 15-10 ka Using the CCSM3 TraCE Climate Simulation

    NASA Astrophysics Data System (ADS)

    Shafer, S. L.; Bartlein, P. J.

    2017-12-01

    The period from 15-10 ka was a time of rapid vegetation changes in North America. Continental ice sheets in northern North America were receding, exposing new habitat for vegetation, and regions distant from the ice sheets experienced equally large environmental changes. Northern hemisphere temperatures during this period were increasing, promoting transitions from cold-adapted to temperate plant taxa at mid-latitudes. Long, transient paleovegetation simulations can provide important information on vegetation responses to climate changes, including both the spatial dynamics and rates of species distribution changes over time. Paleovegetation simulations also can fill the spatial and temporal gaps in observed paleovegetation records (e.g., pollen data from lake sediments), allowing us to test hypotheses about past vegetation changes (e.g., the location of past refugia). We used the CCSM3 TraCE transient climate simulation as input for LPJ-GUESS, a general ecosystem model, to simulate vegetation changes from 15-10 ka for parts of western North America at mid-latitudes ( 35-55° N). For these simulations, LPJ-GUESS was parameterized to simulate key tree taxa for western North America (e.g., Pseudotsuga, Tsuga, Quercus, etc.). The CCSM3 TraCE transient climate simulation data were regridded onto a 10-minute grid of the study area. We analyzed the simulated spatial and temporal dynamics of these taxa and compared the simulated changes with observed paleovegetation changes recorded in pollen and plant macrofossil data (e.g., data from the Neotoma Paleoecology Database). In general, the LPJ-GUESS simulations reproduce the general patterns of paleovegetation responses to climate change, although the timing of some simulated vegetation changes do not match the observed paleovegetation record. We describe the areas and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of the simulated climate and vegetation data. The magnitude and rate of the simulated past vegetation changes are compared with projected future vegetation changes for the region.

  18. The Detection and Attribution Model Intercomparison Project (DAMIP v1.0)contribution to CMIP6

    DOE PAGES

    Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; ...

    2016-10-18

    Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of futuremore » climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.« less

  19. The Detection and Attribution Model Intercomparison Project (DAMIP v1.0) contribution to CMIP6

    NASA Astrophysics Data System (ADS)

    Gillett, Nathan P.; Shiogama, Hideo; Funke, Bernd; Hegerl, Gabriele; Knutti, Reto; Matthes, Katja; Santer, Benjamin D.; Stone, Daithi; Tebaldi, Claudia

    2016-10-01

    Detection and attribution (D&A) simulations were important components of CMIP5 and underpinned the climate change detection and attribution assessments of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The primary goals of the Detection and Attribution Model Intercomparison Project (DAMIP) are to facilitate improved estimation of the contributions of anthropogenic and natural forcing changes to observed global warming as well as to observed global and regional changes in other climate variables; to contribute to the estimation of how historical emissions have altered and are altering contemporary climate risk; and to facilitate improved observationally constrained projections of future climate change. D&A studies typically require unforced control simulations and historical simulations including all major anthropogenic and natural forcings. Such simulations will be carried out as part of the DECK and the CMIP6 historical simulation. In addition D&A studies require simulations covering the historical period driven by individual forcings or subsets of forcings only: such simulations are proposed here. Key novel features of the experimental design presented here include firstly new historical simulations with aerosols-only, stratospheric-ozone-only, CO2-only, solar-only, and volcanic-only forcing, facilitating an improved estimation of the climate response to individual forcing, secondly future single forcing experiments, allowing observationally constrained projections of future climate change, and thirdly an experimental design which allows models with and without coupled atmospheric chemistry to be compared on an equal footing.

  20. Modeling the influence of climate change on watershed systems: Adaptation through targeted practices

    NASA Astrophysics Data System (ADS)

    Dudula, John; Randhir, Timothy O.

    2016-10-01

    Climate change may influence hydrologic processes of watersheds (IPCC, 2013) and increased runoff may cause flooding, eroded stream banks, widening of stream channels, increased pollutant loading, and consequently impairment of aquatic life. The goal of this study was to quantify the potential impacts of climate change on watershed hydrologic processes and to evaluate scale and effectiveness of management practices for adaptation. We simulate baseline watershed conditions using the Hydrological Simulation Program Fortran (HSPF) simulation model to examine the possible effects of changing climate on watershed processes. We also simulate the effects of adaptation and mitigation through specific best management strategies for various climatic scenarios. With continuing low-flow conditions and vulnerability to climate change, the Ipswich watershed is the focus of this study. We quantify fluxes in runoff, evapotranspiration, infiltration, sediment load, and nutrient concentrations under baseline and climate change scenarios (near and far future). We model adaptation options for mitigating climate effects on watershed processes using bioretention/raingarden Best Management Practices (BMPs). It was observed that climate change has a significant impact on watershed runoff and carefully designed and maintained BMPs at subwatershed scale can be effective in mitigating some of the problems related to stormwater runoff. Policy options include implementation of BMPs through education and incentives for scale-dependent and site specific bioretention units/raingardens to increase the resilience of the watershed system to current and future climate change.

  1. Uncertainty in simulating wheat yields under climate change

    USDA-ARS?s Scientific Manuscript database

    Anticipating the impacts of climate change on crop yields is critical for assessing future food security. Process-based crop simulation models are the most commonly used tools in such assessments. Analysis of uncertainties in future greenhouse gas emissions and their impacts on future climate change...

  2. Potential economic benefits of adapting agricultural production systems to future climate change

    USGS Publications Warehouse

    Fagre, Daniel B.; Pederson, Gregory; Bengtson, Lindsey E.; Prato, Tony; Qui, Zeyuan; Williams, Jimmie R.

    2010-01-01

    Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960–2005) and future climate period (2006–2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO2 emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

  3. Potential economic benefits of adapting agricultural production systems to future climate change.

    PubMed

    Prato, Tony; Zeyuan, Qiu; Pederson, Gregory; Fagre, Dan; Bengtson, Lindsey E; Williams, Jimmy R

    2010-03-01

    Potential economic impacts of future climate change on crop enterprise net returns and annual net farm income (NFI) are evaluated for small and large representative farms in Flathead Valley in Northwest Montana. Crop enterprise net returns and NFI in an historical climate period (1960-2005) and future climate period (2006-2050) are compared when agricultural production systems (APSs) are adapted to future climate change. Climate conditions in the future climate period are based on the A1B, B1, and A2 CO(2) emission scenarios from the Intergovernmental Panel on Climate Change Fourth Assessment Report. Steps in the evaluation include: (1) specifying crop enterprises and APSs (i.e., combinations of crop enterprises) in consultation with locals producers; (2) simulating crop yields for two soils, crop prices, crop enterprises costs, and NFIs for APSs; (3) determining the dominant APS in the historical and future climate periods in terms of NFI; and (4) determining whether NFI for the dominant APS in the historical climate period is superior to NFI for the dominant APS in the future climate period. Crop yields are simulated using the Environmental/Policy Integrated Climate (EPIC) model and dominance comparisons for NFI are based on the stochastic efficiency with respect to a function (SERF) criterion. Probability distributions that best fit the EPIC-simulated crop yields are used to simulate 100 values for crop yields for the two soils in the historical and future climate periods. Best-fitting probability distributions for historical inflation-adjusted crop prices and specified triangular probability distributions for crop enterprise costs are used to simulate 100 values for crop prices and crop enterprise costs. Averaged over all crop enterprises, farm sizes, and soil types, simulated net return per ha averaged over all crop enterprises decreased 24% and simulated mean NFI for APSs decreased 57% between the historical and future climate periods. Although adapting APSs to future climate change is advantageous (i.e., NFI with adaptation is superior to NFI without adaptation based on SERF), in six of the nine cases in which adaptation is advantageous, NFI with adaptation in the future climate period is inferior to NFI in the historical climate period. Therefore, adaptation of APSs to future climate change in Flathead Valley is insufficient to offset the adverse impacts on NFI of such change.

  4. Impact of the climate change on the performance of the steam and gas turbines in Russia

    NASA Astrophysics Data System (ADS)

    Fedotova (Kasilova, E. V.; Klimenko, V. V.; Klimenko, A. V.; Tereshin, A. G.

    2017-11-01

    The power generating industry is known to be vulnerable to the climate change due to the deteriorating efficiency of the power equipment. Effects for Russia are not completely understood yet. But they are already detected and will be more pronounced during the entire current century, as the Russian territory is one of the areas around the world where the climate change is developing most rapidly. An original climate model was applied to simulate the change of the air temperature across Russia for the twenty-first century. The results of the climate simulations were used to conduct impact analysis for the steam and gas turbine performance taking into account seasonal and spatial heterogeneity of the climate change across the Russian territory. Sensitivity of the turbines to the climatic conditions was simulated using both results of fundamental heat transfer research and empirical performance curves for the units being in operation nowadays. The integral effect of the climate change on the power generating industry was estimated. Some possible challenges and opportunities resulted from the climate change were identified.

  5. Collaborative Project: Development of an Isotope-Enabled CESM for Testing Abrupt Climate Changes

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

    Liu, Zhengyu

    One of the most important validations for a state-of-art Earth System Model (ESM) with respect to climate changes is the simulation of the climate evolution and abrupt climate change events in the Earth’s history of the last 21,000 years. However, one great challenge for model validation is that ESMs usually do not directly simulate geochemical variables that can be compared directly with past proxy records. In this proposal, we have met this challenge by developing the simulation capability of major isotopes in a state-of-art ESM, the Community Earth System Model (CESM), enabling us to make direct model-data comparison by comparingmore » the model directly against proxy climate records. Our isotope-enabled ESM incorporates the capability of simulating key isotopes and geotracers, notably δ 18O, δD, δ 14C, and δ 13C, Nd and Pa/Th. The isotope-enabled ESM have been used to perform some simulations for the last 21000 years. The direct comparison of these simulations with proxy records has shed light on the mechanisms of important climate change events.« less

  6. Can role-play with interactive simulations enhance climate change knowledge, affect and intent to act?

    NASA Astrophysics Data System (ADS)

    Rooney-varga, J. N.; Sterman, J.; Fracassi, E. P.; Franck, T.; Kapmeier, F.; Kurker, V.; Jones, A.; Rath, K.

    2017-12-01

    The strong scientific consensus about the reality and risks of anthropogenic climate change stands in stark contrast to widespread confusion and complacency among the public. Many efforts to close that gap, grounded in the information deficit model of risk communication, provide scientific information on climate change through reports and presentations. However, research shows that showing people research does not work: the gap between scientific and public understanding of climate change remains wide. Tools that are rigorously grounded in the science and motivate action on climate change are urgently needed. Here we assess the impact of one such tool, an interactive, role-play simulation, World Climate. Participants take the roles of delegates to the UN climate negotiations and are challenged to create an agreement limiting warming to no more than 2°C. The C-ROADS climate simulation model then provides participants with immediate feedback about the expected impacts of their decisions. Participants use C-ROADS to explore the climate system and use the results to refine their negotiating positions, learning about climate change while experiencing the social dynamics of negotiations and decision-making. Pre- and post-survey results from 21 sessions in eight nations showed significant gains in participants' climate change knowledge, affective engagement, intent to take action, and desire to learn. Contrary to the deficit model, gains in participants' desire to learn more and intention to act were associated with gains in affective engagement, particularly feelings of urgency and hope, but not climate knowledge. Gains were just as strong among participants who oppose government regulation, suggesting the simulation's potential to reach across political divides. Results indicate that simulations like World Climate offer a climate change communication tool that enables people to learn and feel for themselves, which together have the potential to motivate action informed by science.

  7. Evaluation of simulated corn yields and associated uncertainty in different climate zones of China using Daycent Model

    NASA Astrophysics Data System (ADS)

    Fu, A.; Xue, Y.

    2017-12-01

    Corn is one of most important agricultural production in China. Research on the simulation of corn yields and the impacts of climate change and agricultural management practices on corn yields is important in maintaining the stable corn production. After climatic data including daily temperature, precipitation, solar radiation, relative humidity, and wind speed from 1948 to 2010, soil properties, observed corn yields, and farmland management information were collected, corn yields grown in humidity and hot environment (Sichuang province) and cold and dry environment (Hebei province) in China in the past 63 years were simulated by Daycent, and the results was evaluated based on published yield record. The relationship between regional climate change, global warming and corn yield were analyzed, the uncertainties of simulation derived from agricultural management practices by changing fertilization levels, land fertilizer maintenance and tillage methods were reported. The results showed that: (1) Daycent model is capable to simulate corn yields under the different climatic background in China. (2) When studying the relationship between regional climate change and corn yields, it has been found that observed and simulated corn yields increased along with total regional climate change. (3) When studying the relationship between the global warming and corn yields, It was discovered that newly-simulated corn yields after removing the global warming trend of original temperature data were lower than before.

  8. Global Responses to Potential Climate Change: A Simulation.

    ERIC Educational Resources Information Center

    Williams, Mary Louise; Mowry, George

    This interdisciplinary five-day unit provides students with an understanding of the issues in the debate on global climate change. Introductory lessons enhance understanding of the "greenhouse gases" and their sources with possible global effects of climate change. Students then roleplay negotiators from 10 nations in a simulation of the…

  9. The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

    NASA Technical Reports Server (NTRS)

    Rind, David H.; Lean, Judith L.; Jonas, Jeffrey

    2014-01-01

    Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

  10. Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

    Treesearch

    John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

    2016-01-01

    We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

  11. Simulated soil organic carbon changes in Maryland are affected by tillage, climate change, and crop yield

    USDA-ARS?s Scientific Manuscript database

    The impact of climate change on soil organic carbon (SOC) stocks in no-till (NT) and conventionally-tilled (CT) agricultural systems is poorly understood. The objective of this study was to simulate the impact of projected climate change (air temperature and precipitation) on SOC to 50 cm soil depth...

  12. [Lake eutrophication modeling in considering climatic factors change: a review].

    PubMed

    Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

    2012-11-01

    Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

  13. Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

    PubMed

    Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

    2015-01-01

    Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

  14. Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

    DOE PAGES

    Eum, Hyung-Il; Gachon, Philippe; Laprise, René

    2016-01-01

    This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

  15. Impacts of Model Bias on the Climate Change Signal and Effects of Weighted Ensembles of Regional Climate Model Simulations: A Case Study over Southern Québec, Canada

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

    Eum, Hyung-Il; Gachon, Philippe; Laprise, René

    This study examined the impact of model biases on climate change signals for daily precipitation and for minimum and maximum temperatures. Through the use of multiple climate scenarios from 12 regional climate model simulations, the ensemble mean, and three synthetic simulations generated by a weighting procedure, we investigated intermodel seasonal climate change signals between current and future periods, for both median and extreme precipitation/temperature values. A significant dependence of seasonal climate change signals on the model biases over southern Québec in Canada was detected for temperatures, but not for precipitation. This suggests that the regional temperature change signal is affectedmore » by local processes. Seasonally, model bias affects future mean and extreme values in winter and summer. In addition, potentially large increases in future extremes of temperature and precipitation values were projected. For three synthetic scenarios, systematically less bias and a narrow range of mean change for all variables were projected compared to those of climate model simulations. In addition, synthetic scenarios were found to better capture the spatial variability of extreme cold temperatures than the ensemble mean scenario. Finally, these results indicate that the synthetic scenarios have greater potential to reduce the uncertainty of future climate projections and capture the spatial variability of extreme climate events.« less

  16. 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...

  17. The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

    NASA Astrophysics Data System (ADS)

    Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

    2015-12-01

    Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

  18. Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

    NASA Technical Reports Server (NTRS)

    Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian; hide

    2015-01-01

    Many studies have been carried out during the last decade to study the effect of climate change on crop yields and other key crop characteristics. In these studies, one or several crop models were used to simulate crop growth and development for different climate scenarios that correspond to different projections of atmospheric CO2 concentration, temperature, and rainfall changes (Semenov et al., 1996; Tubiello and Ewert, 2002; White et al., 2011). The Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al., 2013) builds on these studies with the goal of using an ensemble of multiple crop models in order to assess effects of climate change scenarios for several crops in contrasting environments. These studies generate large datasets, including thousands of simulated crop yield data. They include series of yield values obtained by combining several crop models with different climate scenarios that are defined by several climatic variables (temperature, CO2, rainfall, etc.). Such datasets potentially provide useful information on the possible effects of different climate change scenarios on crop yields. However, it is sometimes difficult to analyze these datasets and to summarize them in a useful way due to their structural complexity; simulated yield data can differ among contrasting climate scenarios, sites, and crop models. Another issue is that it is not straightforward to extrapolate the results obtained for the scenarios to alternative climate change scenarios not initially included in the simulation protocols. Additional dynamic crop model simulations for new climate change scenarios are an option but this approach is costly, especially when a large number of crop models are used to generate the simulated data, as in AgMIP. Statistical models have been used to analyze responses of measured yield data to climate variables in past studies (Lobell et al., 2011), but the use of a statistical model to analyze yields simulated by complex process-based crop models is a rather new idea. We demonstrate herewith that statistical methods can play an important role in analyzing simulated yield data sets obtained from the ensembles of process-based crop models. Formal statistical analysis is helpful to estimate the effects of different climatic variables on yield, and to describe the between-model variability of these effects.

  19. Watershed scale response to climate change--Yampa River Basin, Colorado

    USGS Publications Warehouse

    Hay, Lauren E.; Battaglin, William A.; Markstrom, Steven L.

    2012-01-01

    General Circulation Model simulations of future climate through 2099 project a wide range of possible scenarios. To determine the sensitivity and potential effect of long-term climate change on the freshwater resources of the United States, the U.S. Geological Survey Global Change study, "An integrated watershed scale response to global change in selected basins across the United States" was started in 2008. The long-term goal of this national study is to provide the foundation for hydrologically based climate change studies across the nation. Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Yampa River Basin at Steamboat Springs, Colorado.

  20. Simulating stand climate, phenology, and photosynthesis of a forest stand with a process-based growth model.

    PubMed

    Rötzer, Thomas; Leuchner, Michael; Nunn, Angela J

    2010-07-01

    In the face of climate change and accompanying risks, forest management in Europe is becoming increasingly important. Model simulations can help to understand the reactions and feedbacks of a changing environment on tree growth. In order to simulate forest growth based on future climate change scenarios, we tested the basic processes underlying the growth model BALANCE, simulating stand climate (air temperature, photosynthetically active radiation (PAR) and precipitation), tree phenology, and photosynthesis. A mixed stand of 53- to 60-year-old Norway spruce (Picea abies) and European beech (Fagus sylvatica) in Southern Germany was used as a reference. The results show that BALANCE is able to realistically simulate air temperature gradients in a forest stand using air temperature measurements above the canopy and PAR regimes at different heights for single trees inside the canopy. Interception as a central variable for water balance of a forest stand was also estimated. Tree phenology, i.e. bud burst and leaf coloring, could be reproduced convincingly. Simulated photosynthesis rates were in accordance with measured values for beech both in the sun and the shade crown. For spruce, however, some discrepancies in the rates were obvious, probably due to changed environmental conditions after bud break. Overall, BALANCE has shown to respond to scenario simulations of a changing environment (e.g., climate change, change of forest stand structure).

  1. Possible climate change over Eurasia under different emission scenarios

    NASA Astrophysics Data System (ADS)

    Sokolov, A. P.; Monier, E.; Scott, J. R.; Forest, C. E.; Schlosser, C. A.

    2011-12-01

    In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

  2. Possible climate change over Eurasia under different emission scenarios

    NASA Astrophysics Data System (ADS)

    Sokolov, A. P.; Monier, E.; Gao, X.

    2012-12-01

    In an attempt to evaluate possible climate change over EURASIA, we analyze results of six AMIP type simulations with CAM version 3 (CAM3) at 2x2.5 degree resolution. CAM3 is driven by time series of sea surface temperatures (SSTs) and sea ice obtained by running the MIT IGSM2.3, which consists of a 3D ocean GCM coupled to a zonally-averaged atmospheric climate-chemistry model. In addition to changes in SSTs, CAM3 is forced by changes in greenhouse gases and ozone concentrations, sulfate aerosol forcing and black carbon loading calculated by the IGSM2.3. An essential feature of the IGSM is the possibility to vary its climate sensitivity (using a cloud adjustment technique) and the strength of the aerosol forcing. For consistency, new modules were developed in CAM3 to modify its climate sensitivity and aerosol forcing to match those used in the simulations with the IGSM2.3. The simulations presented in this paper were carried out for two emission scenarios, a "Business as usual" scenario and a 660 ppm of CO2-EQ stabilization, which are similar to the RCP8.5 and RCP4.5 scenarios, respectively. Values of climate sensitivity used in the simulations within the IGSM-CAM framework are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the 20th century climate simulated by different versions of the IGSM with observations. The associated strength of the aerosol forcing was chosen to ensure a good agreement with the observed climate change over the 20th century. Because the concentration of sulfate aerosol significantly decreases over the 21st century in both emissions scenarios, climate changes obtained in these simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

  3. Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

    PubMed Central

    Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

    2012-01-01

    The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

  4. Climate Change Impact on Air Quality in High Resolution Simulation for Central Europe

    NASA Astrophysics Data System (ADS)

    Halenka, T.; Huszar, P.; Belda, M.

    2009-04-01

    Recently the effects of climate change on air-quality and vice-versa are studied quite extensively. In fact, even at regional and local scale especially the impact of climate change on the atmospheric composition and photochemical smog formation conditions can be significant when expecting e.g. more frequent appearance of heat waves etc. For the purpose of qualifying and quantifying the magnitude of such effects and to study the potential of climate forcing due to atmospheric chemistry/aerosols on regional scale, chemistry-transport model was coupled to RegCM on the Department of Meteorology and Environmental Protection, Faculty of Mathematics and Physics, Charles University in Prague, for the simulations in framework of the EC FP6 Project CECILIA. Off-line one way coupling enables the simulation of distribution of pollutants over 1991-2001 in very high resolution of 10 km is compared to the EMEP observations for the area of Central Europe. Simulations driven by climate change boundary conditions for time slices 1991-2000, 2041-2050 and 2091-2100 are presented to show the effect of climate change on the air quality in the region.

  5. Sensitivity of Ocean Chemistry and Oxygen Change to the Uncertainty in Climate Change

    NASA Astrophysics Data System (ADS)

    Cao, L.; Wang, S.; Zheng, M.; Zhang, H.

    2014-12-01

    With increasing atmospheric CO2 and climate change, global ocean is undergoing substantial physical and biogeochemical changes. In particular, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would affect the projection of ocean oxygen and carbonate chemistry. To examine the effect of climate change on ocean oxygen and carbonate chemistry, we used an Earth system model of intermediate complexity to perform simulations that are driven by atmospheric CO2 concentration pathway of RCP 8.5 with climate sensitivity varying from 0.0°C to 4.5 °C. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. Our simulations show that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO2-induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO2-induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude, to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change.

  6. Forecasting carbon budget under climate change and CO2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

    USGS Publications Warehouse

    Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

    2011-01-01

    The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr-1 during the last half of the 21st century. An NPP increase of about 24 Mt C by the end of the 21st century was estimated with the combined effects of increasing CO2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr-1. NEP will increase to about 5 Mt C yr-1 by the end of the 21st century with the increasing atmospheric CO2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

  7. Forecasting carbon budget under climate change and CO 2 fertilization for subtropical region in China using integrated biosphere simulator (IBIS) model

    USGS Publications Warehouse

    Zhu, Q.; Jiang, H.; Liu, J.; Peng, C.; Fang, X.; Yu, S.; Zhou, G.; Wei, X.; Ju, W.

    2011-01-01

    The regional carbon budget of the climatic transition zone may be very sensitive to climate change and increasing atmospheric CO 2 concentrations. This study simulated the carbon cycles under these changes using process-based ecosystem models. The Integrated Biosphere Simulator (IBIS), a Dynamic Global Vegetation Model (DGVM), was used to evaluate the impacts of climate change and CO 2 fertilization on net primary production (NPP), net ecosystem production (NEP), and the vegetation structure of terrestrial ecosystems in Zhejiang province (area 101,800 km 2, mainly covered by subtropical evergreen forest and warm-temperate evergreen broadleaf forest) which is located in the subtropical climate area of China. Two general circulation models (HADCM3 and CGCM3) representing four IPCC climate change scenarios (HC3AA, HC3GG, CGCM-sresa2, and CGCM-sresb1) were used as climate inputs for IBIS. Results show that simulated historical biomass and NPP are consistent with field and other modelled data, which makes the analysis of future carbon budget reliable. The results indicate that NPP over the entire Zhejiang province was about 55 Mt C yr -1 during the last half of the 21 st century. An NPP increase of about 24 Mt C by the end of the 21 st century was estimated with the combined effects of increasing CO 2 and climate change. A slight NPP increase of about 5 Mt C was estimated under the climate change alone scenario. Forests in Zhejiang are currently acting as a carbon sink with an average NEP of about 2.5 Mt C yr -1. NEP will increase to about 5 Mt C yr -1 by the end of the 21 st century with the increasing atmospheric CO 2 concentration and climate change. However, climate change alone will reduce the forest carbon sequestration of Zhejiang's forests. Future climate warming will substantially change the vegetation cover types; warm-temperate evergreen broadleaf forest will be gradually substituted by subtropical evergreen forest. An increasing CO 2 concentration will have little contribution to vegetation changes. Simulated NPP shows geographic patterns consistent with temperature to a certain extent, and precipitation is not the limiting factor for forest NPP in the subtropical climate conditions. There is no close relationship between the spatial pattern of NEP and climate condition.

  8. On the limitations of General Circulation Climate Models

    NASA Technical Reports Server (NTRS)

    Stone, Peter H.; Risbey, James S.

    1990-01-01

    General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

  9. Research on the response of the water sources to the climatic change in Shiyang River Basin

    NASA Astrophysics Data System (ADS)

    Jin, Y. Z.; Zeng, J. J.; Hu, X. Q.; Sun, D. Y.; Song, Z. F.; Zhang, Y. L.; Lu, S. C.; Cui, Y. Q.

    2017-08-01

    The influence of the future climate change to the water resource will directly pose some impact on the watershed management planning and administrative strategies of Shiyang River Basin. With the purpose of exploring the influence of climate change to the runoff, this paper set Shiyang River as the study area and then established a SWAT basin hydrological model based on the data such as DEM, land use, soil, climate hydrology and so on. Besides, algorithm of SUFI2 embedded in SWAT-CUP software is adopted. The conclusion shows that SWAT Model can simulate the runoff process of Nanying River well. During the period of model verification and simulation, the runoff Nash-Sutcliffe efficient coefficient of the verification and simulation is 0.76 and 0.72 separately. The relative error between the simulation and actual measurement and the model efficient coefficient are both within the scope of acceptance, which means that the SWAT hydrological model can be properly applied into the runoff simulation of Shiyang River Basin. Meantime, analysis on the response of the water resources to the climate change in Shiyang River Basin indicates that the impact of climate change on runoff is remarkable under different climate change situations and the annual runoff will be greatly decreased as the precipitation falls and the temperature rises. Influence of precipitation to annual runoff is greater than that of temperature. Annual runoff differs obviously under different climate change situations. All in all, this paper tries to provide some technical assistance for the water sources development and utilization assessment and optimal configuration.

  10. Climate change negotiation simulations for students: responses across gender and age.A case study: San Francisco State University World Climate Exercises

    NASA Astrophysics Data System (ADS)

    Rasheva, E. A.

    2015-12-01

    For decades, role-play and simulation exercises have been utilized for learning and policy decision making. While the power of Model UN simulations in building first-person experience and understanding of complex international issues is well known, the effectiveness of simulations for inspiring citizen engagement in scientific public-policy issues is little studied. My work hypothesizes that climate-change negotiation simulations can enhance students' scientific literacy and policy advocacy. It aims to determine how age and gender influence the responsiveness of students to such simulations. During the 2015 fall semester, I am conducting World Climate exercises for fellow graduate and undergraduate students at San Francisco State University. At the end of the exercise, I will have collected the responses to an anonymous questionnaire in which the participants indicate age and gender. The questionnaire asks participants to describe their hopes and fears for the future and to propose public and personal actions for achieving a strong climate change agreement. I am tracking differences to determine whether participants' age and gender correlate with particular patterns of feeling and thinking. My future research will aim to determine whether and how strongly the World Climate Exercise has affected participants' actual policy engagement. This work will also reflect on my experiences as a World Climate facilitator. I will describe the facilitation process and then discuss some of my observations from the sessions. I will specify the challenges I have encountered and suggest strategies that can strengthen the learning process. World Climate is a computer-simulation-based climate change negotiations role-playing exercise developed by Climate Interactive in partnership with the System Dynamics Group at the MIT Sloan School of Management.

  11. Simulating Climate Change in Ireland

    NASA Astrophysics Data System (ADS)

    Nolan, P.; Lynch, P.

    2012-04-01

    At the Meteorology & Climate Centre at University College Dublin, we are using the CLM-Community's COSMO-CLM Regional Climate Model (RCM) and the WRF RCM (developed at NCAR) to simulate the climate of Ireland at high spatial resolution. To address the issue of model uncertainty, a Multi-Model Ensemble (MME) approach is used. The ensemble method uses different RCMs, driven by several Global Climate Models (GCMs), to simulate climate change. Through the MME approach, the uncertainty in the RCM projections is quantified, enabling us to estimate the probability density function of predicted changes, and providing a measure of confidence in the predictions. The RCMs were validated by performing a 20-year simulation of the Irish climate (1981-2000), driven by ECMWF ERA-40 global re-analysis data, and comparing the output to observations. Results confirm that the output of the RCMs exhibit reasonable and realistic features as documented in the historical data record. Projections for the future Irish climate were generated by downscaling the Max Planck Institute's ECHAM5 GCM, the UK Met Office HadGEM2-ES GCM and the CGCM3.1 GCM from the Canadian Centre for Climate Modelling. Simulations were run for a reference period 1961-2000 and future period 2021-2060. The future climate was simulated using the A1B, A2, B1, RCP 4.5 & RCP 8.5 greenhouse gas emission scenarios. Results for the downscaled simulations show a substantial overall increase in precipitation and wind speed for the future winter months and a decrease during the summer months. The predicted annual change in temperature is approximately 1.1°C over Ireland. To date, all RCM projections are in general agreement, thus increasing our confidence in the robustness of the results.

  12. LPJ-GUESS Simulated North America Vegetation for 21-0 ka Using the TraCE-21ka Climate Simulation

    NASA Astrophysics Data System (ADS)

    Shafer, S. L.; Bartlein, P. J.

    2016-12-01

    Transient climate simulations that span multiple millennia (e.g., TraCE-21ka) have become more common as computing power has increased, allowing climate models to complete long simulations in relatively short periods of time (i.e., months). These climate simulations provide information on the potential rate, variability, and spatial expression of past climate changes. They also can be used as input data for other environmental models to simulate transient changes for different components of paleoenvironmental systems, such as vegetation. Long, transient paleovegetation simulations can provide information on a range of ecological processes, describe the spatial and temporal patterns of changes in species distributions, and identify the potential locations of past species refugia. Paleovegetation simulations also can be used to fill in spatial and temporal gaps in observed paleovegetation data (e.g., pollen records from lake sediments) and to test hypotheses of past vegetation change. We used the TraCE-21ka transient climate simulation for 21-0 ka from CCSM3, a coupled atmosphere-ocean general circulation model. The TraCE-21ka simulated temperature, precipitation, and cloud data were regridded onto a 10-minute grid of North America. These regridded climate data, along with soil data and atmospheric carbon dioxide concentrations, were used as input to LPJ-GUESS, a general ecosystem model, to simulate North America vegetation from 21-0 ka. LPJ-GUESS simulates many of the processes controlling the distribution of vegetation (e.g., competition), although some important processes (e.g., dispersal) are not simulated. We evaluate the LPJ-GUESS-simulated vegetation (in the form of plant functional types and biomes) for key time periods and compare the simulated vegetation with observed paleovegetation data, such as data archived in the Neotoma Paleoecology Database. In general, vegetation simulated by LPJ-GUESS reproduces the major North America vegetation patterns (e.g., forest, grassland) with regional areas of disagreement between simulated and observed vegetation. We describe the regions and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of both the simulated climate and simulated vegetation data.

  13. Serious Simulation Role-Playing Games for Transformative Climate Change Education: "World Climate" and "Future Climate"

    NASA Astrophysics Data System (ADS)

    Rooney-Varga, J. N.; Sterman, J.; Sawin, E.; Jones, A.; Merhi, H.; Hunt, C.

    2012-12-01

    Climate change, its mitigation, and adaption to its impacts are among the greatest challenges of our times. Despite the importance of societal decisions in determining climate change outcomes, flawed mental models about climate change remain widespread, are often deeply entrenched, and present significant barriers to understanding and decision-making around climate change. Here, we describe two simulation role-playing games that combine active, affective, and analytical learning to enable shifts of deeply held conceptions about climate change. The games, World Climate and Future Climate, use a state-of-the-art decision support simulation, C-ROADS (Climate Rapid Overview and Decision Support) to provide users with immediate feedback on the outcomes of their mitigation strategies at the national level, including global greenhouse gas (GHG) emissions and concentrations, mean temperature changes, sea level rise, and ocean acidification. C-ROADS outcomes are consistent with the atmosphere-ocean general circulation models (AOGCMS), such as those used by the IPCC, but runs in less than one second on ordinary laptops, providing immediate feedback to participants on the consequences of their proposed policies. Both World Climate and Future Climate role-playing games provide immersive, situated learning experiences that motivate active engagement with climate science and policy. In World Climate, participants play the role of United Nations climate treaty negotiators. Participant emissions reductions proposals are continually assessed through interactive exploration of the best available science through C-ROADS. Future Climate focuses on time delays in the climate and energy systems. Participants play the roles of three generations: today's policymakers, today's youth, and 'just born.' The game unfolds in three rounds 25 simulated years apart. In the first round, only today's policymakers make decisions; In the next round, the young become the policymakers and inherit the results of the earlier decisions, as simulated by C-ROADS. Preliminary evaluations show that both exercises have the potential to provide powerful learning experiences. University students who played World Climate in a climate change course cited it as one of the course activities "promoting the most learning." Students' responses on anonymous surveys and open-ended questions revealed that the experience affected them at visceral, as well as intellectual levels. All of the students recommended that the exercise be continued in future years and many felt that it was the most important learning experience of the semester. Similarly, understanding of climate change and the dynamics of the climate improved for the majority of Future Climate participants, and 90% of participants stated that they were more likely to take action to address climate change on a personal level because of their experience.

  14. Evaluating the effects of climate change on summertime ozone using a relative response factor approach for policymakers.

    PubMed

    Avise, Jeremy; Abraham, Rodrigo Gonzalez; Chung, Serena H; Chen, Jack; Lamb, Brian; Salathé, Eric P; Zhang, Yongxin; Nolte, Christopher G; Loughlin, Daniel H; Guenther, Alex; Wiedinmyer, Christine; Duhl, Tiffany

    2012-09-01

    The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRF(E)), which estimates the relative change in peak ozone concentration for a given change in pollutant emissions (the subscript E is added to RRF to remind the reader that the RRF is due to emission changes only). A matrix of model simulations was conducted to examine the individual and combined effects offuture anthropogenic emissions, biogenic emissions, and climate on the RRF(E). For each member in the matrix of simulations the warmest and coolest summers were modeled for the present-day (1995-2004) and future (2045-2054) decades. A climate adjustment factor (CAF(C) or CAF(CB) when biogenic emissions are allowed to change with the future climate) was defined as the ratio of the average daily maximum 8-hr ozone simulated under a future climate to that simulated under the present-day climate, and a climate-adjusted RRF(EC) was calculated (RRF(EC) = RRF(E) x CAF(C)). In general, RRF(EC) > RRF(E), which suggests additional emission controls will be required to achieve the same reduction in ozone that would have been achieved in the absence of climate change. Changes in biogenic emissions generally have a smaller impact on the RRF(E) than does future climate change itself The direction of the biogenic effect appears closely linked to organic-nitrate chemistry and whether ozone formation is limited by volatile organic compounds (VOC) or oxides of nitrogen (NO(x) = NO + NO2). Regions that are generally NO(x) limited show a decrease in ozone and RRF(EC), while VOC-limited regions show an increase in ozone and RRF(EC). Comparing results to a previous study using different climate assumptions and models showed large variability in the CAF(CB). We present a methodology for adjusting the RRF to account for the influence of climate change on ozone. The findings of this work suggest that in some geographic regions, climate change has the potential to negate decreases in surface ozone concentrations that would otherwise be achieved through ozone mitigation strategies. In regions of high biogenic VOC emissions relative to anthropogenic NO(x) emissions, the impact of climate change is somewhat reduced, while the opposite is true in regions of high anthropogenic NO(x) emissions relative to biogenic VOC emissions. Further, different future climate realizations are shown to impact ozone in different ways.

  15. Potential effects of climate change on streamflow, eastern and western slopes of the Sierra Nevada, California and Nevada

    USGS Publications Warehouse

    Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue

    1996-01-01

    Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.

  16. Climate changes and wildfire alter vegetation of Yellowstone National Park, but forest cover persists

    USGS Publications Warehouse

    Clark, Jason A.; Loehman, Rachel A.; Keane, Robert E.

    2017-01-01

    We present landscape simulation results contrasting effects of changing climates on forest vegetation and fire regimes in Yellowstone National Park, USA, by mid-21st century. We simulated potential changes to fire dynamics and forest characteristics under three future climate projections representing a range of potential future conditions using the FireBGCv2 model. Under the future climate scenarios with moderate warming (>2°C) and moderate increases in precipitation (3–5%), model simulations resulted in 1.2–4.2 times more burned area, decreases in forest cover (10–44%), and reductions in basal area (14–60%). In these same scenarios, lodgepole pine (Pinus contorta) decreased in basal area (18–41%), while Douglas-fir (Pseudotsuga menziesii) basal area increased (21–58%). Conversely, mild warming (<2°C) coupled with greater increases in precipitation (12–13%) suggested an increase in forest cover and basal area by mid-century, with spruce and subalpine fir increasing in abundance. Overall, we found changes in forest tree species compositions were caused by the climate-mediated changes in fire regime (56–315% increase in annual area burned). Simulated changes in forest composition and fire regime under warming climates portray a landscape that shifts from lodgepole pine to Douglas-fir caused by the interaction between the magnitude and seasonality of future climate changes, by climate-induced changes in the frequency and intensity of wildfires, and by tree species response.

  17. Transient simulations of historical climate change including interactive carbon emissions from land-use change.

    NASA Astrophysics Data System (ADS)

    Matveev, A.; Matthews, H. D.

    2009-04-01

    Carbon fluxes from land conversion are among the most uncertain variables in our understanding of the contemporary carbon cycle, which limits our ability to estimate both the total human contribution to current climate forcing and the net effect of terrestrial biosphere changes on atmospheric CO2 increases. The current generation of coupled climate-carbon models have made significant progress in simulating the coupled climate and carbon cycle response to anthropogenic CO2 emissions, but do not typically include land-use change as a dynamic component of the simulation. In this work we have incorporated a book-keeping land-use carbon accounting model into the University of Victoria Earth System Climate Model (UVic ESCM), and intermediate-complexity coupled climate-carbon model. The terrestrial component of the UVic ESCM allows an aerial competition of five plant functional types (PFTs) in response to climatic conditions and area availability, and tracks the associated changes in affected carbon pools. In order to model CO2 emissions from land conversion in the terrestrial component of the model, we calculate the allocation of carbon to short and long-lived wood products following specified land-cover change, and use varying decay timescales to estimate CO2 emissions. We use recently available spatial datasets of both crop and pasture distributions to drive a series of transient simulations and estimate the net contribution of human land-use change to historical carbon emissions and climate change.

  18. Changes in Concurrent Precipitation and Temperature Extremes

    DOE PAGES

    Hao, Zengchao; AghaKouchak, Amir; Phillips, Thomas J.

    2013-08-01

    While numerous studies have addressed changes in climate extremes, analyses of concurrence of climate extremes are scarce, and climate change effects on joint extremes are rarely considered. This study assesses the occurrence of joint (concurrent) monthly continental precipitation and temperature extremes in Climate Research Unit (CRU) and University of Delaware (UD) observations, and in 13 Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate simulations. Moreover, the joint occurrences of precipitation and temperature extremes simulated by CMIP5 climate models are compared with those derived from the CRU and UD observations for warm/wet, warm/dry, cold/wet, and cold/dry combinations of joint extremes.more » The number of occurrences of these four combinations during the second half of the 20th century (1951–2004) is assessed on a common global grid. CRU and UD observations show substantial increases in the occurrence of joint warm/dry and warm/wet combinations for the period 1978–2004 relative to 1951–1977. The results show that with respect to the sign of change in the concurrent extremes, the CMIP5 climate model simulations are in reasonable overall agreement with observations. The results reveal notable discrepancies between regional patterns and the magnitude of change in individual climate model simulations relative to the observations of precipitation and temperature.« less

  19. Combined top-down and bottom-up climate change impact assessment for the hydrological system in the Vu Gia- Thu Bon River Basin.

    PubMed

    Tra, Tran Van; Thinh, Nguyen Xuan; Greiving, Stefan

    2018-07-15

    Vu Gia- Thu Bon (VGTB) River Basin, located in the Central Coastal zone of Viet Nam currently faces water shortage. Climate change is expected to exacerbate the challenge. Therefore, there is a need to study the impacts of climate change on water shortage in the river basin. The study adopts a combined top-down and bottom-up climate change impact assessment to address the impacts of climate change on water shortage in the VGTB River Basin. A MIKE BASIN water balance model for the river basin was established to simulate the response of the hydrological system. Simulations were performed through parametrically varying temperature and precipitation to determine the vulnerability space of water shortage. General Circulation Models (GCMs) were then utilized to provide climate projections for the river basin. The output from GCMs was then mapped onto the vulnerability space determined earlier. In total, 9 out of 55 water demand nodes in the simulation are expected to face problematic conditions as future climate changes. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Effects of global climate change on the US forest sector: response functions derived from a dynamic resource and market simulator.

    Treesearch

    Bruce A. McCarl; Darius M. Adams; Ralph J. Alig; Diana Burton; Chi-Chung. Chen

    2000-01-01

    A multiperiod, regional, mathematical programming economic model is used to evaluate the potential economic impacts of global climatic change on the US forest sector. A wide range of scenarios for the biological response of forests to climate change are developed, ranging from small to large changes in forest growth rates. These scenarios are simulated in the economic...

  1. Building an ensemble of climate scenarios for decision-making in hydrology: benefits, pitfalls and uncertainties

    NASA Astrophysics Data System (ADS)

    Braun, Marco; Chaumont, Diane

    2013-04-01

    Using climate model output to explore climate change impacts on hydrology requires several considerations, choices and methods in the post treatment of the datasets. In the effort of producing a comprehensive data base of climate change scenarios for over 300 watersheds in the Canadian province of Québec, a selection of state of the art procedures were applied to an ensemble comprising 87 climate simulations. The climate data ensemble is based on global climate simulations from the Coupled Model Intercomparison Project - Phase 3 (CMIP3) and regional climate simulations from the North American Regional Climate Change Assessment Program (NARCCAP) and operational simulations produced at Ouranos. Information on the response of hydrological systems to changing climate conditions can be derived by linking climate simulations with hydrological models. However, the direct use of raw climate model output variables as drivers for hydrological models is limited by issues such as spatial resolution and the calibration of hydro models with observations. Methods for downscaling and bias correcting the data are required to achieve seamless integration of climate simulations with hydro models. The effects on the results of four different approaches to data post processing were explored and compared. We present the lessons learned from building the largest data base yet for multiple stakeholders in the hydro power and water management sector in Québec putting an emphasis on the benefits and pitfalls in choosing simulations, extracting the data, performing bias corrections and documenting the results. A discussion of the sources and significance of uncertainties in the data will also be included. The climatological data base was subsequently used by the state owned hydro power company Hydro-Québec and the Centre d'expertise hydrique du Québec (CEHQ), the provincial water authority, to simulate future stream flows and analyse the impacts on hydrological indicators. While this submission focuses on the production of climatic scenarios for application in hydrology, the submission « The (cQ)2 project: assessing watershed scale hydrological changes for the province of Québec at the 2050 horizon, a collaborative framework » by Catherine Guay describes how Hydro-Québec and CEHQ put the data into use.

  2. An effective online data monitoring and saving strategy for large-scale climate simulations

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

    Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin

    Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

  3. An effective online data monitoring and saving strategy for large-scale climate simulations

    DOE PAGES

    Xian, Xiaochen; Archibald, Rick; Mayer, Benjamin; ...

    2018-01-22

    Large-scale climate simulation models have been developed and widely used to generate historical data and study future climate scenarios. These simulation models often have to run for a couple of months to understand the changes in the global climate over the course of decades. This long-duration simulation process creates a huge amount of data with both high temporal and spatial resolution information; however, how to effectively monitor and record the climate changes based on these large-scale simulation results that are continuously produced in real time still remains to be resolved. Due to the slow process of writing data to disk,more » the current practice is to save a snapshot of the simulation results at a constant, slow rate although the data generation process runs at a very high speed. This study proposes an effective online data monitoring and saving strategy over the temporal and spatial domains with the consideration of practical storage and memory capacity constraints. Finally, our proposed method is able to intelligently select and record the most informative extreme values in the raw data generated from real-time simulations in the context of better monitoring climate changes.« less

  4. Regional Climate Models as a Tool for Assessing Changes in the Laurentian Great Lakes Net Basin Supply

    NASA Astrophysics Data System (ADS)

    Music, B.; Mailhot, E.; Nadeau, D.; Irambona, C.; Frigon, A.

    2017-12-01

    Over the last decades, there has been growing concern about the effects of climate change on the Great Lakes water supply. Most of the modelling studies focusing on the Laurentian Great Lakes do not allow two-way exchanges of water and energy between the atmosphere and the underlying surface, and therefore do not account for important feedback mechanisms. Moreover, energy budget constraint at the land surface is not usually taken into account. To address this issue, several recent climate change studies used high resolution Regional Climate Models (RCMs) for evaluating changes in the hydrological regime of the Great Lakes. As RCMs operate on the concept of water and energy conservation, an internal consistency of the simulated energy and water budget components is assured. In this study we explore several recently generated Regional Climate Model (RCM) simulations to investigate the Great Lakes' Net Basin Supply (NBS) in a changing climate. These include simulations of the Canadian Regional Climate Model (CRCM5) supplemented by simulations from several others RCMs participating to the North American CORDEX project (CORDEX-NA). The analysis focuses on the NBS extreme values under nonstationary conditions. The results are expected to provide useful information to the industries in the Great Lakes that all need to include accurate climate change information in their long-term strategy plans to better anticipate impacts of low and/or high water levels.

  5. Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

    NASA Astrophysics Data System (ADS)

    Wakazuki, Y.

    2015-12-01

    A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

  6. Changes in U.S. Regional-Scale Air Quality at 2030 Simulated Using RCP 6.0

    NASA Astrophysics Data System (ADS)

    Nolte, C. G.; Otte, T.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

    2012-12-01

    Recent improvements in air quality in the United States have been due to significant reductions in emissions of ozone and particulate matter (PM) precursors, and these downward emissions trends are expected to continue in the next few decades. To ensure that planned air quality regulations are robust under a range of possible future climates and to consider possible policy actions to mitigate climate change, it is important to characterize and understand the effects of climate change on air quality. Recent work by several research groups using global and regional models has demonstrated that there is a "climate penalty," in which climate change leads to increases in surface ozone levels in polluted continental regions. One approach to simulating future air quality at the regional scale is via dynamical downscaling, in which fields from a global climate model are used as input for a regional climate model, and these regional climate data are subsequently used for chemical transport modeling. However, recent studies using this approach have encountered problems with the downscaled regional climate fields, including unrealistic surface temperatures and misrepresentation of synoptic pressure patterns such as the Bermuda High. We developed a downscaling methodology and showed that it now reasonably simulates regional climate by evaluating it against historical data. In this work, regional climate simulations created by downscaling the NASA/GISS Model E2 global climate model are used as input for the Community Multiscale Air Quality (CMAQ) model. CMAQ simulations over the continental United States are conducted for two 11-year time slices, one representing current climate (1995-2005) and one following Representative Concentration Pathway 6.0 from 2025-2035. Anthropogenic emissions of ozone and PM precursors are held constant at year 2006 levels for both the current and future periods. In our presentation, we will examine the changes in ozone and PM concentrations, with particular focus on exceedances of the current U.S. air quality standards, and attempt to relate the changes in air quality to the projected changes in regional climate.

  7. Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

    USGS Publications Warehouse

    Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

    2015-01-01

    Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

  8. Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

    PubMed Central

    Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

    2015-01-01

    Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

  9. Climate Change Signals in the EURO-CORDEX Simulations

    NASA Astrophysics Data System (ADS)

    Jacob, Daniela; Preuschmann, Swantje

    2014-05-01

    A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. Within this presentation, the first results on climate change signals based on simulations with a horizontal resolution of 12.5 km for the new emission scenarios RCP4.5 and RCP8.5 will be presented. The new EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The presentation is based on the results of the Paper JACOB et al. (2013). We concentrated on the statistical analysis of robustness and significance of the climate change signals for mean annual and seasonal temperature, total annual and seasonal precipitation, heavy precipitation, heat waves and dry spells, by using daily data for three time periods: 1971-2000, 2021-2050 and 2071-2100. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities. The analysis of projected changes in the 95th percentile of the mean length of dry spells shows similar patterns for all scenarios. The climate projections from the new ensemble indicate a reduced northwards shift of Mediterranean drying evolution and slightly stronger mean precipitation increases over most of Europe. Within the high-resolution simulations in the EURO-CORDEX changes of the pattern for heavy precipitation events are clearly visible. (Jacob2013) Jacob, D.; Petersen, J.; Eggert, B.; Alias, A.; Christensen, O. B.; Bouwer, L.; Braun, A.; Colette, A.; Déqué, M.; Georgievski, G.; Georgopoulou, E.; Gobiet, A.; Menut, L.; Nikulin, G.; Haensler, A.; Hempelmann, N.; Jones, C.; Keuler, K.; Kovats, S.; Kröner, N.; Kotlarski, S.; Kriegsmann, A.; Martin, E.; Meijgaard, E.; Moseley, C.; Pfeifer, S.; Preuschmann, S.; Radermacher, C.; Radtke, K.; Rechid, D.; Rounsevell, M.; Samuelsson, P.; Somot, S.; Soussana, J.-F.; Teichmann, C.; Valentini, R.; Vautard, R.; Weber, B. & Yiou, P.( 2013): EURO-CORDEX: new high-resolution climate change projections for European impact research Regional Environmental Change, Springer Berlin Heidelberg, 2013, 1-16.

  10. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming

    NASA Astrophysics Data System (ADS)

    Betts, R. A.; Cox, P. M.; Collins, M.; Harris, P. P.; Huntingford, C.; Jones, C. D.

    A suite of simulations with the HadCM3LC coupled climate-carbon cycle model is used to examine the various forcings and feedbacks involved in the simulated precipitation decrease and forest dieback. Rising atmospheric CO2 is found to contribute 20% to the precipitation reduction through the physiological forcing of stomatal closure, with 80% of the reduction being seen when stomatal closure was excluded and only radiative forcing by CO2 was included. The forest dieback exerts two positive feedbacks on the precipitation reduction; a biogeophysical feedback through reduced forest cover suppressing local evaporative water recycling, and a biogeochemical feedback through the release of CO2 contributing to an accelerated global warming. The precipitation reduction is enhanced by 20% by the biogeophysical feedback, and 5% by the carbon cycle feedback from the forest dieback. This analysis helps to explain why the Amazonian precipitation reduction simulated by HadCM3LC is more extreme than that simulated in other GCMs; in the fully-coupled, climate-carbon cycle simulation, approximately half of the precipitation reduction in Amazonia is attributable to a combination of physiological forcing and biogeophysical and global carbon cycle feedbacks, which are generally not included in other GCM simulations of future climate change. The analysis also demonstrates the potential contribution of regional-scale climate and ecosystem change to uncertainties in global CO2 and climate change projections. Moreover, the importance of feedbacks suggests that a human-induced increase in forest vulnerability to climate change may have implications for regional and global scale climate sensitivity.

  11. Past climates primary productivity changes in the Indian Ocean

    NASA Astrophysics Data System (ADS)

    Le Mézo, P. K.; Kageyama, M.; Bopp, L.; Beaufort, L.; Braconnot, P.; Bassinot, F. C.

    2016-02-01

    Organic climate recorders, e.g., coccolithophorids and foraminifera, are widely used to reconstruct past climate conditions, such as the Indian monsoon intensity and variability, since they are sensitive to climate-induced fluctuations of their environment. In the Indian Ocean, it is commonly accepted that a stronger summer monsoon will enhance productivity in the Arabian Sea and therefore the amount of organisms in a sediment core should reflect monsoon intensity. In this study, we use the coupled Earth System Model IPSLCM5A, which has a biogeochemical component PISCES that simulates primary production. We use 8 climate simulations of the IPSL-CM5A model, from -72kyr BP climate conditions to a preindustrial state. Our simulations have different orbital forcing (precession, obliquity and eccentricity), greenhouse gas concentrations as well as different ice sheet covers. The objective of this work is to characterize the mechanisms behind the changes in primary productivity between the different time periods. Our model shows that in climates where monsoon is enhanced (due to changes in precession) we do not necessarily see an increase in summer productivity in the Arabian Sea, and inversely. It seems that the glacial-interglacial state of the simulation is important in driving productivity changes in this region of the world. We try to explain the changes in productivity in the Arabian Sea with the local climate and then to link the changes in local climate to large scale atmospheric forcing and commonly used Indian monsoon definitions.

  12. Understanding the science of climate change: Talking points - Impacts to Prairie Potholes and Grasslands

    Treesearch

    Rachel Loehman

    2009-01-01

    Climate changes in the Prairie Potholes and Grasslands bioregion include increased seasonal, annual, minimum, and maximum temperature and changing precipitation patterns. Because the region is relatively dry with a strong seasonal climate, it is sensitive to climatic changes and vulnerable to changes in climatic regime. For example, model simulations show that regional...

  13. Climate change and watershed mercury export: a multiple projection and model analysis

    USGS Publications Warehouse

    Golden, Heather E.; Knightes, Christopher D.; Conrads, Paul; Feaster, Toby D.; Davis, Gary M.; Benedict, Stephen T.; Bradley, Paul M.

    2013-01-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling.

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

    Voigt, Aiko; Biasutti, Michela; Scheff, Jacob

    This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

  15. Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 7. Economic Analysis of Field Crops and Land Use with Climate Change

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

    Sands, Ronald D.; Edmonds, James A.

    PNNL's Agriculture and Land Use (AgLU) model is used to demonstrate the impact of potential changes in climate on agricultural production and land use in the United States. AgLU simulates production of four crop types in several world regions, in 15-year time steps from 1990 to 2095. Changes in yield of major field crops in the United States, for 12 climate scenarios, are obtained from simulations of the EPIC crop growth model. Results from the HUMUS model are used to constrain crop irrigation, and the BIOME3 model is used to simulate productivity of unmanaged ecosystems. Assumptions about changes in agriculturalmore » productivity outside the United States are treated on a scenario basis, either responding in the same way as in the United States, or not responding to climate.« less

  16. The response of land-falling tropical cyclone characteristics to projected climate change in northeast Australia

    NASA Astrophysics Data System (ADS)

    Parker, Chelsea L.; Bruyère, Cindy L.; Mooney, Priscilla A.; Lynch, Amanda H.

    2018-01-01

    Land-falling tropical cyclones along the Queensland coastline can result in serious and widespread damage. However, the effects of climate change on cyclone characteristics such as intensity, trajectory, rainfall, and especially translation speed and size are not well-understood. This study explores the relative change in the characteristics of three case studies by comparing the simulated tropical cyclones under current climate conditions with simulations of the same systems under future climate conditions. Simulations are performed with the Weather Research and Forecasting Model and environmental conditions for the future climate are obtained from the Community Earth System Model using a pseudo global warming technique. Results demonstrate a consistent response of increasing intensity through reduced central pressure (by up to 11 hPa), increased wind speeds (by 5-10% on average), and increased rainfall (by up to 27% for average hourly rainfall rates). The responses of other characteristics were variable and governed by either the location and trajectory of the current climate cyclone or the change in the steering flow. The cyclone that traveled furthest poleward encountered a larger climate perturbation, resulting in a larger proportional increase in size, rainfall rate, and wind speeds. The projected monthly average change in the 500 mb winds with climate change governed the alteration in the both the trajectory and translation speed for each case. The simulated changes have serious implications for damage to coastal settlements, infrastructure, and ecosystems through increased wind speeds, storm surge, rainfall, and potentially increased size of some systems.

  17. Climate change streamflow scenarios designed for critical period water resources planning studies

    NASA Astrophysics Data System (ADS)

    Hamlet, A. F.; Snover, A. K.; Lettenmaier, D. P.

    2003-04-01

    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.

  18. Wintertime urban heat island modified by global climate change over Japan

    NASA Astrophysics Data System (ADS)

    Hara, M.

    2015-12-01

    Urban thermal environment change, especially, surface air temperature (SAT) rise in metropolitan areas, is one of the major recent issues in urban areas. The urban thermal environmental change affects not only human health such as heat stroke, but also increasing infectious disease due to spreading out virus vectors habitat and increase of industry and house energy consumption. The SAT rise is mostly caused by global climate change and urban heat island (hereafter UHI) by urbanization. The population in Tokyo metropolitan area is over 30 millions and the Tokyo metropolitan area is one of the biggest megacities in the world. The temperature rise due to urbanization seems comparable to the global climate change in the major megacities. It is important to project how the urbanization and the global climate change affect to the future change of urban thermal environment to plan the adaptation and mitigation policy. To predict future SAT change in urban scale, we should estimate future UHI modified by the global climate change. This study investigates change in UHI intensity (UHII) of major metropolitan areas in Japan by effects of the global climate change. We performed a series of climate simulations. Present climate simulations with and without urban process are conducted for ten seasons using a high-resolution numerical climate model, the Weather Research and Forecasting (WRF) model. Future climate projections with and without urban process are also conducted. The future projections are performed using the pseudo global warming method, assuming 2050s' initial and boundary conditions estimated by a GCM under the RCP scenario. Simulation results indicated that UHII would be enhanced more than 30% in Tokyo during the night due to the global climate change. The enhancement of urban heat island is mostly caused by change of lower atmospheric stability.

  19. Rapid genetic divergence in response to 15 years of simulated climate change.

    PubMed

    Ravenscroft, Catherine H; Whitlock, Raj; Fridley, Jason D

    2015-11-01

    Genetic diversity may play an important role in allowing individual species to resist climate change, by permitting evolutionary responses. Our understanding of the potential for such responses to climate change remains limited, and very few experimental tests have been carried out within intact ecosystems. Here, we use amplified fragment length polymorphism (AFLP) data to assess genetic divergence and test for signatures of evolutionary change driven by long-term simulated climate change applied to natural grassland at Buxton Climate Change Impacts Laboratory (BCCIL). Experimental climate treatments were applied to grassland plots for 15 years using a replicated and spatially blocked design and included warming, drought and precipitation treatments. We detected significant genetic differentiation between climate change treatments and control plots in two coexisting perennial plant study species (Festuca ovina and Plantago lanceolata). Outlier analyses revealed a consistent signature of selection associated with experimental climate treatments at individual AFLP loci in P. lanceolata, but not in F. ovina. Average background differentiation at putatively neutral AFLP loci was close to zero, and genomewide genetic structure was associated neither with species abundance changes (demography) nor with plant community-level responses to long-term climate treatments. Our results demonstrate genetic divergence in response to a suite of climatic environments in reproductively mature populations of two perennial plant species and are consistent with an evolutionary response to climatic selection in P. lanceolata. These genetic changes have occurred in parallel with impacts on plant community structure and may have contributed to the persistence of individual species through 15 years of simulated climate change at BCCIL. © 2015 The Authors. Global Change Biology Bioenergy Published by John Wiley & Sons Ltd.

  20. An integrated assessment modeling framework for uncertainty studies in global and regional climate change: the MIT IGSM-CAM (version 1.0)

    NASA Astrophysics Data System (ADS)

    Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

    2013-12-01

    This paper describes a computationally efficient framework for uncertainty studies in global and regional climate change. In this framework, the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity to a human activity model, is linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). Since the MIT IGSM-CAM framework (version 1.0) incorporates a human activity model, it is possible to analyze uncertainties in emissions resulting from both uncertainties in the underlying socio-economic characteristics of the economic model and in the choice of climate-related policies. Another major feature is the flexibility to vary key climate parameters controlling the climate system response to changes in greenhouse gases and aerosols concentrations, e.g., climate sensitivity, ocean heat uptake rate, and strength of the aerosol forcing. The IGSM-CAM is not only able to realistically simulate the present-day mean climate and the observed trends at the global and continental scale, but it also simulates ENSO variability with realistic time scales, seasonality and patterns of SST anomalies, albeit with stronger magnitudes than observed. The IGSM-CAM shares the same general strengths and limitations as the Coupled Model Intercomparison Project Phase 3 (CMIP3) models in simulating present-day annual mean surface temperature and precipitation. Over land, the IGSM-CAM shows similar biases to the NCAR Community Climate System Model (CCSM) version 3, which shares the same atmospheric model. This study also presents 21st century simulations based on two emissions scenarios (unconstrained scenario and stabilization scenario at 660 ppm CO2-equivalent) similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios, and three sets of climate parameters. Results of the simulations with the chosen climate parameters provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century changes in global mean surface air temperature from previous work with the IGSM. Because the IGSM-CAM framework only considers one particular climate model, it cannot be used to assess the structural modeling uncertainty arising from differences in the parameterization suites of climate models. However, comparison of the IGSM-CAM projections with simulations of 31 CMIP5 models under the RCP4.5 and RCP8.5 scenarios show that the range of warming at the continental scale shows very good agreement between the two ensemble simulations, except over Antarctica, where the IGSM-CAM overestimates the warming. This demonstrates that by sampling the climate system response, the IGSM-CAM, even though it relies on one single climate model, can essentially reproduce the range of future continental warming simulated by more than 30 different models. Precipitation changes projected in the IGSM-CAM simulations and the CMIP5 multi-model ensemble both display a large uncertainty at the continental scale. The two ensemble simulations show good agreement over Asia and Europe. However, the ranges of precipitation changes do not overlap - but display similar size - over Africa and South America, two continents where models generally show little agreement in the sign of precipitation changes and where CCSM3 tends to be an outlier. Overall, the IGSM-CAM provides an efficient and consistent framework to explore the large uncertainty in future projections of global and regional climate change associated with uncertainty in the climate response and projected emissions.

  1. On the Value of Climate Elasticity Indices to Assess the Impact of Climate Change on Streamflow Projection using an ensemble of bias corrected CMIP5 dataset

    NASA Astrophysics Data System (ADS)

    Demirel, Mehmet; Moradkhani, Hamid

    2015-04-01

    Changes in two climate elasticity indices, i.e. temperature and precipitation elasticity of streamflow, were investigated using an ensemble of bias corrected CMIP5 dataset as forcing to two hydrologic models. The Variable Infiltration Capacity (VIC) and the Sacramento Soil Moisture Accounting (SAC-SMA) hydrologic models, were calibrated at 1/16 degree resolution and the simulated streamflow was routed to the basin outlet of interest. We estimated precipitation and temperature elasticity of streamflow from: (1) observed streamflow; (2) simulated streamflow by VIC and SAC-SMA models using observed climate for the current climate (1963-2003); (3) simulated streamflow using simulated climate from 10 GCM - CMIP5 dataset for the future climate (2010-2099) including two concentration pathways (RCP4.5 and RCP8.5) and two downscaled climate products (BCSD and MACA). The streamflow sensitivity to long-term (e.g., 30-year) average annual changes in temperature and precipitation is estimated for three periods i.e. 2010-40, 2040-70 and 2070-99. We compared the results of the three cases to reflect on the value of precipitation and temperature indices to assess the climate change impacts on Columbia River streamflow. Moreover, these three cases for two models are used to assess the effects of different uncertainty sources (model forcing, model structure and different pathways) on the two climate elasticity indices.

  2. Simulated Hydrologic Responses to Climate Variations and Change in the Merced, Carson, and American River Basins, Sierra Nevada, California, 1900-2099

    NASA Astrophysics Data System (ADS)

    Dettinger, M. D.; Cayan, D. R.; Cayan, D. R.; Meyer, M. K.

    2001-12-01

    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.

  3. Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

    NASA Astrophysics Data System (ADS)

    Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

    2015-04-01

    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.

  4. Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

    PubMed Central

    Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.

    2015-01-01

    Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478

  5. Local variability mediates vulnerability of trout populations to land use and climate change

    USGS Publications Warehouse

    Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.

    2015-01-01

    Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

  6. Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

    PubMed

    Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E

    2015-01-01

    Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

  7. Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

    NASA Astrophysics Data System (ADS)

    Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

    2014-12-01

    Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

  8. Interactive Nature of Climate Change and Aerosol Forcing

    NASA Technical Reports Server (NTRS)

    Nazarenko, L.; Rind, D.; Tsigaridis, K.; Del Genio, A. D.; Kelley, M.; Tausnev, N.

    2017-01-01

    The effect of changing cloud cover on climate, based on cloud-aerosol interactions, is one of the major unknowns for climate forcing and climate sensitivity. It has two components: (1) the impact of aerosols on clouds and climate due to in-situ interactions (i.e., rapid response); and (2) the effect of aerosols on the cloud feedback that arises as climate changes - climate feedback response. We examine both effects utilizing the NASA GISS ModelE2 to assess the indirect effect, with both mass-based and microphysical aerosol schemes, in transient twentieth-century simulations. We separate the rapid response and climate feedback effects by making simulations with a coupled version of the model as well as one with no sea surface temperature or sea ice response (atmosphere-only simulations). We show that the indirect effect of aerosols on temperature is altered by the climate feedbacks following the ocean response, and this change differs depending upon which aerosol model is employed. Overall the effective radiative forcing (ERF) for the direct effect of aerosol-radiation interaction (ERFari) ranges between -0.2 and -0.6 W/sq m for atmosphere-only experiments while the total effective radiative forcing, including the indirect effect (ERFari+aci) varies between about -0.4 and -1.1 W/sq m for atmosphere-only simulations; both ranges are in agreement with those given in IPCC (2013). Including the full feedback of the climate system lowers these ranges to -0.2 to -0.5 W/sq m for ERFari, and -0.3 to -0.74 W/sq m for ERFari+aci. With both aerosol schemes, the climate change feedbacks have reduced the global average indirect radiative effect of atmospheric aerosols relative to what the emission changes would have produced, at least partially due to its effect on tropical upper tropospheric clouds.

  9. Characterizing the "Time of Emergence" of Air Quality Climate Penalties

    NASA Astrophysics Data System (ADS)

    Rothenberg, D. A.; Garcia-Menendez, F.; Monier, E.; Solomon, S.; Selin, N. E.

    2017-12-01

    By driving not only local changes in temperature, but also precipitation and regional-scale changes in seasonal circulation patterns, climate change can directly and indirectly influence changes in air quality and its extremes. These changes - often referred to as "climate penalties" - can have important implications for human health, which is often targeted when assessing the potential co-benefits of climate policy. But because climate penalties are driven by slow, spatially-varying, temporal changes in the climate system, their emergence in the real world should also have a spatio-temporal component following regional variability in background air quality. In this work, we attempt to estimate the spatially-varying "time of emergence" of climate penalty signals by using an ensemble modeling framework based on the MIT Integrated Global System Model (MIT IGSM). With this framework we assess three climate policy scenarios assuming three different underlying climate sensitivities, and conduct a 5-member ensemble for each case to capture internal variability within the model. These simulations are used to drive offline chemical transport modeling (using CAM-Chem and GEOS-Chem). In these simulations, we find that the air quality response to climate change can vary dramatically across different regions of the globe. To analyze these regionally-varying climate signals, we employ a hierarchical clustering technique to identify regions with similar seasonal patterns of air quality change. Our simulations suggest that the earliest emergence of ozone climate penalties would occur in Southern Europe (by 2035), should the world neglect climate change and rely on a "business-as-usual" emissions policy. However, even modest climate policy dramatically pushes back the time of emergence of these penalties - to beyond 2100 - across most of the globe. The emergence of climate-forced changes in PM2.5 are much more difficult to detect, partially owing to the large role that changes in the frequency and spatial distribution of precipitation play in limiting the accumulation and duration of particulate pollution episodes.

  10. Multi-millennia simulation of Greenland deglaciation from the Max-Plank-Institute Model (MPI-ISM) 2xCO2 simulation

    NASA Astrophysics Data System (ADS)

    Cabot, Vincent; Vizcaino, Miren; Mikolajewicz, Uwe

    2016-04-01

    Long-term ice sheet and climate coupled simulations are of great interest since they assess how the Greenland Ice Sheet (GrIS) will respond to global warming and how GrIS changes will impact on the climate system. We have run the Max-Plank-Institute Earth System Model coupled with an Ice Sheet Model (SICOPOLIS) over a time period of 10500 years under two times CO2 forcing. This is a coupled atmosphere (ECHAM5T31), ocean (MPI-OM), dynamic vegetation (LPJ), and ice sheet (SICOPOLIS, 10 km horizontal resolution) model. Given the multi-millennia simulation, the horizontal spatial resolution of the atmospheric component is relatively coarse (3.75°). A time-saving technique (asynchronous coupling) is used once the global climate reaches quasi-equilibrium. In our doubling-CO2 simulation, the GrIS is expected to break up into two pieces (one ice cap in the far north on one ice sheet in the south and east) after 3000 years. During the first 500 simulation years, the GrIS climate and surface mass balance (SMB) are mainly affected by the greenhouse effect-forced climate change. After the simulated year 500, the global climate reaches quasi-equilibrium. Henceforth Greenland climate change is mainly due to ice sheet decay. GrIS albedo reduction enhances melt and acts as a powerful feedback for deglaciation. Due to increased cloudiness in the Arctic region as a result of global climate change, summer incoming shortwave radiation is substantially reduced over Greenland, reducing deglaciation rates. At the end of the simulation, Greenland becomes green with forest growing over the newly deglaciated regions. References: Helsen, M. M., van de Berg, W. J., van de Wal, R. S. W., van den Broeke, M. R., and Oerlemans, J. (2013), Coupled regional climate-ice-sheet simulation shows limited Greenland ice loss during the Eemian, Climate of the Past, 9, 1773-1788, doi: 10.5194/cp-9-1773-2013 Helsen, M. M., van de Wal, R. S. W., van den Broeke, M. R., van de Berg, W. J., and Oerlemans, J. (2015), Coupling of climate models and ice sheet models by the surface mass balance gradients: application to the Greenland Ice Sheet, The Cryosphere, 6, 255-272, doi: 10.5194/tc-6-255-2012 Robinson, A., Calov, R., and Ganopolski, A. (2011), Greenland ice sheet model parameters constrained using simulations of the Eemian Interglacial, Climate of the Past, 7, 381-396, doi: 10.5194/cp-7-381-2011 Vizcaino, M., Mikolajewicz, U., Ziemen, F., Rodehacke, C. B., Greve, R., and van den Broeke, M. R. (2015), Coupled simulations of Greenland Ice Sheet and climate change up to A.D. 2300, Geophysical Research Letters, 42, doi: 10.1002/2014GL061142

  11. Potential effects of climate change on the growth of fishes from different thermal guilds in Lakes Michigan and Huron

    USGS Publications Warehouse

    Kao, Yu-Chun; Madenjian, Charles P.; Bunnell, David B.; Lofgren, Brent M.; Perroud, Marjorie

    2015-01-01

    We used a bioenergetics modeling approach to investigate potential effects of climate change on the growth of two economically important native fishes: yellow perch (Perca flavescens), a cool-water fish, and lake whitefish (Coregonus clupeaformis), a cold-water fish, in deep and oligotrophic Lakes Michigan and Huron. For assessing potential changes in fish growth, we contrasted simulated fish growth in the projected future climate regime during the period 2043-2070 under different prey availability scenarios with the simulated growth during the baseline (historical reference) period 1964-1993. Results showed that effects of climate change on the growth of these two fishes are jointly controlled by behavioral thermoregulation and prey availability. With the ability of behavioral thermoregulation, temperatures experienced by yellow perch in the projected future climate regime increased more than those experienced by lake whitefish. Thus simulated future growth decreased more for yellow perch than for lake whitefish under scenarios where prey availability remains constant into the future. Under high prey availability scenarios, simulated future growth of these two fishes both increased but yellow perch could not maintain the baseline efficiency of converting prey consumption into body weight. We contended that thermal guild should not be the only factor used to predict effects of climate change on the growth of a fish, and that ecosystem responses to climate change should be also taken into account.

  12. Climate and atmosphere simulator for experiments on ecological systems in changing environments.

    PubMed

    Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François

    2014-01-01

    Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.

  13. Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

    NASA Astrophysics Data System (ADS)

    Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

    2017-12-01

    Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017. Techniques of the database system for near-future climate change projections might be quite useful for simulation and observational data in other research fields. We report current status of development and some case studies of the database system for near-future climate change projections.

  14. Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

    USGS Publications Warehouse

    Shafer, S.L.; Atkins, J.; Bancroft, B.A.; Bartlein, P.J.; Lawler, J.J.; Smith, B.; Wilsey, C.B.

    2012-01-01

    The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

  15. Potential effects of climate change on ground water in Lansing, Michigan

    USGS Publications Warehouse

    Croley, T.E.; Luukkonen, C.L.

    2003-01-01

    Computer simulations involving general circulation models, a hydrologic modeling system, and a ground water flow model indicate potential impacts of selected climate change projections on ground water levels in the Lansing, Michigan, area. General circulation models developed by the Canadian Climate Centre and the Hadley Centre generated meteorology estimates for 1961 through 1990 (as a reference condition) and for the 20 years centered on 2030 (as a changed climate condition). Using these meteorology estimates, the Great Lakes Environmental Research Laboratory's hydrologic modeling system produced corresponding period streamflow simulations. Ground water recharge was estimated from the streamflow simulations and from variables derived from the general circulation models. The U.S. Geological Survey developed a numerical ground water flow model of the Saginaw and glacial aquifers in the Tri-County region surrounding Lansing, Michigan. Model simulations, using the ground water recharge estimates, indicate changes in ground water levels. Within the Lansing area, simulated ground water levels in the Saginaw aquifer declined under the Canadian predictions and increased under the Hadley.

  16. Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

    NASA Astrophysics Data System (ADS)

    Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

    2017-12-01

    Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

  17. Climate-FVS Version 2: Content, users guide, applications, and behavior

    Treesearch

    Nicholas L. Crookston

    2014-01-01

    Climate change in the 21st Century is projected to cause widespread changes in forest ecosystems. Climate-FVS is a modification to the Forest Vegetation Simulator designed to take climate change into account when predicting forest dynamics at decadal to century time scales. Individual tree climate viability scores measure the likelihood that the climate at a given...

  18. Future change in seasonal march of snow water equivalent due to global climate change

    NASA Astrophysics Data System (ADS)

    Hara, M.; Kawase, H.; Ma, X.; Wakazuki, Y.; Fujita, M.; Kimura, F.

    2012-04-01

    Western side of Honshu Island in Japan is one of the heaviest snowfall areas in the world, although the location is relatively lower latitude than other heavy snowfall areas. Snowfall is one of major source for agriculture, industrial, and house-use in Japan. The change in seasonal march of snow water equivalent, e.g., snowmelt season and amount will strongly influence to social-economic activities (ex. Ma et al., 2011). We performed the four numerical experiments including present and future climate simulations and much-snow and less-snow cases using a regional climate model. Pseudo-Global-Warming (PGW) method (Kimura and Kitoh, 2008) is applied for the future climate simulations. NCEP/NCAR reanalysis is used for initial and boundary conditions in present climate simulation and PGW method. MIROC 3.2 medres 2070s output under IPCC SRES A2 scenario and 1990s output under 20c3m scenario used for PGW method. In much-snow cases, Maximum total snow water equivalent over Japan, which is mostly observed in early February, is 49 G ton in the present simulation, the one decreased 26 G ton in the future simulation. The decreasing rate of snow water equivalent due to climate change was 49%. Main cause of the decrease of the total snow water equivalent is strongly affected by the air temperature rise due to global climate change. The difference in present and future precipitation amount is little.

  19. The tropical rain belts with an annual cycle and a continent model intercomparison project: TRACMIP

    DOE PAGES

    Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; ...

    2016-11-16

    This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of the present-day climate and expected future climate change,more » including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to the present-day climate. Quadrupling CO 2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO 2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO 2; for example it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. Finally, this survey illustrates TRACMIP’s potential to engender a deeper understanding of global and regional climate phenomena and to address pressing questions on past and future climate change.« less

  20. Impacts of climate change on paddy rice yield in a temperate climate.

    PubMed

    Kim, Han-Yong; Ko, Jonghan; Kang, Suchel; Tenhunen, John

    2013-02-01

    The crop simulation model is a suitable tool for evaluating the potential impacts of climate change on crop production and on the environment. This study investigates the effects of climate change on paddy rice production in the temperate climate regions under the East Asian monsoon system using the CERES-Rice 4.0 crop simulation model. This model was first calibrated and validated for crop production under elevated CO2 and various temperature conditions. Data were obtained from experiments performed using a temperature gradient field chamber (TGFC) with a CO2 enrichment system installed at Chonnam National University in Gwangju, Korea in 2009 and 2010. Based on the empirical calibration and validation, the model was applied to deliver a simulated forecast of paddy rice production for the region, as well as for the other Japonica rice growing regions in East Asia, projecting for years 2050 and 2100. In these climate change projection simulations in Gwangju, Korea, the yield increases (+12.6 and + 22.0%) due to CO2 elevation were adjusted according to temperature increases showing variation dependent upon the cultivars, which resulted in significant yield decreases (-22.1% and -35.0%). The projected yields were determined to increase as latitude increases due to reduced temperature effects, showing the highest increase for any of the study locations (+24%) in Harbin, China. It appears that the potential negative impact on crop production may be mediated by appropriate cultivar selection and cultivation changes such as alteration of the planting date. Results reported in this study using the CERES-Rice 4.0 model demonstrate the promising potential for its further application in simulating the impacts of climate change on rice production from a local to a regional scale under the monsoon climate system. © 2012 Blackwell Publishing Ltd.

  1. Climate change and watershed mercury export: a multiple projection and model analysis.

    PubMed

    Golden, Heather E; Knightes, Christopher D; Conrads, Paul A; Feaster, Toby D; Davis, Gary M; Benedict, Stephen T; Bradley, Paul M

    2013-09-01

    Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. An ensemble of watershed models was applied in the present study to simulate and evaluate the responses of hydrological and total Hg (THg) fluxes from the landscape to the watershed outlet and in-stream THg concentrations to contrasting climate change projections for a watershed in the southeastern coastal plain of the United States. Simulations were conducted under stationary atmospheric deposition and land cover conditions to explicitly evaluate the effect of projected precipitation and temperature on watershed Hg export (i.e., the flux of Hg at the watershed outlet). Based on downscaled inputs from 2 global circulation models that capture extremes of projected wet (Community Climate System Model, Ver 3 [CCSM3]) and dry (ECHAM4/HOPE-G [ECHO]) conditions for this region, watershed model simulation results suggest a decrease of approximately 19% in ensemble-averaged mean annual watershed THg fluxes using the ECHO climate-change model and an increase of approximately 5% in THg fluxes with the CCSM3 model. Ensemble-averaged mean annual ECHO in-stream THg concentrations increased 20%, while those of CCSM3 decreased by 9% between the baseline and projected simulation periods. Watershed model simulation results using both climate change models suggest that monthly watershed THg fluxes increase during the summer, when projected flow is higher than baseline conditions. The present study's multiple watershed model approach underscores the uncertainty associated with climate change response projections and their use in climate change management decisions. Thus, single-model predictions can be misleading, particularly in developmental stages of watershed Hg modeling. Copyright © 2013 SETAC.

  2. The Tropical Rain Belts with an Annual Cycle and a Continent Model Intercomparison Project: TRACMIP

    NASA Technical Reports Server (NTRS)

    Voigt, Aiko; Biasutti, Michela; Scheff, Jacob; Bader, Juergen; Bordoni, Simona; Codron, Francis; Dixon, Ross D.; Jonas, Jeffrey; Kang, Sarah M.; Klingaman, Nicholas P.; hide

    2016-01-01

    This paper introduces the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project (TRACMIP). TRACMIP studies the dynamics of tropical rain belts and their response to past and future radiative forcings through simulations with 13 comprehensive and one simplified atmosphere models coupled to a slab ocean and driven by seasonally-varying insolation. Five idealized experiments, two with an aquaplanet setup and three with a setup with an idealized tropical continent, fill the space between prescribed-SST aquaplanet simulations and realistic simulations provided by CMIP5/6. The simulations reproduce key features of present-day climate and expected future climate change, including an annual-mean intertropical convergence zone (ITCZ) that is located north of the equator and Hadley cells and eddy-driven jets that are similar to present-day climate. Quadrupling CO2 leads to a northward ITCZ shift and preferential warming in Northern high-latitudes. The simulations show interesting CO2-induced changes in the seasonal excursion of the ITCZ and indicate a possible state-dependence of climate sensitivity. The inclusion of an idealized continent modulates both the control climate and the response to increased CO2; for example, it reduces the northward ITCZ shift associated with warming and, in some models, climate sensitivity. In response to eccentricity-driven seasonal insolation changes, seasonal changes in oceanic rainfall are best characterized as a meridional dipole, while seasonal continental rainfall changes tend to be symmetric about the equator. This survey illustrates TRACMIP's potential to engender a deeper understanding of global and regional climate and to address questions on past and future climate change.

  3. Predicted effects of gypsy moth defoliation and climate change on forest carbon dynamics in the New Jersey pine barrens.

    PubMed

    Kretchun, Alec M; Scheller, Robert M; Lucash, Melissa S; Clark, Kenneth L; Hom, John; Van Tuyl, Steve

    2014-01-01

    Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years.

  4. Predicted Effects of Gypsy Moth Defoliation and Climate Change on Forest Carbon Dynamics in the New Jersey Pine Barrens

    PubMed Central

    Kretchun, Alec M.; Scheller, Robert M.; Lucash, Melissa S.; Clark, Kenneth L.; Hom, John; Van Tuyl, Steve

    2014-01-01

    Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years. PMID:25119162

  5. Assessing Climate Change Impacts on Wildfire Exposure in Mediterranean Areas.

    PubMed

    Lozano, Olga M; Salis, Michele; Ager, Alan A; Arca, Bachisio; Alcasena, Fermin J; Monteiro, Antonio T; Finney, Mark A; Del Giudice, Liliana; Scoccimarro, Enrico; Spano, Donatella

    2017-10-01

    We used simulation modeling to assess potential climate change impacts on wildfire exposure in Italy and Corsica (France). Weather data were obtained from a regional climate model for the period 1981-2070 using the IPCC A1B emissions scenario. Wildfire simulations were performed with the minimum travel time fire spread algorithm using predicted fuel moisture, wind speed, and wind direction to simulate expected changes in weather for three climatic periods (1981-2010, 2011-2040, and 2041-2070). Overall, the wildfire simulations showed very slight changes in flame length, while other outputs such as burn probability and fire size increased significantly in the second future period (2041-2070), especially in the southern portion of the study area. The projected changes fuel moisture could result in a lengthening of the fire season for the entire study area. This work represents the first application in Europe of a methodology based on high resolution (250 m) landscape wildfire modeling to assess potential impacts of climate changes on wildfire exposure at a national scale. The findings can provide information and support in wildfire management planning and fire risk mitigation activities. © 2016 Society for Risk Analysis.

  6. Implication of Agricultural Land Use Change on Regional Climate Projection

    NASA Astrophysics Data System (ADS)

    Wang, G.; Ahmed, K. F.; You, L.

    2015-12-01

    Agricultural land use plays an important role in land-atmosphere interaction. Agricultural activity is one of the most important processes driving human-induced land use land cover change (LULCC) in a region. In addition to future socioeconomic changes, climate-induced changes in crop yield represent another important factor shaping agricultural land use. In feedback, the resulting LULCC influences the direction and magnitude of global, regional and local climate change by altering Earth's radiative equilibrium. Therefore, assessment of climate change impact on future agricultural land use and its feedback is of great importance in climate change study. In this study, to evaluate the feedback of projected land use changes to the regional climate in West Africa, we employed an asynchronous coupling between a regional climate model (RegCM) and a prototype land use projection model (LandPro). The LandPro model, which was developed to project the future change in agricultural land use and the resulting shift in natural vegetation in West Africa, is a spatially explicit model that can account for both climate and socioeconomic changes in projecting future land use changes. In the asynchronously coupled modeling framework, LandPro was run for every five years during the period of 2005-2050 accounting for climate-induced change in crop yield and socioeconomic changes to project the land use pattern by the mid-21st century. Climate data at 0.5˚ was derived from RegCM to drive the crop model DSSAT for each of the five-year periods to simulate crop yields, which was then provided as input data to LandPro. Subsequently, the land use land cover map required to run RegCM was updated every five years using the outputs from the LandPro simulations. Results from the coupled model simulations improve the understanding of climate change impact on future land use and the resulting feedback to regional climate.

  7. Selecting climate simulations for impact studies based on multivariate patterns of climate change.

    PubMed

    Mendlik, Thomas; Gobiet, Andreas

    In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

  8. The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models

    NASA Astrophysics Data System (ADS)

    Keller, Michael; Kröner, Nico; Fuhrer, Oliver; Lüthi, Daniel; Schmidli, Juerg; Stengel, Martin; Stöckli, Reto; Schär, Christoph

    2018-04-01

    Climate models project an increase in heavy precipitation events in response to greenhouse gas forcing. Important elements of such events are rain showers and thunderstorms, which are poorly represented in models with parameterized convection. In this study, simulations with 12 km horizontal grid spacing (convection-parameterizing model, CPM) and 2 km grid spacing (convection-resolving model, CRM) are employed to investigate the change in the diurnal cycle of convection with warmer climate. For this purpose, simulations of 11 days in June 2007 with a pronounced diurnal cycle of convection are compared with surrogate simulations from the same period. The surrogate climate simulations mimic a future climate with increased temperatures but unchanged relative humidity and similar synoptic-scale circulation. Two temperature scenarios are compared: one with homogeneous warming (HW) using a vertically uniform warming and the other with vertically dependent warming (VW) that enables changes in lapse rate. The two sets of simulations with parameterized and explicit convection exhibit substantial differences, some of which are well known from the literature. These include differences in the timing and amplitude of the diurnal cycle of convection, and the frequency of precipitation with low intensities. The response to climate change is much less studied. We can show that stratification changes have a strong influence on the changes in convection. Precipitation is strongly increasing for HW but decreasing for the VW simulations. For cloud type frequencies, virtually no changes are found for HW, but a substantial reduction in high clouds is found for VW. Further, we can show that the climate change signal strongly depends upon the horizontal resolution. In particular, significant differences between CPM and CRM are found in terms of the radiative feedbacks, with CRM exhibiting a stronger negative feedback in the top-of-the-atmosphere energy budget.

  9. Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

    NASA Astrophysics Data System (ADS)

    van Walsum, P. E. V.; Supit, I.

    2012-06-01

    Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.

  10. Changes of climate regimes during the last millennium and the twenty-first century simulated by the Community Earth System Model

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Feng, Song; Liu, Chang; Chen, Jie; Chen, Jianhui; Chen, Fahu

    2018-01-01

    This study examines the shifts in terrestrial climate regimes using the Köppen-Trewartha (K-T) climate classification by analyzing the Community Earth System Model Last Millennium Ensemble (CESM-LME) simulations for the period 850-2005 and CESM Medium Ensemble (CESM-ME), CESM Large Ensemble (CESM-LE) and CESM with fixed aerosols Medium Ensemble (CESM-LE_FixA) simulations for the period 1920-2080. We compare K-T climate types from the Medieval Climate Anomaly (MCA) (950-1250) with the Little Ice Age (LIA) (1550-1850), from present day (PD) (1971-2000) with the last millennium (LM) (850-1850), and from the future (2050-2080) with the LM in order to place anthropogenic changes in the context of changes due to natural forcings occurring during the last millennium. For CESM-LME, we focused on the simulations with all forcings, though the impacts of individual forcings (e.g., solar activities, volcanic eruptions, greenhouse gases, aerosols and land use changes) were also analyzed. We found that the climate types changed slightly between the MCA and the LIA due to weak changes in temperature and precipitation. The climate type changes in PD relative to the last millennium have been largely driven by greenhouse gas-induced warming, but anthropogenic aerosols have also played an important role on regional scales. At the end of the twenty-first century, the anthropogenic forcing has a much greater effect on climate types than the PD. Following the reduction of aerosol emissions, the impact of greenhouse gases will further promote global warming in the future. Compared to precipitation, changes in climate types are dominated by greenhouse gas-induced warming. The large shift in climate types by the end of this century suggests possible wide-spread redistribution of surface vegetation and a significant change in species distributions.

  11. Regional climate model simulations indicate limited climatic impacts by operational and planned European wind farms.

    PubMed

    Vautard, Robert; Thais, Françoise; Tobin, Isabelle; Bréon, François-Marie; Devezeaux de Lavergne, Jean-Guy; Colette, Augustin; Yiou, Pascal; Ruti, Paolo Michele

    2014-01-01

    The rapid development of wind energy has raised concerns about environmental impacts. Temperature changes are found in the vicinity of wind farms and previous simulations have suggested that large-scale wind farms could alter regional climate. However, assessments of the effects of realistic wind power development scenarios at the scale of a continent are missing. Here we simulate the impacts of current and near-future wind energy production according to European Union energy and climate policies. We use a regional climate model describing the interactions between turbines and the atmosphere, and find limited impacts. A statistically significant signal is only found in winter, with changes within ±0.3 °C and within 0-5% for precipitation. It results from the combination of local wind farm effects and changes due to a weak, but robust, anticyclonic-induced circulation over Europe. However, the impacts remain much weaker than the natural climate interannual variability and changes expected from greenhouse gas emissions.

  12. Influences of Regional Climate Change on Air Quality across the Continental U.S. Projected from Downscaling IPCC ARS Simulations

    EPA Science Inventory

    Projecting climate change scenarios to local scales is important for understanding, mitigating, and adapting to the effects of climate change on society and the environment. Many of the global climate models (GCMs) that are participating in the Intergovernmental Panel on Climate ...

  13. The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012

    PubMed Central

    Bai, Jie; Li, Longhui

    2017-01-01

    The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang. PMID:28841645

  14. The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012.

    PubMed

    Yuan, Xiuliang; Bai, Jie; Li, Longhui; Kurban, Alishir; De Maeyer, Philippe

    2017-01-01

    The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

  15. Predicted impacts of climate change on malaria transmission in West Africa

    NASA Astrophysics Data System (ADS)

    Yamana, T. K.; Eltahir, E. A. B.

    2014-12-01

    Increases in temperature and changes in precipitation due to climate change are expected to alter the spatial distribution of malaria transmission. This is especially true in West Africa, where malaria prevalence follows the current north-south gradients in temperature and precipitation. We assess the skill of GCMs at simulating past and present climate in West Africa in order to select the most credible climate predictions for the periods 2030-2060 and 2070-2100. We then use the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS), a mechanistic model of malaria transmission, to translate the predicted changes in climate into predicted changes availability of mosquito breeding sites, mosquito populations, and malaria prevalence. We investigate the role of acquired immunity in determining a population's response to changes in exposure to the malaria parasite.

  16. Farm Simulation: a tool for evaluating the mitigation of greenhouse gas emissions and the adaptation of dairy production to climate change

    USDA-ARS?s Scientific Manuscript database

    Farms both produce greenhouse gas emissions that drive human-induced climate change and are impacted by that climate change. Whole farm and global climate models provide useful tools for studying the benefits and costs of greenhouse gas mitigation and the adaptation of farms to changing climate. The...

  17. The MIT IGSM-CAM framework for uncertainty studies in global and regional climate change

    NASA Astrophysics Data System (ADS)

    Monier, E.; Scott, J. R.; Sokolov, A. P.; Forest, C. E.; Schlosser, C. A.

    2011-12-01

    The MIT Integrated Global System Model (IGSM) version 2.3 is an intermediate complexity fully coupled earth system model that allows simulation of critical feedbacks among its various components, including the atmosphere, ocean, land, urban processes and human activities. A fundamental feature of the IGSM2.3 is the ability to modify its climate parameters: climate sensitivity, net aerosol forcing and ocean heat uptake rate. As such, the IGSM2.3 provides an efficient tool for generating probabilistic distribution functions of climate parameters using optimal fingerprint diagnostics. A limitation of the IGSM2.3 is its zonal-mean atmosphere model that does not permit regional climate studies. For this reason, the MIT IGSM2.3 was linked to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM) version 3 and new modules were developed and implemented in CAM in order to modify its climate sensitivity and net aerosol forcing to match that of the IGSM. The IGSM-CAM provides an efficient and innovative framework to study regional climate change where climate parameters can be modified to span the range of uncertainty and various emissions scenarios can be tested. This paper presents results from the cloud radiative adjustment method used to modify CAM's climate sensitivity. We also show results from 21st century simulations based on two emissions scenarios (a median "business as usual" scenario where no policy is implemented after 2012 and a policy scenario where greenhouse-gas are stabilized at 660 ppm CO2-equivalent concentrations by 2100) and three sets of climate parameters. The three values of climate sensitivity chosen are median and the bounds of the 90% probability interval of the probability distribution obtained by comparing the observed 20th century climate change with simulations by the IGSM with a wide range of climate parameters values. The associated aerosol forcing values were chosen to ensure a good agreement of the simulations with the observed climate change over the 20th century. Because the concentrations of sulfate aerosols significantly decrease over the 21st century in both emissions scenarios, climate changes obtained in these six simulations provide a good approximation for the median, and the 5th and 95th percentiles of the probability distribution of 21st century climate change.

  18. The PMIP4 contribution to CMIP6 - Part 2: Two interglacials, scientific objective and experimental design for Holocene and Last Interglacial simulations

    NASA Astrophysics Data System (ADS)

    Otto-Bliesner, Bette L.; Braconnot, Pascale; Harrison, Sandy P.; Lunt, Daniel J.; Abe-Ouchi, Ayako; Albani, Samuel; Bartlein, Patrick J.; Capron, Emilie; Carlson, Anders E.; Dutton, Andrea; Fischer, Hubertus; Goelzer, Heiko; Govin, Aline; Haywood, Alan; Joos, Fortunat; LeGrande, Allegra N.; Lipscomb, William H.; Lohmann, Gerrit; Mahowald, Natalie; Nehrbass-Ahles, Christoph; Pausata, Francesco S. R.; Peterschmitt, Jean-Yves; Phipps, Steven J.; Renssen, Hans; Zhang, Qiong

    2017-11-01

    Two interglacial epochs are included in the suite of Paleoclimate Modeling Intercomparison Project (PMIP4) simulations in the Coupled Model Intercomparison Project (CMIP6). The experimental protocols for simulations of the mid-Holocene (midHolocene, 6000 years before present) and the Last Interglacial (lig127k, 127 000 years before present) are described here. These equilibrium simulations are designed to examine the impact of changes in orbital forcing at times when atmospheric greenhouse gas levels were similar to those of the preindustrial period and the continental configurations were almost identical to modern ones. These simulations test our understanding of the interplay between radiative forcing and atmospheric circulation, and the connections among large-scale and regional climate changes giving rise to phenomena such as land-sea contrast and high-latitude amplification in temperature changes, and responses of the monsoons, as compared to today. They also provide an opportunity, through carefully designed additional sensitivity experiments, to quantify the strength of atmosphere, ocean, cryosphere, and land-surface feedbacks. Sensitivity experiments are proposed to investigate the role of freshwater forcing in triggering abrupt climate changes within interglacial epochs. These feedback experiments naturally lead to a focus on climate evolution during interglacial periods, which will be examined through transient experiments. Analyses of the sensitivity simulations will also focus on interactions between extratropical and tropical circulation, and the relationship between changes in mean climate state and climate variability on annual to multi-decadal timescales. The comparative abundance of paleoenvironmental data and of quantitative climate reconstructions for the Holocene and Last Interglacial make these two epochs ideal candidates for systematic evaluation of model performance, and such comparisons will shed new light on the importance of external feedbacks (e.g., vegetation, dust) and the ability of state-of-the-art models to simulate climate changes realistically.

  19. Legacy effects of simulated short-term climate change on ammonia oxidisers, denitrifiers, and nitrous oxide emissions in an acid soil.

    PubMed

    Xu, Xiaoya; Liu, Xiaorui; Li, Yong; Ran, Yu; Liu, Yapeng; Zhang, Qichun; Li, Zheng; He, Yan; Xu, Jianming; Di, Hongjie

    2017-04-01

    Although the effect of simulated climate change on nitrous oxide (N 2 O) emissions and on associated microbial communities has been reported, it is not well understood if these effects are short-lived or long-lasting. Here, we conducted a field study to determine the interactive effects of simulated warmer and drier conditions on nitrifier and denitrifier communities and N 2 O emissions in an acidic soil and the longevity of the effects. A warmer (+2.3 °C) and drier climate (-7.4% soil moisture content) was created with greenhouses. The variation of microbial population abundance and community structure of ammonia-oxidizing archaea (AOA), bacteria (AOB), and denitrifiers (nirK/S, nosZ) were determined using real-time PCR and high-throughput sequencing. The results showed that the simulated warmer and drier conditions under the greenhouse following urea application significantly increased N 2 O emissions. There was also a moderate legacy effect on the N 2 O emissions when the greenhouses were removed in the urea treatment, although this effect only lasted a short period of time (about 60 days). The simulated climate change conditions changed the composition of AOA with the species affiliated to marine group 1.1a-associated lineage increasing significantly. The abundance of all the functional denitrifier genes decreased significantly under the simulated climate change conditions and the legacy effect, after the removal of greenhouses, significantly increased the abundance of AOB, AOA (mainly the species affiliated to marine group 1.1a-associated lineage), and nirK and nosZ genes in the urea-treated soil. In general, the effect of the simulated climate change was short-lived, with the denitrifier communities being able to return to ambient levels after a period of adaptation to ambient conditions. Therefore, the legacy effect of simulated short-time climate change conditions on the ammonia oxidizer and denitrifier communities and N 2 O emissions were temporary and once the conditions were removed, the microbial communities were able to adapt to the ambient conditions.

  20. Changes in Moisture Flux Over the Tibetan Plateau During 1979-2011: Insights from a High Resolution Simulation

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

    Gao, Yanhong; Leung, Lai-Yung R.; Zhang, Yongxin

    2015-05-01

    Net precipitation (precipitation minus evapotranspiration, P-E) changes from a high resolution regional climate simulation and its reanalysis forcing are analyzed over the Tibet Plateau (TP) and compared to the global land data assimilation system (GLDAS) product. The mechanism behind the P-E changes is explored by decomposing the column integrated moisture flux convergence into thermodynamic, dynamic, and transient eddy components. High-resolution climate simulation improves the spatial pattern of P-E changes over the best available global reanalysis. Improvement in simulating precipitation changes at high elevations contributes dominantly to the improved P-E changes. High-resolution climate simulation also facilitates new and substantial findings regardingmore » the role of thermodynamics and transient eddies in P-E changes reflected in observed changes in major river basins fed by runoff from the TP. The analysis revealed the contrasting convergence/divergence changes between the northwestern and southeastern TP and feedback through latent heat release as an important mechanism leading to the mean P-E changes in the TP.« less

  1. Assessment of potential climate change impacts on peatland dissolved organic carbon release and drinking water treatment from laboratory experiments.

    PubMed

    Tang, R; Clark, J M; Bond, T; Graham, N; Hughes, D; Freeman, C

    2013-02-01

    Catchments draining peat soils provide the majority of drinking water in the UK. Over the past decades, concentrations of dissolved organic carbon (DOC) have increased in surface waters. Residual DOC can cause harmful carcinogenic disinfection by-products to form during water treatment processes. Increased frequency and severity of droughts combined with and increased temperatures expected as the climate changes, have potentials to change water quality. We used a novel approach to investigate links between climate change, DOC release and subsequent effects on drinking water treatment. We designed a climate manipulation experiment to simulate projected climate changes and monitored releases from peat soil and litter, then simulated coagulation used in water treatment. We showed that the 'drought' simulation was the dominant factor altering DOC release and affected the ability to remove DOC. Our results imply that future short-term drought events could have a greater impact than increased temperature on DOC treatability. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Application of MODFLOW’s farm process to California’s Central Valley

    USGS Publications Warehouse

    Faunt, Claudia; Hanson, Randall T.; Schmid, Wolfgang; Belitz, Kenneth

    2008-01-01

    landscape processes. The FMP provides coupled simulation of the ground-water and surface-water components of the hydrologic cycle for irrigated and non-irrigated areas. A dynamic allocation of ground-water recharge and ground-water pumping is simulated on the basis of residual crop-water demand after surface-water deliveries and root uptake from shallow ground water. The FMP links with the Streamflow Routing Package SFR1) to facilitate the simulated conveyance of surface-water deliveries. Ground-water Pumpage through both single-aquifer and multi-node wells, irrigation return flow, and variable irrigation efficiencies also are simulated by the FMP. The simulated deliveries and ground-water pumpage in the updated model reflect climatic differences, differences among defined water-balance regions, and changes in the waterdelivery system, during the 1961–2003 simulation period. The model is designed to accept forecasts from Global Climate Models (GCMs) to simulate the potential effects on surface-water delivery, ground-water pumpage, and ground-water storage in response to climate change. The model provides a detailed transient analysis of changes in ground-water availability in relation to climatic variability, urbanization, and changes in irrigated agriculture.

  3. Simulating streamflow in ungauged basins under a changing climate: The importance of landscape characteristics

    NASA Astrophysics Data System (ADS)

    Teutschbein, Claudia; Grabs, Thomas; Laudon, Hjalmar; Karlsen, Reinert H.; Bishop, Kevin

    2018-06-01

    In this paper we explored how landscape characteristics such as topography, geology, soils and land cover influence the way catchments respond to changing climate conditions. Based on an ensemble of 15 regional climate models bias-corrected with a distribution-mapping approach, present and future streamflow in 14 neighboring and rather similar catchments in Northern Sweden was simulated with the HBV model. We established functional relationships between a range of landscape characteristics and projected changes in streamflow signatures. These were then used to analyze hydrological consequences of physical perturbations in a hypothetically ungauged basin in a climate change context. Our analysis showed a strong connection between the forest cover extent and the sensitivity of different components of a catchment's hydrological regime to changing climate conditions. This emphasizes the need to redefine forestry goals and practices in advance of climate change-related risks and uncertainties.

  4. Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

    NASA Astrophysics Data System (ADS)

    Quetin, G. R.; Swann, A. L. S.

    2017-12-01

    Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

  5. A comparative analysis of the impacts of climate change and irrigation on land surface and subsurface hydrology in the North China Plain

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

    Leng, Guoyong; Tang, Qiuhong; Huang, Maoyi

    The Community Land Model 4.0 (CLM4) was used to investigate and compare the effects of climate change and irrigation on terrestrial water cycle. Three climate change scenarios and one irrigation scenario (IRRIG) were simulated in the North China Plain (NCP), which is one of the most vulnerable regions to climate change and human perturbations in China. The climate change scenarios consist of (1) HOT (i.e. temperature increase by 2oC); (2) HOTWET (same with HOT but with an increase of precipitation by 15%); (3) HOTDRY (same with HOT but with a decrease of precipitation by 15%). In the IRRIG scenario, themore » irrigation scheme was calibrated to simulate irrigation amounts that match the actual irrigation amounts and irrigation was divided between surface water and groundwater withdrawals based on census data. Our results show that the impacts of climate change were more widespread while those of irrigation were concentrated only over the agricultural regions. Specifically, the mean water table depth was simulated to decline persistently by over 1 m annually due to groundwater exploitation during the period of 1980-2000, while much smaller effects were induced by climate change. Although irrigation has comparable effects on surface fluxes and surface soil moisture as climate change, it has much greater effects on water table depth and groundwater storage. Moreover, irrigation has much larger effects on the top layer soil moisture whereas increase in precipitation associated with climate change exerts more influence on lower layer soil moisture. This study emphasizes the need to accurately account for irrigation impacts in adapting to climate change.« less

  6. A multi-model framework for simulating wildlife population response to land-use and climate change

    USGS Publications Warehouse

    McRae, B.H.; Schumaker, N.H.; McKane, R.B.; Busing, R.T.; Solomon, A.M.; Burdick, C.A.

    2008-01-01

    Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

  7. Projected changes of the southwest Australian wave climate under two atmospheric greenhouse gas concentration pathways

    NASA Astrophysics Data System (ADS)

    Wandres, Moritz; Pattiaratchi, Charitha; Hemer, Mark A.

    2017-09-01

    Incident wave energy flux is responsible for sediment transport and coastal erosion in wave-dominated regions such as the southwestern Australian (SWA) coastal zone. To evaluate future wave climates under increased greenhouse gas concentration scenarios, past studies have forced global wave simulations with wind data sourced from global climate model (GCM) simulations. However, due to the generally coarse spatial resolution of global climate and wave simulations, the effects of changing offshore wave conditions and sea level rise on the nearshore wave climate are still relatively unknown. To address this gap of knowledge, we investigated the projected SWA offshore, shelf, and nearshore wave climate under two potential future greenhouse gas concentration trajectories (representative concentration pathways RCP4.5 and RCP8.5). This was achieved by downscaling an ensemble of global wave simulations, forced with winds from GCMs participating in the Coupled Model Inter-comparison Project (CMIP5), into two regional domains, using the Simulating WAves Nearshore (SWAN) wave model. The wave climate is modeled for a historical 20-year time slice (1986-2005) and a projected future 20-year time-slice (2081-2100) for both scenarios. Furthermore, we compare these scenarios to the effects of considering sea-level rise (SLR) alone (stationary wave climate), and to the effects of combined SLR and projected wind-wave change. Results indicated that the SWA shelf and nearshore wave climate is more sensitive to changes in offshore mean wave direction than offshore wave heights. Nearshore, wave energy flux was projected to increase by ∼10% in exposed areas and decrease by ∼10% in sheltered areas under both climate scenarios due to a change in wave directions, compared to an overall increase of 2-4% in offshore wave heights. With SLR, the annual mean wave energy flux was projected to increase by up to 20% in shallow water (< 30 m) as a result of decreased wave dissipation. In winter months, the longshore wave energy flux, which is responsible for littoral drift, is expected to increase by up to 39% (62%) under the RCP4.5 (RCP8.5) greenhouse gas concentration pathway with SLR. The study highlights the importance of using high-resolution wave simulations to evaluate future regional wave climates, since the coastal wave climate is more responsive to changes in wave direction and sea level than offshore wave heights.

  8. Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

    NASA Astrophysics Data System (ADS)

    Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

    2010-12-01

    Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

  9. Stress testing hydrologic models using bottom-up climate change assessment

    NASA Astrophysics Data System (ADS)

    Stephens, C.; Johnson, F.; Marshall, L. A.

    2017-12-01

    Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

  10. Simulating effects of changing climate and CO(2) emissions on soil carbon pools at the Hubbard Brook experimental forest.

    PubMed

    Dib, Alain E; Johnson, Chris E; Driscoll, Charles T; Fahey, Timothy J; Hayhoe, Katharine

    2014-05-01

    Carbon (C) sequestration in forest biomass and soils may help decrease regional C footprints and mitigate future climate change. The efficacy of these practices must be verified by monitoring and by approved calculation methods (i.e., models) to be credible in C markets. Two widely used soil organic matter models - CENTURY and RothC - were used to project changes in SOC pools after clear-cutting disturbance, as well as under a range of future climate and atmospheric carbon dioxide (CO(2) ) scenarios. Data from the temperate, predominantly deciduous Hubbard Brook Experimental Forest (HBEF) in New Hampshire, USA, were used to parameterize and validate the models. Clear-cutting simulations demonstrated that both models can effectively simulate soil C dynamics in the northern hardwood forest when adequately parameterized. The minimum postharvest SOC predicted by RothC occurred in postharvest year 14 and was within 1.5% of the observed minimum, which occurred in year 8. CENTURY predicted the postharvest minimum SOC to occur in year 45, at a value 6.9% greater than the observed minimum; the slow response of both models to disturbance suggests that they may overestimate the time required to reach new steady-state conditions. Four climate change scenarios were used to simulate future changes in SOC pools. Climate-change simulations predicted increases in SOC by as much as 7% at the end of this century, partially offsetting future CO(2) emissions. This sequestration was the product of enhanced forest productivity, and associated litter input to the soil, due to increased temperature, precipitation and CO(2) . The simulations also suggested that considerable losses of SOC (8-30%) could occur if forest vegetation at HBEF does not respond to changes in climate and CO(2) levels. Therefore, the source/sink behavior of temperate forest soils likely depends on the degree to which forest growth is stimulated by new climate and CO(2) conditions. © 2013 John Wiley & Sons Ltd.

  11. Water Source and Isotope changes through the Deglaciation and Holocene

    NASA Astrophysics Data System (ADS)

    LeGrande, A. N.; Carlson, A. E.; Ullman, D. J.; Nusbaumer, J. M.

    2017-12-01

    The deglacial period saw radical shifts in climate across the globe. Water isotopologues provide some of the most wide-spread proxy archives of these climate changes. Here we present new analyses on a suite of 12 water isotope-enabled coupled atmosphere-ocean GCM simulations from GISS ModelE-R that span 24kya to the pre-industrial period. We show how millennial scale co-variability in water isotopes and climate (temperature, precipitation, humidity, and moist-static energy) is distinct from regional scale spatial slopes, consistent with proxy archives (e.g., Cuffey et al 1995). We supplement this set of simulations with a new ensemble of deglacial simulations that contain a complementary suite of tracers that determine moisture provenance changes through the deglaciation. We diagnose regions that have had significant changes in moisture provenance and compare this information against simulated changes in the water isotope changes.

  12. Robust Spring Drying in the Southwestern U.S. and Seasonal Migration of Wet/Dry Patterns in a Warmer Climate

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

    Gao, Yang; Leung, Lai-Yung R.; Lu, Jian

    2014-03-16

    This study compares climate simulations over the United States produced by a regional climate model with the driving global climate simulations as well as a large multi-model ensemble of global climate simulations to investigate robust changes in water availability (precipitation (P) – evapotranspiration (E)). A robust spring dry signal across multiple models is identified in the Southwest that results from a decrease in P and an increase in E in the future. In the boreal winter and summer, the prominent changes in P – E are associated with a north – south dipole pattern, while in spring, the prominent changesmore » in P – E appear as an east – west dipole pattern. The progression of the north – south and east – west dipole patterns through the seasons manifests clearly as a seasonal “clockwise” migration of wet/dry patterns, which is shown to be a robust feature of water availability changes in the US consistent across regional and global climate simulations.« less

  13. Insights on the energy-water nexus through modeling of the integrated water cycle

    NASA Astrophysics Data System (ADS)

    Leung, L. R.; Li, H. Y.; Zhang, X.; Wan, W.; Voisin, N.; Leng, G.

    2016-12-01

    For sustainable energy planning, understanding the impacts of climate change, land use change, and water management is essential as they all exert notable controls on streamflow and stream temperature that influence energy production. An integrated water model representing river processes, irrigation water use and water management has been developed and coupled to a land surface model to investigate the energy-water nexus. Simulations driven by two climate change projections with the RCP 4.5 and RCP 8.5 emissions scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature. The simulations revealed important impacts of climate change and water management on both floods and droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the climate mitigation (RCP 4.5) and business as usual (RCP 8.5) scenarios that influence streamflow and stream temperature, with important consequences to energy production. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME) to enable investigation of the energy-water nexus in the fully coupled Earth system.

  14. CLARREO shortwave observing system simulation experiments of the twenty-first century: Simulator design and implementation

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

    Feldman, D.R.; Algieri, C.A.; Ong, J.R.

    2011-04-01

    Projected changes in the Earth system will likely be manifested in changes in reflected solar radiation. This paper introduces an operational Observational System Simulation Experiment (OSSE) to calculate the signals of future climate forcings and feedbacks in top-of-atmosphere reflectance spectra. The OSSE combines simulations from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report for the NCAR Community Climate System Model (CCSM) with the MODTRAN radiative transfer code to calculate reflectance spectra for simulations of current and future climatic conditions over the 21st century. The OSSE produces narrowband reflectances and broadband fluxes, the latter of which have been extensivelymore » validated against archived CCSM results. The shortwave reflectance spectra contain atmospheric features including signals from water vapor, liquid and ice clouds, and aerosols. The spectra are also strongly influenced by the surface bidirectional reflectance properties of predicted snow and sea ice and the climatological seasonal cycles of vegetation. By comparing and contrasting simulated reflectance spectra based on emissions scenarios with increasing projected and fixed present-day greenhouse gas and aerosol concentrations, we find that prescribed forcings from increases in anthropogenic sulfate and carbonaceous aerosols are detectable and are spatially confined to lower latitudes. Also, changes in the intertropical convergence zone and poleward shifts in the subsidence zones and the storm tracks are all detectable along with large changes in snow cover and sea ice fraction. These findings suggest that the proposed NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission to measure shortwave reflectance spectra may help elucidate climate forcings, responses, and feedbacks.« less

  15. Simulating post-wildfire forest trajectories under alternative climate and management scenarios

    Treesearch

    Alicia Azpeleta Tarancon; Peter Z. Fule; Kristen L. Shive; Carolyn H. Sieg; Andrew Sanchez Meador; Barbara Strom

    2014-01-01

    Post-fire predictions of forest recovery under future climate change and management actions are necessary for forest managers to make decisions about treatments. We applied the Climate-Forest Vegetation Simulator (Climate-FVS), a new version of a widely used forest management model, to compare alternative climate and management scenarios in a severely burned...

  16. Mid-Century Ensemble Regional Climate Change Scenarios for the Western United States

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

    Leung, Lai R.; Qian, Yun; Bian, Xindi

    To study the impacts of climate change on water resources in the western U.S., global climate simulations were produced using the National Center for Atmospheric Research/Department of Energy (NCAR/DOE) Parallel Climate Model (PCM). The Penn State/NCAR Mesoscale Model (MM5) was used to downscale the PCM control (1995-2015) and three future (2040-2060) climate simulations to yield ensemble regional climate simulations at 40 km spatial resolution for the western U.S. This paper focuses on analyses of regional simulations in the Columbia River and Sacramento-San Joaquin River Basins. Results based on the regional simulations show that by mid-century, the average regional warming ofmore » 1-2.5oC strongly affects snowpack in the western U.S. Along coastal mountains, reduction in annual snowpack is about 70%. Besides changes in mean temperature, precipitation, and snowpack, cold season extreme daily precipitation is found to increase by 5 to 15 mm/day (15-20%) along the Cascades and the Sierra. The warming results in increased rainfall over snowfall and reduced snow accumulation (or earlier snowmelt) during the cold season. In the Columbia River Basin, these changes are accompanied by more frequent rain-on-snow events. Overall, they induce higher likelihood of wintertime flooding and reduced runoff and soil moisture in the summer. Such changes could have serious impacts on water resources and agriculture in the western U.S. Changes in surface water and energy budgets in the Columbia River and Sacramento-San Joaquin basins are driven mainly by changes in surface temperature, which are statistically significant at the 0.95 confidence level. Changes in precipitation, however, are spatially incoherent and not statistically significant except for the drying trend during summer.« less

  17. Assessing climate-change risks to cultural and natural resources in the Yakima River Basin, Washington, USA

    USGS Publications Warehouse

    Hatten, James R.; Waste, Stephen M.; Maule, Alec G.

    2014-01-01

    We provide an overview of an interdisciplinary special issue that examines the influence of climate change on people and fish in the Yakima River Basin, USA. Jenni et al. (2013) addresses stakeholder-relevant climate change issues, such as water availability and uncertainty, with decision analysis tools. Montag et al. (2014) explores Yakama Tribal cultural values and well-being and their incorporation into the decision-making process. Graves and Maule (2012) simulates effects of climate change on stream temperatures under baseline conditions (1981–2005) and two future climate scenarios (increased air temperature of 1 °C and 2 °C). Hardiman and Mesa (2013) looks at the effects of increased stream temperatures on juvenile steelhead growth with a bioenergetics model. Finally, Hatten et al. (2013) examines how changes in stream flow will affect salmonids with a rule-based fish habitat model. Our simulations indicate that future summer will be a very challenging season for salmonids when low flows and high water temperatures can restrict movement, inhibit or alter growth, and decrease habitat. While some of our simulations indicate salmonids may benefit from warmer water temperatures and increased winter flows, the majority of simulations produced less habitat. The floodplain and tributary habitats we sampled are representative of the larger landscape, so it is likely that climate change will reduce salmonid habitat potential throughout particular areas of the basin. Management strategies are needed to minimize potential salmonid habitat bottlenecks that may result from climate change, such as keeping streams cool through riparian protection, stream restoration, and the reduction of water diversions. An investment in decision analysis and support technologies can help managers understand tradeoffs under different climate scenarios and possibly improve water and fish conservation over the next century.

  18. Coupled Global-Regional Climate Model Simulations of Future Changes in Hydrology over Central America

    NASA Astrophysics Data System (ADS)

    Oglesby, R. J.; Erickson, D. J.; Hernandez, J. L.; Irwin, D.

    2005-12-01

    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.

  19. Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

    NASA Astrophysics Data System (ADS)

    Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

    2013-05-01

    climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

  20. Natural climate variability and teleconnections to precipitation over the Pacific-North American region in CMIP3 and CMIP5 models

    USGS Publications Warehouse

    Polade, Suraj D.; Gershunov, Alexander; Cayan, Daniel R.; Dettinger, Michael D.; Pierce, David W.

    2013-01-01

    Natural climate variability will continue to be an important aspect of future regional climate even in the midst of long-term secular changes. Consequently, the ability of climate models to simulate major natural modes of variability and their teleconnections provides important context for the interpretation and use of climate change projections. Comparisons reported here indicate that the CMIP5 generation of global climate models shows significant improvements in simulations of key Pacific climate mode and their teleconnections to North America compared to earlier CMIP3 simulations. The performance of 14 models with simulations in both the CMIP3 and CMIP5 archives are assessed using singular value decomposition analysis of simulated and observed winter Pacific sea surface temperatures (SSTs) and concurrent precipitation over the contiguous United States and northwestern Mexico. Most of the models reproduce basic features of the key natural mode and their teleconnections, albeit with notable regional deviations from observations in both SST and precipitation. Increasing horizontal resolution in the CMIP5 simulations is an important, but not a necessary, factor in the improvement from CMIP3 to CMIP5.

  1. Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

    NASA Astrophysics Data System (ADS)

    Watanabe, S.; Kim, H.; Utsumi, N.

    2017-12-01

    This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.

  2. Regional Climate Change across the Continental U.S. Projected from Downscaling IPCC AR5 Simulations

    NASA Astrophysics Data System (ADS)

    Otte, T. L.; Nolte, C. G.; Otte, M. J.; Pinder, R. W.; Faluvegi, G.; Shindell, D. T.

    2011-12-01

    Projecting climate change scenarios to local scales is important for understanding and mitigating the effects of climate change on society and the environment. Many of the general circulation models (GCMs) that are participating in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) do not fully resolve regional-scale processes and therefore cannot capture local changes in temperature and precipitation extremes. We seek to project the GCM's large-scale climate change signal to the local scale using a regional climate model (RCM) by applying dynamical downscaling techniques. The RCM will be used to better understand the local changes of temperature and precipitation extremes that may result from a changing climate. Preliminary results from downscaling NASA/GISS ModelE simulations of the IPCC AR5 Representative Concentration Pathway (RCP) scenario 6.0 will be shown. The Weather Research and Forecasting (WRF) model will be used as the RCM to downscale decadal time slices for ca. 2000 and ca. 2030 and illustrate potential changes in regional climate for the continental U.S. that are projected by ModelE and WRF under RCP6.0.

  3. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

    EPA Pesticide Factsheets

    Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).

  4. GIS and crop simulation modelling applications in climate change research

    USDA-ARS?s Scientific Manuscript database

    The challenges that climate change presents humanity require an unprecedented ability to predict the responses of crops to environment and management. Geographic information systems (GIS) and crop simulation models are two powerful and highly complementary tools that are increasingly used for such p...

  5. Role-play simulations for climate change adaptation education and engagement

    NASA Astrophysics Data System (ADS)

    Rumore, Danya; Schenk, Todd; Susskind, Lawrence

    2016-08-01

    In order to effectively adapt to climate change, public officials and other stakeholders need to rapidly enhance their understanding of local risks and their ability to collaboratively and adaptively respond to them. We argue that science-based role-play simulation exercises -- a type of 'serious game' involving face-to-face mock decision-making -- have considerable potential as education and engagement tools for enhancing readiness to adapt. Prior research suggests role-play simulations and other serious games can foster public learning and encourage collective action in public policy-making contexts. However, the effectiveness of such exercises in the context of climate change adaptation education and engagement has heretofore been underexplored. We share results from two research projects that demonstrate the effectiveness of role-play simulations in cultivating climate change adaptation literacy, enhancing collaborative capacity and facilitating social learning. Based on our findings, we suggest such exercises should be more widely embraced as part of adaptation professionals' education and engagement toolkits.

  6. 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.

  7. Biome changes in Asia since the mid-Holocene - an analysis of different transient Earth system model simulations

    NASA Astrophysics Data System (ADS)

    Dallmeyer, Anne; Claussen, Martin; Ni, Jian; Cao, Xianyong; Wang, Yongbo; Fischer, Nils; Pfeiffer, Madlene; Jin, Liya; Khon, Vyacheslav; Wagner, Sebastian; Haberkorn, Kerstin; Herzschuh, Ulrike

    2017-02-01

    The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate-vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere-ocean(-vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon-westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5 to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert-steppe margin is shifted westward by 5° (1-9° in the individual simulations). The forest biomes are expanded north-westward by 2°, ranging from 0 to 4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.

  8. Simulation of Optimal Decision-Making Under the Impacts of Climate Change.

    PubMed

    Møller, Lea Ravnkilde; Drews, Martin; Larsen, Morten Andreas Dahl

    2017-07-01

    Climate change causes transformations to the conditions of existing agricultural practices appointing farmers to continuously evaluate their agricultural strategies, e.g., towards optimising revenue. In this light, this paper presents a framework for applying Bayesian updating to simulate decision-making, reaction patterns and updating of beliefs among farmers in a developing country, when faced with the complexity of adapting agricultural systems to climate change. We apply the approach to a case study from Ghana, where farmers seek to decide on the most profitable of three agricultural systems (dryland crops, irrigated crops and livestock) by a continuous updating of beliefs relative to realised trajectories of climate (change), represented by projections of temperature and precipitation. The climate data is based on combinations of output from three global/regional climate model combinations and two future scenarios (RCP4.5 and RCP8.5) representing moderate and unsubstantial greenhouse gas reduction policies, respectively. The results indicate that the climate scenario (input) holds a significant influence on the development of beliefs, net revenues and thereby optimal farming practices. Further, despite uncertainties in the underlying net revenue functions, the study shows that when the beliefs of the farmer (decision-maker) opposes the development of the realised climate, the Bayesian methodology allows for simulating an adjustment of such beliefs, when improved information becomes available. The framework can, therefore, help facilitating the optimal choice between agricultural systems considering the influence of climate change.

  9. Response of the tropical Pacific to abrupt climate change 8,200 years ago

    NASA Astrophysics Data System (ADS)

    Atwood, A. R.; Battisti, D.; Bitz, C. M.; Sachs, J. P.

    2017-12-01

    The relatively stable climate of the Holocene epoch was punctuated by a period of large and abrupt climate change ca. 8,200 yr BP, when an outburst of glacial meltwater into the Labrador Sea drove large and abrupt climate changes across the globe. However, little is known about the response of the tropical Pacific to this event. We present the first evidence for large perturbations to the eastern tropical Pacific climate, based on sedimentary biomarker and hydrogen isotopic records from a freshwater lake in the Galápagos Islands. We inform these reconstructions with freshwater forcing simulations performed with the Community Climate System Model version 4. Together, the biomarker records and model simulations provide evidence for a mechanistic link between (1) a southward shift of the Intertropical Convergence Zone in the eastern equatorial Pacific and (2) decreased frequency and/or intensity of Eastern Pacific El Niño events during the 8,200 BP event. While climate theory and modeling studies support a southward shift of the ITCZ in response to a weakened AMOC, the dynamical drivers for the observed change in ENSO variability are less well developed. To explore these linkages, we perform simulations with an intermediate complexity model of the tropical Pacific. These results provide valuable insight into the controls of tropical Pacific climate variability and the mechanisms behind the global response to abrupt climate change.

  10. Evaluation of regional climate simulations for air quality modelling purposes

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

    2013-05-01

    In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

  11. Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

    NASA Astrophysics Data System (ADS)

    Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

    2013-04-01

    Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.

  12. Eco-hydrologic model cascades: Simulating land use and climate change impacts on hydrology, hydraulics and habitats for fish and macroinvertebrates.

    PubMed

    Guse, Björn; Kail, Jochem; Radinger, Johannes; Schröder, Maria; Kiesel, Jens; Hering, Daniel; Wolter, Christian; Fohrer, Nicola

    2015-11-15

    Climate and land use changes affect the hydro- and biosphere at different spatial scales. These changes alter hydrological processes at the catchment scale, which impact hydrodynamics and habitat conditions for biota at the river reach scale. In order to investigate the impact of large-scale changes on biota, a cascade of models at different scales is required. Using scenario simulations, the impact of climate and land use change can be compared along the model cascade. Such a cascade of consecutively coupled models was applied in this study. Discharge and water quality are predicted with a hydrological model at the catchment scale. The hydraulic flow conditions are predicted by hydrodynamic models. The habitat suitability under these hydraulic and water quality conditions is assessed based on habitat models for fish and macroinvertebrates. This modelling cascade was applied to predict and compare the impacts of climate- and land use changes at different scales to finally assess their effects on fish and macroinvertebrates. Model simulations revealed that magnitude and direction of change differed along the modelling cascade. Whilst the hydrological model predicted a relevant decrease of discharge due to climate change, the hydraulic conditions changed less. Generally, the habitat suitability for fish decreased but this was strongly species-specific and suitability even increased for some species. In contrast to climate change, the effect of land use change on discharge was negligible. However, land use change had a stronger impact on the modelled nitrate concentrations affecting the abundances of macroinvertebrates. The scenario simulations for the two organism groups illustrated that direction and intensity of changes in habitat suitability are highly species-dependent. Thus, a joined model analysis of different organism groups combined with the results of hydrological and hydrodynamic models is recommended to assess the impact of climate and land use changes on river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

    NASA Astrophysics Data System (ADS)

    Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

    2017-12-01

    Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

  14. Changing Characteristics of convective storms: Results from a continental-scale convection-permitting climate simulations

    NASA Astrophysics Data System (ADS)

    Prein, A. F.; Ikeda, K.; Liu, C.; Bullock, R.; Rasmussen, R.

    2016-12-01

    Convective storms are causing extremes such as flooding, landslides, and wind gusts and are related to the development of tornadoes and hail. Convective storms are also the dominant source of summer precipitation in most regions of the Contiguous United States. So far little is known about how convective storms might change due to global warming. This is mainly because of the coarse grid spacing of state-of-the-art climate models that are not able to resolve deep convection explicitly. Instead, coarse resolution models rely on convective parameterization schemes that are a major source of errors and uncertainties in climate change projections. Convection-permitting climate simulations, with grid-spacings smaller than 4 km, show significant improvements in the simulation of convective storms by representing deep convection explicitly. Here we use a pair of 13-year long current and future convection-permitting climate simulations that cover large parts of North America. We use the Method for Object-Based Diagnostic Evaluation (MODE) that incorporates the time dimension (MODE-TD) to analyze the model performance in reproducing storm features in the current climate and to investigate their potential future changes. We show that the model is able to accurately reproduce the main characteristics of convective storms in the present climate. The comparison with the future climate simulation shows that convective storms significantly increase in frequency, intensity, and size. Furthermore, they are projected to move slower which could result in a substantial increase in convective storm-related hazards such as flash floods, debris flows, and landslides. Some regions, such as the North Atlantic, might experience a regime shift that leads to significantly stronger storms that are unrepresented in the current climate.

  15. Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

    2017-11-01

    Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

  16. Stochastic sensitivity analysis of nitrogen pollution to climate change in a river basin with complex pollution sources.

    PubMed

    Yang, Xiaoying; Tan, Lit; He, Ruimin; Fu, Guangtao; Ye, Jinyin; Liu, Qun; Wang, Guoqing

    2017-12-01

    It is increasingly recognized that climate change could impose both direct and indirect impacts on the quality of the water environment. Previous studies have mostly concentrated on evaluating the impacts of climate change on non-point source pollution in agricultural watersheds. Few studies have assessed the impacts of climate change on the water quality of river basins with complex point and non-point pollution sources. In view of the gap, this paper aims to establish a framework for stochastic assessment of the sensitivity of water quality to future climate change in a river basin with complex pollution sources. A sub-daily soil and water assessment tool (SWAT) model was developed to simulate the discharge, transport, and transformation of nitrogen from multiple point and non-point pollution sources in the upper Huai River basin of China. A weather generator was used to produce 50 years of synthetic daily weather data series for all 25 combinations of precipitation (changes by - 10, 0, 10, 20, and 30%) and temperature change (increases by 0, 1, 2, 3, and 4 °C) scenarios. The generated daily rainfall series was disaggregated into the hourly scale and then used to drive the sub-daily SWAT model to simulate the nitrogen cycle under different climate change scenarios. Our results in the study region have indicated that (1) both total nitrogen (TN) loads and concentrations are insensitive to temperature change; (2) TN loads are highly sensitive to precipitation change, while TN concentrations are moderately sensitive; (3) the impacts of climate change on TN concentrations are more spatiotemporally variable than its impacts on TN loads; and (4) wide distributions of TN loads and TN concentrations under individual climate change scenario illustrate the important role of climatic variability in affecting water quality conditions. In summary, the large variability in SWAT simulation results within and between each climate change scenario highlights the uncertainty of the impacts of climate change and the need to incorporate extreme conditions in managing water environment and developing climate change adaptation and mitigation strategies.

  17. Climate-suitable planting as a strategy for maintaining forest productivity and functional diversity.

    PubMed

    Duveneck, Matthew J; Scheller, Robert M

    2015-09-01

    Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass).

  18. Multi-Scale Simulations of Past and Future Projections of Hydrology in Lake Tahoe Basin, California-Nevada (Invited)

    NASA Astrophysics Data System (ADS)

    Niswonger, R. G.; Huntington, J. L.; Dettinger, M. D.; Rajagopal, S.; Gardner, M.; Morton, C. G.; Reeves, D. M.; Pohll, G. M.

    2013-12-01

    Water resources in the Tahoe basin are susceptible to long-term climate change and extreme events because it is a middle-altitude, snow-dominated basin that experiences large inter-annual climate variations. Lake Tahoe provides critical water supply for its basin and downstream populations, but changes in water supply are obscured by complex climatic and hydrologic gradients across the high relief, geologically complex basin. An integrated surface and groundwater model of the Lake Tahoe basin has been developed using GSFLOW to assess the effects of climate change and extreme events on surface and groundwater resources. Key hydrologic mechanisms are identified with this model that explains recent changes in water resources of the region. Critical vulnerabilities of regional water-supplies and hazards also were explored. Maintaining a balance between (a) accurate representation of spatial features (e.g., geology, streams, and topography) and hydrologic response (i.e., groundwater, stream, lake, and wetland flows and storages), and (b) computational efficiency, is a necessity for the desired model applications. Potential climatic influences on water resources are analyzed here in simulations of long-term water-availability and flood responses to selected 100-year climate-model projections. GSFLOW is also used to simulate a scenario depicting an especially extreme storm event that was constructed from a combination of two historical atmospheric-river storm events as part of the USGS MultiHazards Demonstration Project. Historical simulated groundwater levels, streamflow, wetlands, and lake levels compare well with measured values for a 30-year historical simulation period. Results are consistent for both small and large model grid cell sizes, due to the model's ability to represent water table altitude, streams, and other hydrologic features at the sub-grid scale. Simulated hydrologic responses are affected by climate change, where less groundwater resources will be available during more frequent droughts. Simulated floods for the region indicate issues related to drainage in the developed areas around Lake Tahoe, and necessary dam releases that create downstream flood risks.

  19. Changes in Moisture Flux over the Tibetan Plateau during 1979-2011: Insights from a High Resolution Simulation

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

    Gao, Yanhong; Leung, Lai-Yung R.; Zhang, Yongxin

    2015-05-15

    Net precipitation (precipitation minus evapotranspiration, P-E) changes between 1979 and 2011 from a high resolution regional climate simulation and its reanalysis forcing are analyzed over the Tibet Plateau (TP) and compared to the global land data assimilation system (GLDAS) product. The high resolution simulation better resolves precipitation changes than its coarse resolution forcing, which contributes dominantly to the improved P-E change in the regional simulation compared to the global reanalysis. Hence, the former may provide better insights about the drivers of P-E changes. The mechanism behind the P-E changes is explored by decomposing the column integrated moisture flux convergence intomore » thermodynamic, dynamic, and transient eddy components. High-resolution climate simulation improves the spatial pattern of P-E changes over the best available global reanalysis. High-resolution climate simulation also facilitates new and substantial findings regarding the role of thermodynamics and transient eddies in P-E changes reflected in observed changes in major river basins fed by runoff from the TP. The analysis revealed the contrasting convergence/divergence changes between the northwestern and southeastern TP and feedback through latent heat release as an important mechanism leading to the mean P-E changes in the TP.« less

  20. Vegetation-climate feedback causes reduced precipitation and tropical rainforest cover in CMIP5 regional Earth system model simulation over Africa

    NASA Astrophysics Data System (ADS)

    Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

    2012-12-01

    We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feed back to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feed back to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. Our study, the first application of a coupled Earth system model at regional scale and resolution over Africa, reveals that vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa.

  1. Deciphering the expression of climate change within the Lower Colorado River basin by stochastic simulation of convective rainfall

    NASA Astrophysics Data System (ADS)

    Bliss Singer, Michael; Michaelides, Katerina

    2017-10-01

    In drylands, convective rainstorms typically control runoff, streamflow, water supply and flood risk to human populations, and ecological water availability at multiple spatial scales. Since drainage basin water balance is sensitive to climate, it is important to improve characterization of convective rainstorms in a manner that enables statistical assessment of rainfall at high spatial and temporal resolution, and the prediction of plausible manifestations of climate change. Here we present a simple rainstorm generator, STORM, for convective storm simulation. It was created using data from a rain gauge network in one dryland drainage basin, but is applicable anywhere. We employ STORM to assess watershed rainfall under climate change simulations that reflect differences in wetness/storminess, and thus provide insight into observed or projected regional hydrologic trends. Our analysis documents historical, regional climate change manifesting as a multidecadal decline in rainfall intensity, which we suggest has negatively impacted ephemeral runoff in the Lower Colorado River basin, but has not contributed substantially to regional negative streamflow trends.

  2. Modelling the impact of climate change and atmospheric N deposition on French forests biodiversity.

    PubMed

    Rizzetto, Simon; Belyazid, Salim; Gégout, Jean-Claude; Nicolas, Manuel; Alard, Didier; Corcket, Emmanuel; Gaudio, Noémie; Sverdrup, Harald; Probst, Anne

    2016-06-01

    A dynamic coupled biogeochemical-ecological model was used to simulate the effects of nitrogen deposition and climate change on plant communities at three forest sites in France. The three sites had different forest covers (sessile oak, Norway spruce and silver fir), three nitrogen loads ranging from relatively low to high, different climatic regions and different soil types. Both the availability of vegetation time series and the environmental niches of the understory species allowed to evaluate the model for predicting the composition of the three plant communities. The calibration of the environmental niches was successful, with a model performance consistently reasonably high throughout the three sites. The model simulations of two climatic and two deposition scenarios showed that climate change may entirely compromise the eventual recovery from eutrophication of the simulated plant communities in response to the reductions in nitrogen deposition. The interplay between climate and deposition was strongly governed by site characteristics and histories in the long term, while forest management remained the main driver of change in the short term. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Towards process-informed bias correction of climate change simulations

    NASA Astrophysics Data System (ADS)

    Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

    2017-11-01

    Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

  4. CERES-Maize model-based simulation of climate change impacts on maize yields and potential adaptive measures in Heilongjiang Province, China.

    PubMed

    Lin, Yumei; Wu, Wenxiang; Ge, Quansheng

    2015-11-01

    Climate change would cause negative impacts on future agricultural production and food security. Adaptive measures should be taken to mitigate the adverse effects. The objectives of this study were to simulate the potential effects of climate change on maize yields in Heilongjiang Province and to evaluate two selected typical household-level autonomous adaptive measures (cultivar changes and planting time adjustments) for mitigating the risks of climate change based on the CERES-Maize model. The results showed that flowering duration and maturity duration of maize would be shortened in the future climate and thus maize yield would reduce by 11-46% during 2011-2099 relative to 1981-2010. Increased CO2 concentration would not benefit maize production significantly. However, substituting local cultivars with later-maturing ones and delaying the planting date could increase yields as the climate changes. The results provide insight regarding the likely impacts of climate change on maize yields and the efficacy of selected adaptive measures by presenting evidence-based implications and mitigation strategies for the potential negative impacts of future climate change. © 2014 Society of Chemical Industry.

  5. Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

    PubMed Central

    Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

    2013-01-01

    The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change. PMID:23593325

  6. Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China.

    PubMed

    Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

    2013-01-01

    The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems' response to global climate change. China's ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund-Potsdam-Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China's terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

  7. The Use of Climate Projections in the Modelling of Bud Burst

    NASA Astrophysics Data System (ADS)

    O'Neill, Bridget F.; Caffara, Amelia; Gleeson, Emily; Semmler, Tido; McGrath, Ray; Donnelly, Alison

    2010-05-01

    Recent changes in global climate, such as increasing temperature, have had notable effects on the phenology (timing of biological events) of plants. The effects are variable across habitats and between species, but increasing temperatures have been shown to advance certain key phenophases of trees, such as bud burst (beginning of leaf unfolding). This project considered climate change impacts on phenology of plants at a local scale in Ireland. The output from the ENSEMBLES climate simulations were down-scaled to Ireland and utilised by a phenological model to project changes over the next 50-100 years. This project helps to showcase the potential use of climate simulations in phenological research.

  8. 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...

  9. Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

    NASA Astrophysics Data System (ADS)

    Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

    2016-10-01

    We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

  10. An Assessment of IPCC 20th Century Climate Simulations Using the 15-year Sea Level Record from Altimetry

    NASA Astrophysics Data System (ADS)

    Leuliette, E.; Nerem, S.; Jakub, T.

    2006-07-01

    Recen tly, multiple ensemble climate simulations h ave been produced for th e forthco ming Fourth A ssessment Report of the Intergovernmental Panel on Climate Change (IPCC). N early two dozen coupled ocean- atmo sphere models have contr ibuted output for a variety of climate scen arios. One scenar io, the climate of the 20th century exper imen t (20C3 M), produces model output that can be comp ared to th e long record of sea level provided by altimetry . Generally , the output from the 20C3M runs is used to initialize simulations of future climate scenar ios. Hence, v alidation of the 20 C3 M experiment resu lts is crucial to the goals of th e IPCC. We present compar isons of global mean sea level (G MSL) , global mean steric sea level change, and regional patterns of sea lev el chang e from these models to r esults from altimetry, tide gauge measurements, and reconstructions.

  11. Impact of Future Emissions and Climate Change on Surface Ozone over China

    NASA Astrophysics Data System (ADS)

    Ma, C. T.; Westervelt, D. M.; Fiore, A. M.; Rieder, H. E.; Kinney, P.; Wang, S.; Correa, G. J. P.

    2017-12-01

    China's immense ambient air pollution problem and world-leading greenhouse gas emissions place it at the forefront of global efforts to address these related environmental concerns. Here, we analyze the impact of ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) future emissions scenarios representative of current legislation (CLE) and maximum technically feasible emissions reductions (MFR) on surface ozone (O3) concentrations over China in the 2030s and 2050s, in the context of a changing climate. We use a suite of simulations performed with the NOAA Geophysical Fluid Dynamics Laboratory's AM3 global chemistry-climate model. To estimate the impact of climate change in isolation on Chinese air quality, we hold emissions of air pollutants including O3 precursors fixed at 2015 levels but allow climate (global sea surface temperatures and sea ice cover) to change according to decadal averages for the years 2026-2035 and 2046-2055 from a three-member ensemble of GFDL-CM3 simulations under the RCP8.5 high warming scenario. Evaluation of the present-day simulation (2015 CLE) with observations from 1497 chiefly urban air quality monitoring stations shows that simulated surface O3 is positively biased by 26 ppb on average over the domain of China. Previous studies, however, have shown that the modeled ozone response to changes in NOx emissions over the Eastern United States mirrors the magnitude and structure of observed changes in maximum daily average 8-hour (MDA8) O3 distributions. Therefore, we use the model's simulated changes for the 2030s and 2050s to project changes in policy-relevant MDA8 O3 concentrations. We find an overall increase in MDA8 O3 for CLE scenarios in which emissions of NOx precursors are projected to increase, and under MFR scenarios, an overall decrease, with the highest changes occurring in summertime for both 2030 and 2050 MFR. Under climate change alone, the model simulates a mean summertime decrease of 1.3 ppb and wintertime increase of 3.3 ppb by 2050. Adjustment of the observed site-level MDA8 O3 distribution to reflect regionally interpolated projected changes from AM3 allows us to examine changes in the number of days in exceedance of MDA8 O3 Level I (50 ppb) and Level II (80 ppb) Chinese national ambient air quality standards.

  12. Change in atmospheric mineral aerosols in response to climate: Last glacial period, preindustrial, modern, and doubled carbon dioxide climates

    USGS Publications Warehouse

    Mahowald, N.M.; Muhs, D.R.; Levis, S.; Rasch, P.J.; Yoshioka, M.; Zender, C.S.; Luo, C.

    2006-01-01

    Desert dust simulations generated by the National Center for Atmospheric Research's Community Climate System Model for the current climate are shown to be consistent with present day satellite and deposition data. The response of the dust cycle to last glacial maximum, preindustrial, modern, and doubled-carbon dioxide climates is analyzed. Only natural (non-land use related) dust sources are included in this simulation. Similar to some previous studies, dust production mainly responds to changes in the source areas from vegetation changes, not from winds or soil moisture changes alone. This model simulates a +92%, +33%, and -60% change in dust loading for the last glacial maximum, preindustrial, and doubled-carbon dioxide climate, respectively, when impacts of carbon dioxide fertilization on vegetation are included in the model. Terrestrial sediment records from the last glacial maximum compiled here indicate a large underestimate of deposition in continental regions, probably due to the lack of simulation of glaciogenic dust sources. In order to include the glaciogenic dust sources as a first approximation, we designate the location of these sources, and infer the size of the sources using an inversion method that best matches the available data. The inclusion of these inferred glaciogenic dust sources increases our dust flux in the last glacial maximum from 2.1 to 3.3 times current deposition. Copyright 2006 by the American Geophysical Union.

  13. Using Coupled Groundwater-Surface Water Models to Simulate Eco-Regional Differences in Climate Change Impacts on Hydrological Drought Regimes in British Columbia

    NASA Astrophysics Data System (ADS)

    Dierauer, J. R.; Allen, D. M.

    2016-12-01

    Climate change is expected to lead to an increase in extremes, including daily maximum temperatures, heat waves, and meteorological droughts, which will likely result in shifts in the hydrological drought regime (i.e. the frequency, timing, duration, and severity of drought events). While many studies have used hydrologic models to simulate climate change impacts on water resources, only a small portion of these studies have analyzed impacts on low flows and/or hydrological drought. This study is the first to use a fully coupled groundwater-surface water (gw-sw) model to study climate change impacts on hydrological drought. Generic catchment-scale gw-sw models were created for each of the six major eco-regions in British Columbia using the MIKE-SHE/MIKE-11 modelling code. Daily precipitation and temperature time series downscaled using bias-correction spatial disaggregation for the simulated period of 1950-2100 were obtained from the Pacific Climate Institute Consortium (PCIC). Streamflow and groundwater drought events were identified from the simulated time series for each catchment model using the moving window quantile threshold. The frequency, timing, duration, and severity of drought events were compared between the reference period (1961-2000) and two future time periods (2031-2060, 2071-2100). Results show how hydrological drought regimes across the different British Columbia eco-regions will be impacted by climate change.

  14. Impacts of Interactive Stratospheric Chemistry on Antarctic and Southern Ocean Climate Change in the Goddard Earth Observing System Version 5 (GEOS-5)

    NASA Technical Reports Server (NTRS)

    Li, Feng; Vikhliaev, Yury V.; Newman, Paul A.; Pawson, Steven; Perlwitz, Judith; Waugh, Darryn W.; Douglass, Anne R.

    2016-01-01

    Stratospheric ozone depletion plays a major role in driving climate change in the Southern Hemisphere. To date, many climate models prescribe the stratospheric ozone layer's evolution using monthly and zonally averaged ozone fields. However, the prescribed ozone underestimates Antarctic ozone depletion and lacks zonal asymmetries. In this study we investigate the impact of using interactive stratospheric chemistry instead of prescribed ozone on climate change simulations of the Antarctic and Southern Ocean. Two sets of 1960-2010 ensemble transient simulations are conducted with the coupled ocean version of the Goddard Earth Observing System Model, version 5: one with interactive stratospheric chemistry and the other with prescribed ozone derived from the same interactive simulations. The model's climatology is evaluated using observations and reanalysis. Comparison of the 1979-2010 climate trends between these two simulations reveals that interactive chemistry has important effects on climate change not only in the Antarctic stratosphere, troposphere, and surface, but also in the Southern Ocean and Antarctic sea ice. Interactive chemistry causes stronger Antarctic lower stratosphere cooling and circumpolar westerly acceleration during November-December-January. It enhances stratosphere-troposphere coupling and leads to significantly larger tropospheric and surface westerly changes. The significantly stronger surface wind stress trends cause larger increases of the Southern Ocean Meridional Overturning Circulation, leading to year-round stronger ocean warming near the surface and enhanced Antarctic sea ice decrease.

  15. Hydrologic and water quality sensitivity to climate and land ...

    EPA Pesticide Factsheets

    This page describes a current EPA ORD project. No project report or other download is available at this time. Please see the section Next Steps below for a timeline of anticipated products of this work. Background: Projected changes in climate during the next century could cause or contribute to increased flooding, drought, water quality degradation, and ecosystem impairment. The effects of climate change in different watersheds will vary due to regional differences in climate change, physiographic setting, and interaction with land-use, pollutant sources, and water management in different locations. EPA is conducting watershed modeling to develop hydrologic and water quality change scenarios for 20 relatively large U.S. watersheds. Watershed modeling will be conducted using the Hydrologic Simulation Program-FORTRAN (HSPF) and Soil Water Assessment Tool (SWAT) watershed models. Study areas range from about 10,000-15,000 square miles in size, and will cover nearly every ecoregion in the United States and a range of hydro-climatic conditions. A range of hydrologic and water quality endpoints will be determined for each watershed simulation. Endpoints will be selected to inform upon a range of stream flow, water quality, aquatic ecosystem, and EPA program management goals and targets. Model simulations will be conducted to evaluate a range of projected future (2040-2070) changes in climate and land-use. Simulations will include baseline conditions,

  16. Change of ocean circulation in the East Asian Marginal Seas under different climate conditions

    NASA Astrophysics Data System (ADS)

    Min, Hong Sik; Kim, Cheol-Ho; Kim, Young Ho

    2010-05-01

    Global climate models do not properly resolve an ocean environment in the East Asian Marginal Seas (EAMS), which is mainly due to a poor representation of the topography in continental shelf region and a coarse spatial resolution. To examine a possible change of ocean environment under global warming in the EAMS, therefore we used North Pacific Regional Ocean Model. The regional model was forced by atmospheric conditions extracted from the simulation results of the global climate models for the 21st century projected by the IPCC SRES A1B scenario as well as the 20th century. The North Pacific Regional Ocean model simulated a detailed pattern of temperature change in the EAMS showing locally different rising or falling trend under the future climate condition, while the global climate models simulated a simple pattern like an overall increase. Changes of circulation pattern in the EAMS such as an intrusion of warm water into the Yellow Sea as well as the Kuroshio were also well resolved. Annual variations in volume transports through the Taiwan Strait and the Korea Strait under the future condition were simulated to be different from those under present condition. Relative ratio of volume transport through the Soya Strait to the Tsugaru Strait also responded to the climate condition.

  17. Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

    NASA Technical Reports Server (NTRS)

    Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.; hide

    2017-01-01

    Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

  18. Evaluating the variability in surface water reservoir planning characteristics during climate change impacts assessment

    NASA Astrophysics Data System (ADS)

    Soundharajan, Bankaru-Swamy; Adeloye, Adebayo J.; Remesan, Renji

    2016-07-01

    This study employed a Monte-Carlo simulation approach to characterise the uncertainties in climate change induced variations in storage requirements and performance (reliability (time- and volume-based), resilience, vulnerability and sustainability) of surface water reservoirs. Using a calibrated rainfall-runoff (R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change-perturbed future runoff scenarios. The resulting runoff ensembles were used to force simulation models of the behaviour of the reservoir to produce 'populations' of required reservoir storage capacity to meet demands, and the performance. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the variability in the impacts. The methodology was applied to the Pong reservoir on the Beas River in northern India. The reservoir serves irrigation and hydropower needs and the hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall, both of which are predicted to change due to climate change. The results show that required reservoir capacity is highly variable with a coefficient of variation (CV) as high as 0.3 as the future climate becomes drier. Of the performance indices, the vulnerability recorded the highest variability (CV up to 0.5) while the volume-based reliability was the least variable. Such variabilities or uncertainties will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of their sheer magnitudes as obtained in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.

  19. The implication of irrigation in climate change impact assessment: a European-wide study.

    PubMed

    Zhao, Gang; Webber, Heidi; Hoffmann, Holger; Wolf, Joost; Siebert, Stefan; Ewert, Frank

    2015-11-01

    This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982-2006) and three SRES scenarios (B1, B2 and A1B, 2040-2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE . We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr(-1) ). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area. © 2015 John Wiley & Sons Ltd.

  20. Environmental water demand assessment under climate change conditions.

    PubMed

    Sarzaeim, Parisa; Bozorg-Haddad, Omid; Fallah-Mehdipour, Elahe; Loáiciga, Hugo A

    2017-07-01

    Measures taken to cope with the possible effects of climate change on water resources management are key for the successful adaptation to such change. This work assesses the environmental water demand of the Karkheh river in the reach comprising Karkheh dam to the Hoor-al-Azim wetland, Iran, under climate change during the period 2010-2059. The assessment of the environmental demand applies (1) representative concentration pathways (RCPs) and (2) downscaling methods. The first phase of this work projects temperature and rainfall in the period 2010-2059 under three RCPs and with two downscaling methods. Thus, six climatic scenarios are generated. The results showed that temperature and rainfall average would increase in the range of 1.7-5.2 and 1.9-9.2%, respectively. Subsequently, flows corresponding to the six different climatic scenarios are simulated with the unit hydrographs and component flows from rainfall, evaporation, and stream flow data (IHACRES) rainfall-runoff model and are input to the Karkheh reservoir. The simulation results indicated increases of 0.9-7.7% in the average flow under the six simulation scenarios during the period of analysis. The second phase of this paper's methodology determines the monthly minimum environmental water demands of the Karkheh river associated with the six simulation scenarios using a hydrological method. The determined environmental demands are compared with historical ones. The results show that the temporal variation of monthly environmental demand would change under climate change conditions. Furthermore, some climatic scenarios project environmental water demand larger than and some of them project less than the baseline one.

  1. Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

    NASA Astrophysics Data System (ADS)

    Reyer, Christopher P. O.; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G.; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P.; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Guerra Hernández, Juan; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J.; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João HN; Paulo, Joana A.; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E.; Hanewinkel, Marc

    2017-03-01

    Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

  2. Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

    PubMed Central

    Reyer, Christopher P O; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Hernández, Juan Guerra; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João HN; Paulo, Joana A; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E; Hanewinkel, Marc

    2017-01-01

    Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures. PMID:28855959

  3. Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests?

    PubMed

    Reyer, Christopher P O; Bathgate, Stephen; Blennow, Kristina; Borges, Jose G; Bugmann, Harald; Delzon, Sylvain; Faias, Sonia P; Garcia-Gonzalo, Jordi; Gardiner, Barry; Gonzalez-Olabarria, Jose Ramon; Gracia, Carlos; Hernández, Juan Guerra; Kellomäki, Seppo; Kramer, Koen; Lexer, Manfred J; Lindner, Marcus; van der Maaten, Ernst; Maroschek, Michael; Muys, Bart; Nicoll, Bruce; Palahi, Marc; Palma, João Hn; Paulo, Joana A; Peltola, Heli; Pukkala, Timo; Rammer, Werner; Ray, Duncan; Sabaté, Santiago; Schelhaas, Mart-Jan; Seidl, Rupert; Temperli, Christian; Tomé, Margarida; Yousefpour, Rasoul; Zimmermann, Niklaus E; Hanewinkel, Marc

    2017-03-16

    Recent studies projecting future climate change impacts on forests mainly consider either the effects of climate change on productivity or on disturbances. However, productivity and disturbances are intrinsically linked because 1) disturbances directly affect forest productivity (e.g. via a reduction in leaf area, growing stock or resource-use efficiency), and 2) disturbance susceptibility is often coupled to a certain development phase of the forest with productivity determining the time a forest is in this specific phase of susceptibility. The objective of this paper is to provide an overview of forest productivity changes in different forest regions in Europe under climate change, and partition these changes into effects induced by climate change alone and by climate change and disturbances. We present projections of climate change impacts on forest productivity from state-of-the-art forest models that dynamically simulate forest productivity and the effects of the main European disturbance agents (fire, storm, insects), driven by the same climate scenario in seven forest case studies along a large climatic gradient throughout Europe. Our study shows that, in most cases, including disturbances in the simulations exaggerate ongoing productivity declines or cancel out productivity gains in response to climate change. In fewer cases, disturbances also increase productivity or buffer climate-change induced productivity losses, e.g. because low severity fires can alleviate resource competition and increase fertilization. Even though our results cannot simply be extrapolated to other types of forests and disturbances, we argue that it is necessary to interpret climate change-induced productivity and disturbance changes jointly to capture the full range of climate change impacts on forests and to plan adaptation measures.

  4. Vegetation zones in changing climate

    NASA Astrophysics Data System (ADS)

    Belda, Michal; Holtanova, Eva; Halenka, Tomas; Kalvova, Jaroslava

    2017-04-01

    Climate patterns analysis can be performed for individual climate variables separately or the data can be aggregated using e.g. some kind of climate classification. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. Thus, the Köppen-Trewartha classification provides integrated assessment of temperature and precipitation together with their annual cycle as well. This way climate classifications also can be used as a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes. The Köppen-Trewartha classification is applied on full CMIP5 family of more than 40 GCM simulations and CRU dataset for comparison. This evaluation provides insight on the GCM performance and errors for simulations of the 20th century climate. Common regions are identified, such as Australia or Amazonia, where many state-of-the-art models perform inadequately. Moreover, the analysis of the CMIP5 ensemble for future under RCP 4.5 and RCP 8.5 is performed to assess the climate change for future. There are significant changes for some types in most models e.g. increase of savanna and decrease of tundra for the future climate. For some types significant shifts in latitude can be seen when studying their geographical location in selected continental areas, e.g. toward higher latitudes for boreal climate. Quite significant uncertainty can be seen for some types. For Europe, EuroCORDEX results for both 0.11 and 0.44 degree resolution are validated using Köppen-Trewartha types in comparison to E-OBS based classification. ERA-Interim driven simulations are compared to both present conditions of CMIP5 models as well as their downscaling by EuroCORDEX RCMs. Finally, the climate change signal assessment is provided using the individual climate types. In addition to the changes assessed similarly as for GCMs analysis in terms of the area of individual types, in the continental scale some shifts of boundaries between the selected types can be studied as well providing the information on climate change signal. The shift of the boundary between the boreal zone and continental temperate zone to the north is clearly seen in most simulations as well as eastern move of the boundary of the maritime and continental type of temperate zone. However, there can be quite clear problem with model biases in climate types association. When analysing climate types in Europe and their shifts under climate change using Köppen-Trewartha classification (KTC), for the temperate climate type there are subtypes defined following the continentality patterns, and we can see their generally meridionally located divide across Europe shifted to the east. There is a question whether this is realistic or rather due to the simplistic condition in KTC following the winter minimum temperature, while other continentality indices consider rather the amplitude of temperature during the year. This leads us to connect our analysis of climate change effects using climate classification to the more detailed analysis of continentality patterns development in Europe to provide better insight on the climate regimes and to verify the continentality conditions, their definitions and climate change effects on them. The comparison of several selected continentality indices is shown.

  5. Response of North American freshwater lakes to simulated future climates

    USGS Publications Warehouse

    Hostetler, S.W.; Small, E.E.

    1999-01-01

    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.

  6. Evaluation of high-resolution climate simulations for West Africa using COSMO-CLM

    NASA Astrophysics Data System (ADS)

    Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Laux, Patrick; Heinzeller, Dominikus; Kunstmann, Harald; Sarr, Abdoulaye; Thierno Gaye, Amadou

    2017-04-01

    The climate change modeling activities within the WASCAL program (West African Science Service Center on Climate Change and Adapted Land Use) concentrate on the provisioning of future climate change scenario data at high spatial and temporal resolution and quality in West Africa. Such information is highly required for impact studies in water resources and agriculture for the development of reliable climate change adaptation and mitigation strategies. In this study, we present a detailed evaluation of high simulation runs based on the regional climate model, COSMO model in CLimate Mode (COSMO-CLM). The model is applied over West Africa in a nested approach with two simulation domains at 0.44° and 0.11° resolution using reanalysis data from ERA-Interim (1979-2013). The models runs are compared to several state-of-the-art observational references (e.g., CRU, CHIRPS) including daily precipitation data provided by national meteorological services in West Africa. Special attention is paid to the reproduction of the dynamics of the West African Monsoon (WMA), its associated precipitation patterns and crucial agro-climatological indices such as the onset of the rainy season. In addition, first outcomes of the regional climate change simulations driven by MPI-ESM-LR are presented for a historical period (1980 to 2010) and two future periods (2020 to 2050, 2070 to 2100). The evaluation of the reanalysis runs shows that COSMO-CLM is able to reproduce the observed major climate characteristics including the West African Monsoon within the range of comparable RCM evaluations studies. However, substantial uncertainties remain, especially in the Sahel zone. The added value of the higher resolution of the nested run is reflected in a smaller bias in extreme precipitation statistics with respect to the reference data.

  7. Future Climate Change in the Baltic Sea Area

    NASA Astrophysics Data System (ADS)

    Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak

    2015-04-01

    Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties.

  8. Can the combined use of an ensemble based modelling approach and the analysis of measured meteorological trends lead to increased confidence in climate change impact assessments?

    NASA Astrophysics Data System (ADS)

    Gädeke, Anne; Koch, Hagen; Pohle, Ina; Grünewald, Uwe

    2014-05-01

    In anthropogenically heavily impacted river catchments, such as the Lusatian river catchments of Spree and Schwarze Elster (Germany), the robust assessment of possible impacts of climate change on the regional water resources is of high relevance for the development and implementation of suitable climate change adaptation strategies. Large uncertainties inherent in future climate projections may, however, reduce the willingness of regional stakeholder to develop and implement suitable adaptation strategies to climate change. This study provides an overview of different possibilities to consider uncertainties in climate change impact assessments by means of (1) an ensemble based modelling approach and (2) the incorporation of measured and simulated meteorological trends. The ensemble based modelling approach consists of the meteorological output of four climate downscaling approaches (DAs) (two dynamical and two statistical DAs (113 realisations in total)), which drive different model configurations of two conceptually different hydrological models (HBV-light and WaSiM-ETH). As study area serve three near natural subcatchments of the Spree and Schwarze Elster river catchments. The objective of incorporating measured meteorological trends into the analysis was twofold: measured trends can (i) serve as a mean to validate the results of the DAs and (ii) be regarded as harbinger for the future direction of change. Moreover, regional stakeholders seem to have more trust in measurements than in modelling results. In order to evaluate the nature of the trends, both gradual (Mann-Kendall test) and step changes (Pettitt test) are considered as well as both temporal and spatial correlations in the data. The results of the ensemble based modelling chain show that depending on the type (dynamical or statistical) of DA used, opposing trends in precipitation, actual evapotranspiration and discharge are simulated in the scenario period (2031-2060). While the statistical DAs simulate a strong decrease in future long term annual precipitation, the dynamical DAs simulate a tendency towards increasing precipitation. The trend analysis suggests that precipitation has not changed significantly during the period 1961-2006. Therefore, the decrease simulated by the statistical DAs should be interpreted as a rather dry future projection. Concerning air temperature, measured and simulated trends agree on a positive trend. Also the uncertainty related to the hydrological model within the climate change modelling chain is comparably low when long-term averages are considered but increases significantly during extreme events. This proposed framework of combining an ensemble based modelling approach with measured trend analysis is a promising approach for regional stakeholders to gain more confidence into the final results of climate change impact assessments. However, climate change impact assessments will remain highly uncertain. Thus, flexible adaptation strategies need to be developed which should not only consider climate but also other aspects of global change.

  9. Impacts of climate change and internal climate variability on french rivers streamflows

    NASA Astrophysics Data System (ADS)

    Dayon, Gildas; Boé, Julien; Martin, Eric

    2016-04-01

    The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

  10. Climate change impacts on extreme events in the United States: an uncertainty analysis

    EPA Science Inventory

    Extreme weather and climate events, such as heat waves, droughts and severe precipitation events, have substantial impacts on ecosystems and the economy. However, future climate simulations display large uncertainty in mean changes. As a result, the uncertainty in future changes ...

  11. Statistical structure of intrinsic climate variability under global warming

    NASA Astrophysics Data System (ADS)

    Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

    2017-04-01

    Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

  12. Evaluating climate models: Should we use weather or climate observations?

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

    Oglesby, Robert J; Erickson III, David J

    2009-12-01

    Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

  13. Seasonal variations of soil erosion in UK under climate change: simulations with the use of high-resolution regional climatic models

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Kendon, Elizabeth; Constantine, José Antonio; Schindewolf, Marcus; Hall, Ian

    2017-04-01

    Climate change is expected to have a significant impact on the hydrological cycle, twenty-first century climate change simulations for Great Britain forecast an increase of surface runoff and flooding frequency. Once quality and resolution of the simulated rainfall deeply influence the results, we adopted rainfall simulations issued of a high-resolution climate model recently carried out for extended periods (13 years for present-day and future periods 2100) at 1.5 km grid scale over the south of the United Kingdom (simulations, which for the future period use the Intergovernmental Panel on Climate Change RCP 8.5 scenario, Kendon et al., 2014). We simulated soil erosion with 3D soil erosion model Schmidt (1990) on two catchments of Great Britain: the Rother catchment (350 km2) in West Sussex, England, because it has reported some of the most erosive events observed during the last 50 years in the UK, and the Conwy catchment (628 Km2) in North Wales, which is extremely resilient to soil erosion because of the abundant natural vegetation. Estimation of changes in soil moisture, saturation deficit as well as vegetation cover at daily time step have been done with the Joint UK Land Environment Simulator (JULES) (Best et al, 2011). Our results confirm the Rother catchment is the most erosive, while the Conwy catchment is the more resilient to soil erosion. Sediment production is perceived increase in both cases for the end of the century (27% and 50%, respectively). Seasonal disaggregation of the results revels that, while the most part of soil erosion is produced in winter months (DJF), the higher soil erosion variability for future periods is observed in summer (JJA). This behaviour is supported by the rainfall simulation analyse which highlighted this dual behaviour in precipitations.

  14. Modeling the Impacts of Global Climate and Regional Land Use Change on Regional Climate, Air Quality and Public Health in the New York Metropolitan Region

    NASA Astrophysics Data System (ADS)

    Rosenthal, J. E.; Knowlton, K. M.; Kinney, P. L.

    2002-12-01

    There is an imminent need to downscale the global climate models used by international consortiums like the IPCC (Intergovernmental Panel on Climate Change) to predict the future regional impacts of climate change. To meet this need, a "place-based" climate model that makes specific regional projections about future environmental conditions local inhabitants could face is being created by the Mailman School of Public Health at Columbia University, in collaboration with other researchers and universities, for New York City and the 31 surrounding counties. This presentation describes the design and initial results of this modeling study, aimed at simulating the effects of global climate change and regional land use change on climate and air quality over the northeastern United States in order to project the associated public health impacts in the region. Heat waves and elevated concentrations of ozone and fine particles are significant current public health stressors in the New York metropolitan area. The New York Climate and Health Project is linking human dimension and natural sciences models to assess the potential for future public health impacts from heat stress and air quality, and yield improved tools for assessing climate change impacts. The model will be applied to the NY metropolitan east coast region. The following questions will be addressed: 1. What changes in the frequency and severity of extreme heat events are likely to occur over the next 80 years due to a range of possible scenarios of land use and land cover (LU/LC) and climate change in the region? 2. How might the frequency and severity of episodic concentrations of ozone (O3) and airborne particulate matter smaller than 2.5 æm in diameter (PM2.5) change over the next 80 years due to a range of possible scenarios of land use and climate change in the metropolitan region? 3. What is the range of possible human health impacts of these changes in the region? 4. How might projected future human exposures and responses to heat stress and air quality differ as a function of socio-economic status and race/ethnicity across the region? The model systems used for this study are the Goddard Institute for Space Studies (GISS) Global Atmosphere-Ocean Model; the Regional Atmospheric Modeling System (RAMS) and PennState/NCAR MM5 mesoscale meteorological models; the SLEUTH land use model; the Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE); the Community Multiscale Air Quality (CMAQ) and Comprehensive Air Quality Model with Extensions (CAMx) models for simulating regional air quality; and exposure-risk coefficients for assessing population health impacts based on exposure to extreme heat, fine particulates (PM2.5) and ozone. Two different IPCC global emission scenarios and two different regional land use growth scenarios are considered in the simulations, spanning a range of possible futures. In addition to base simulations for selected time periods in the decade 1990 - 2000, the integrated model is used to simulate future scenarios in the 2020s, 2050s, and 2080s. Predictions from both the meteorological models and the air quality models are compared against available observations for the simulations in the 1990s to establish baseline model performance. A series of sensitivity tests will address whether changes in meteorology due to global climate change, changes in regional land use, or changes in emissions have the largest impact on predicted ozone and particulate matter concentrations.

  15. Natural and anthropogenic land cover change and its impact on the regional climate and hydrological extremes over Sanjiangyuan region

    NASA Astrophysics Data System (ADS)

    Ji, P.; Yuan, X.

    2017-12-01

    Located in the northern Tibetan Plateau, Sanjiangyuan is the headwater region of the Yellow River, Yangtze River and Mekong River. Besides climate change, natural and human-induced land cover change (e.g., Graze for Grass Project) is also influencing the regional hydro-climate and hydrological extremes significantly. To quantify their impacts, a land surface model (LSM) with consideration of soil moisture-lateral surface flow interaction and quasi-three-dimensional subsurface flow, is used to conduct long-term high resolution simulations driven by China Meteorological Administration Land Data Assimilation System forcing data and different land cover scenarios. In particular, the role of surface and subsurface lateral flows is also analyzed by comparing with typical one-dimensional models. Lateral flows help to simulate soil moisture variability caused by topography at hyper-resolution (e.g., 100m), which is also essential for simulating hydrological extremes including soil moisture dryness/wetness and high/low flows. The LSM will also be coupled with a regional climate model to simulate the effect of natural and anthropogenic land cover change on regional climate, with particular focus on the land-atmosphere coupling at different resolutions with different configurations in modeling land surface hydrology.

  16. Simulated Climate Impacts of Mexico City's Historical Urban Expansion

    NASA Astrophysics Data System (ADS)

    Benson-Lira, Valeria

    Urbanization, a direct consequence of land use and land cover change, is responsible for significant modification of local to regional scale climates. It is projected that the greatest urban growth of this century will occur in urban areas in the developing world. In addition, there is a significant research gap in emerging nations concerning this topic. Thus, this research focuses on the assessment of climate impacts related to urbanization on the largest metropolitan area in Latin America: Mexico City. Numerical simulations using a state-of-the-science regional climate model are utilized to address a trio of scientifically relevant questions with wide global applicability. The importance of an accurate representation of land use and land cover is first demonstrated through comparison of numerical simulations against observations. Second, the simulated effect of anthropogenic heating is quantified. Lastly, numerical simulations are performed using pre-historic scenarios of land use and land cover to examine and quantify the impact of Mexico City's urban expansion and changes in surface water features on its regional climate.

  17. Multicentury changes in ocean and land contributions to the climate-carbon feedback

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

    Randerson, J. T.; Lindsay, K.; Munoz, E.

    Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO 2. Each simulation had a different degree of radiative coupling for CO 2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surfacemore » air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO 2, warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO 2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.« less

  18. Multicentury changes in ocean and land contributions to the climate-carbon feedback

    NASA Astrophysics Data System (ADS)

    Randerson, J. T.; Lindsay, K.; Munoz, E.; Fu, W.; Moore, J. K.; Hoffman, F. M.; Mahowald, N. M.; Doney, S. C.

    2015-06-01

    Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO2. Each simulation had a different degree of radiative coupling for CO2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surface air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO2, warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.

  19. A first look at the influence of anthropogenic climate change on the future delivery of fluvial sediment to the Ganges-Brahmaputra-Meghna delta.

    PubMed

    Darby, Stephen E; Dunn, Frances E; Nicholls, Robert J; Rahman, Munsur; Riddy, Liam

    2015-09-01

    We employ a climate-driven hydrological water balance and sediment transport model (HydroTrend) to simulate future climate-driven sediment loads flowing into the Ganges-Brahmaputra-Meghna (GBM) mega-delta. The model was parameterised using high-quality topographic data and forced with daily temperature and precipitation data obtained from downscaled Regional Climate Model (RCM) simulations for the period 1971-2100. Three perturbed RCM model runs were selected to quantify the potential range of future climate conditions associated with the SRES A1B scenario. Fluvial sediment delivery rates to the GBM delta associated with these climate data sets are projected to increase under the influence of anthropogenic climate change, albeit with the magnitude of the increase varying across the two catchments. Of the two study basins, the Brahmaputra's fluvial sediment load is predicted to be more sensitive to future climate change. Specifically, by the middle part of the 21(st) century, our model results suggest that sediment loads increase (relative to the 1981-2000 baseline period) over a range of between 16% and 18% (depending on climate model run) for the Ganges, but by between 25% and 28% for the Brahmaputra. The simulated increase in sediment flux emanating from the two catchments further increases towards the end of the 21(st) century, reaching between 34% and 37% for the Ganges and between 52% and 60% for the Brahmaputra by the 2090s. The variability in these changes across the three climate change simulations is small compared to the changes, suggesting they represent a significant increase. The new data obtained in this study offer the first estimate of whether and how anthropogenic climate change may affect the delivery of fluvial sediment to the GBM delta, informing assessments of the future sustainability and resilience of one of the world's most vulnerable mega-deltas. Specifically, such significant increases in future sediment loads could increase the resilience of the delta to sea-level rise by giving greater potential for vertical accretion. However, these increased sediment fluxes may not be realised due to uncertainties in the monsoon related response to climate change or other human-induced changes in the catchment: this is a subject for further research.

  20. Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

    Cook, Kerry H.; Vizy, Edward

    The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

  1. Fire modulates climate change response of simulated aspen distribution across topoclimatic gradients in a semi-arid montane landscape

    USGS Publications Warehouse

    Yang, Jian; Weisberg, Peter J.; Shinneman, Douglas; Dilts, Thomas E.; Earnst, Susan L.; Scheller, Robert M

    2015-01-01

    Content Changing aspen distribution in response to climate change and fire is a major focus of biodiversity conservation, yet little is known about the potential response of aspen to these two driving forces along topoclimatic gradients. Objective This study is set to evaluate how aspen distribution might shift in response to different climate-fire scenarios in a semi-arid montane landscape, and quantify the influence of fire regime along topoclimatic gradients. Methods We used a novel integration of a forest landscape succession and disturbance model (LANDIS-II) with a fine-scale climatic water deficit approach to simulate dynamics of aspen and associated conifer and shrub species over the next 150 years under various climate-fire scenarios. Results Simulations suggest that many aspen stands could persist without fire for centuries under current climate conditions. However, a simulated 2–5 °C increase in temperature caused a substantial reduction of aspen coverage at lower elevations and a modest increase at upper elevations, leading to an overall reduction of aspen range at the landscape level. Increasing fire activity may favor aspen increase at its upper elevation limits adjacent to coniferous forest, but may also favor reduction of aspen at lower elevation limits adjacent to xeric shrubland. Conclusions Our study highlights the importance of incorporating fine-scale terrain effects on climatic water deficit and ecohydrology when modeling species distribution response to climate change. This modeling study suggests that climate mitigation and adaptation strategies that use fire would benefit from consideration of spatial context at landscape scales.

  2. Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

    NASA Astrophysics Data System (ADS)

    Kim, J. B.; Kerns, B. K.; Halofsky, J.

    2014-12-01

    GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest point demonstrates the importance of using model out as a forum for discussion along with other information, rather than using model output in an inappropriately predictive sense. These lessons are being applied currently to other national forests in the Pacific Northwest to contribute in vulnerability assessments.

  3. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    NASA Astrophysics Data System (ADS)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2018-06-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  4. Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

    NASA Astrophysics Data System (ADS)

    Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

    2017-09-01

    High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

  5. How Hot was Africa during the Mid-Holocene? Reexamining Africa's Thermal History via integrated Climate and Proxy System Modeling

    NASA Astrophysics Data System (ADS)

    Dee, S.; Russell, J. M.; Morrill, C.

    2017-12-01

    Climate models predict Africa will warm by up to 5°C in the coming century. Reconstructions of African temperature since the Last Glacial Maximum (LGM) have made fundamental contributions to our understanding of past, present, and future climate and can help constrain predictions from general circulation models (GCMs). However, many of these reconstructions are based on proxies of lake temperature, so the confounding influences of lacustrine processes may complicate our interpretations of past changes in tropical climate. These proxy-specific uncertainties require robust methodology for data-model comparison. We develop a new proxy system model (PSM) for paleolimnology to facilitate data-model comparison and to fully characterize uncertainties in climate reconstructions. Output from GCMs are used to force the PSM to simulate lake temperature, hydrology, and associated proxy uncertainties. We compare reconstructed East African lake and air temperatures in individual records and in a stack of 9 lake records to those predicted by our PSM forced with Paleoclimate Model Intercomparison Project (PMIP3) simulations, focusing on the mid-Holocene (6 kyr BP). We additionally employ single-forcing transient climate simulations from TraCE (10 kyr to 4 kyr B.P. and historical), as well as 200-yr time slice simulations from CESM1.0 to run the lake PSM. We test the sensitivity of African climate change during the mid-Holocene to orbital, greenhouse gas, and ice-sheet forcing in single-forcing simulations, and investigate dynamical hypotheses for these changes. Reconstructions of tropical African temperature indicate 1-2ºC warming during the mid-Holocene relative to the present, similar to changes predicted in the coming decades. However, most climate models underestimate the warming observed in these paleoclimate data (Fig. 1, 6kyr B.P.). We investigate this discrepancy using the new lake PSM and climate model simulations, with attention to the (potentially non-stationary) relationship between lake surface temperature and air temperature. The data-model comparison helps partition the impacts of lake-specific processes such as energy balance, mixing, sedimentation and bioturbation. We provide new insight into the patterns, amplitudes, sensitivity, and mechanisms of African temperature change.

  6. The sensitivity of the Arctic sea ice to orbitally induced insolation changes: a study of the mid-Holocene Paleoclimate Modelling Intercomparison Project 2 and 3 simulations

    NASA Astrophysics Data System (ADS)

    Berger, M.; Brandefelt, J.; Nilsson, J.

    2013-04-01

    In the present work the Arctic sea ice in the mid-Holocene and the pre-industrial climates are analysed and compared on the basis of climate-model results from the Paleoclimate Modelling Intercomparison Project phase 2 (PMIP2) and phase 3 (PMIP3). The PMIP3 models generally simulate smaller and thinner sea-ice extents than the PMIP2 models both for the pre-industrial and the mid-Holocene climate. Further, the PMIP2 and PMIP3 models all simulate a smaller and thinner Arctic summer sea-ice cover in the mid-Holocene than in the pre-industrial control climate. The PMIP3 models also simulate thinner winter sea ice than the PMIP2 models. The winter sea-ice extent response, i.e. the difference between the mid-Holocene and the pre-industrial climate, varies among both PMIP2 and PMIP3 models. Approximately one half of the models simulate a decrease in winter sea-ice extent and one half simulates an increase. The model-mean summer sea-ice extent is 11 % (21 %) smaller in the mid-Holocene than in the pre-industrial climate simulations in the PMIP2 (PMIP3). In accordance with the simple model of Thorndike (1992), the sea-ice thickness response to the insolation change from the pre-industrial to the mid-Holocene is stronger in models with thicker ice in the pre-industrial climate simulation. Further, the analyses show that climate models for which the Arctic sea-ice responses to increasing atmospheric CO2 concentrations are similar may simulate rather different sea-ice responses to the change in solar forcing between the mid-Holocene and the pre-industrial. For two specific models, which are analysed in detail, this difference is found to be associated with differences in the simulated cloud fractions in the summer Arctic; in the model with a larger cloud fraction the effect of insolation change is muted. A sub-set of the mid-Holocene simulations in the PMIP ensemble exhibit open water off the north-eastern coast of Greenland in summer, which can provide a fetch for surface waves. This is in broad agreement with recent analyses of sea-ice proxies, indicating that beach-ridges formed on the north-eastern coast of Greenland during the early- to mid-Holocene.

  7. Predicting Impacts of Climate Change on the Aboveground Carbon Sequestration Rate of a Temperate Forest in Northeastern China

    PubMed Central

    Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

    2014-01-01

    The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species. PMID:24763409

  8. Predicting impacts of climate change on the aboveground carbon sequestration rate of a temperate forest in northeastern China.

    PubMed

    Ma, Jun; Hu, Yuanman; Bu, Rencang; Chang, Yu; Deng, Huawei; Qin, Qin

    2014-01-01

    The aboveground carbon sequestration rate (ACSR) reflects the influence of climate change on forest dynamics. To reveal the long-term effects of climate change on forest succession and carbon sequestration, a forest landscape succession and disturbance model (LANDIS Pro7.0) was used to simulate the ACSR of a temperate forest at the community and species levels in northeastern China based on both current and predicted climatic data. On the community level, the ACSR of mixed Korean pine hardwood forests and mixed larch hardwood forests, fluctuated during the entire simulation, while a large decline of ACSR emerged in interim of simulation in spruce-fir forest and aspen-white birch forests, respectively. On the species level, the ACSR of all conifers declined greatly around 2070s except for Korean pine. The ACSR of dominant hardwoods in the Lesser Khingan Mountains area, such as Manchurian ash, Amur cork, black elm, and ribbed birch fluctuated with broad ranges, respectively. Pioneer species experienced a sharp decline around 2080s, and they would finally disappear in the simulation. The differences of the ACSR among various climates were mainly identified in mixed Korean pine hardwood forests, in all conifers, and in a few hardwoods in the last quarter of simulation. These results indicate that climate warming can influence the ACSR in the Lesser Khingan Mountains area, and the largest impact commonly emerged in the A2 scenario. The ACSR of coniferous species experienced higher impact by climate change than that of deciduous species.

  9. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies

    NASA Technical Reports Server (NTRS)

    Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.; hide

    2012-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.

  10. Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

    USGS Publications Warehouse

    Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

    2017-01-01

    In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

  11. WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

    NASA Astrophysics Data System (ADS)

    Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

    2014-05-01

    Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are accompanied by the WASCAL Graduate Research Program on the West African Climate System. The GRP-WACS provides ten scholarships per year for West African PhD students with a duration of three years. Present and future WASCAL PhD students will constitute one important user group of the Linux cluster that will be installed at the Competence Center in Ouagadougou, Burkina Faso. Regional Land-Atmosphere Simulations A key research activity of the WASCAL Core Research Program is the analysis of interactions between the land surface and the atmosphere to investigate how land surface changes affect hydro-meteorological surface fluxes such as evapotranspiration. Since current land surface models of global and regional climate models neglect dominant lateral hydrological processes such as surface runoff, a novel land surface model is used, the NCAR Distributed Hydrological Modeling System (NDHMS). This model can be coupled to WRF (WRF-Hydro) to perform two-way coupled atmospheric-hydrological simulations for the watershed of interest. Hardware and network prerequisites include a HPC cluster, network switches, internal storage media, Internet connectivity of sufficient bandwidth. Competences needed are HPC, storage, and visualization systems optimized for climate research, parallelization and optimization of climate models and workflows, efficient management of highest data volumes.

  12. Biomes computed from simulated climatologies

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

    Claussen, M.; Esch, M.

    1994-01-01

    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

  13. Climate change and biofuel wheat: A case study of Southern Saskatchewan

    USDA-ARS?s Scientific Manuscript database

    This study assessed potential impacts of climate change on wheat production as a biofuel crop in southern Saskatchewan, Canada. The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) was used to simulate biomass and grain yield under three climate change scenarios ...

  14. Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, Canada

    NASA Astrophysics Data System (ADS)

    Paradis, Daniel; Vigneault, Harold; Lefebvre, René; Savard, Martine M.; Ballard, Jean-Marc; Qian, Budong

    2016-03-01

    Nitrate (N-NO3) concentration in groundwater, the sole source of potable water in Prince Edward Island (PEI, Canada), currently exceeds the 10 mg L-1 (N-NO3) health threshold for drinking water in 6 % of domestic wells. Increasing climatic and socio-economic pressures on PEI agriculture may further deteriorate groundwater quality. This study assesses how groundwater nitrate concentration could evolve due to the forecasted climate change and its related potential changes in agricultural practices. For this purpose, a tridimensional numerical groundwater flow and mass transport model was developed for the aquifer system of the entire Island (5660 km2). A number of different groundwater flow and mass transport simulations were made to evaluate the potential impact of the projected climate change and agricultural adaptation. According to the simulations for year 2050, N-NO3 concentration would increase due to two main causes: (1) the progressive attainment of steady-state conditions related to present-day nitrogen loadings, and (2) the increase in nitrogen loadings due to changes in agricultural practices provoked by future climatic conditions. The combined effects of equilibration with loadings, climate and agricultural adaptation would lead to a 25 to 32 % increase in N-NO3 concentration over the Island aquifer system. The change in groundwater recharge regime induced by climate change (with current agricultural practices) would only contribute 0 to 6 % of that increase for the various climate scenarios. Moreover, simulated trends in groundwater N-NO3 concentration suggest that an increased number of domestic wells (more than doubling) would exceed the nitrate drinking water criteria. This study underlines the need to develop and apply better agricultural management practices to ensure sustainability of long-term groundwater resources. The simulations also show that observable benefits from positive changes in agricultural practices would be delayed in time due to the slow dynamics of nitrate transport within the aquifer system.

  15. GCM simulations of volcanic aerosol forcing. I - Climate changes induced by steady-state perturbations

    NASA Technical Reports Server (NTRS)

    Pollack, James B.; Rind, David; Lacis, Andrew; Hansen, James E.; Sato, Makiko; Ruedy, Reto

    1993-01-01

    The response of the climate system to a temporally and spatially constant amount of volcanic particles is simulated using a general circulation model (GCM). The optical depth of the aerosols is chosen so as to produce approximately the same amount of forcing as results from doubling the present CO2 content of the atmosphere and from the boundary conditions associated with the peak of the last ice age. The climate changes produced by long-term volcanic aerosol forcing are obtained by differencing this simulation and one made for the present climate with no volcanic aerosol forcing. The simulations indicate that a significant cooling of the troposphere and surface can occur at times of closely spaced multiple sulfur-rich volcanic explosions that span time scales of decades to centuries. The steady-state climate response to volcanic forcing includes a large expansion of sea ice, especially in the Southern Hemisphere; a resultant large increase in surface and planetary albedo at high latitudes; and sizable changes in the annually and zonally averaged air temperature.

  16. High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

    NASA Astrophysics Data System (ADS)

    Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

    2015-04-01

    Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

  17. Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

    NASA Astrophysics Data System (ADS)

    Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

    2013-04-01

    The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc. Nonetheless, according to the results of this work future ozone is conditioned by the dependence of biogenic emissions on the climatological patterns of variability. In this sense, ozone over Europe is mainly driven by the warming-induced increase in biogenic emitting activity (vegetation is kept invariable in the simulations, but estimations of these emissions strongly depends on shortwave radiation and temperature, which are substantially modified in climatic simulations). Moreover, one of the most important drivers for ozone increase is the decrease of cloudiness (related to stronger solar radiation) mostly over southern Europe at the first half of the XXI century. However, given the large uncertainty isoprene sensitivity to climate change and the large uncertainties associated to the cloudiness projections, these results should be carefully considered.

  18. [Simulating the effects of climate change and fire disturbance on aboveground biomass of boreal forests in the Great Xing'an Mountains, Northeast China].

    PubMed

    Luo, Xu; Wang, Yu Li; Zhang, Jin Quan

    2018-03-01

    Predicting the effects of climate warming and fire disturbance on forest aboveground biomass is a central task of studies in terrestrial ecosystem carbon cycle. The alteration of temperature, precipitation, and disturbance regimes induced by climate warming will affect the carbon dynamics of forest ecosystem. Boreal forest is an important forest type in China, the responses of which to climate warming and fire disturbance are increasingly obvious. In this study, we used a forest landscape model LANDIS PRO to simulate the effects of climate change on aboveground biomass of boreal forests in the Great Xing'an Mountains, and compared direct effects of climate warming and the effects of climate warming-induced fires on forest aboveground biomass. The results showed that the aboveground biomass in this area increased under climate warming scenarios and fire disturbance scenarios with increased intensity. Under the current climate and fire regime scenario, the aboveground biomass in this area was (97.14±5.78) t·hm -2 , and the value would increase up to (97.93±5.83) t·hm -2 under the B1F2 scenario. Under the A2F3 scenario, aboveground biomass at landscape scale was relatively higher at the simulated periods of year 100-150 and year 150-200, and the value were (100.02±3.76) t·hm -2 and (110.56±4.08) t·hm -2 , respectively. Compared to the current fire regime scenario, the predicted biomass at landscape scale was increased by (0.56±1.45) t·hm -2 under the CF2 scenario (fire intensity increased by 30%) at some simulated periods, and the aboveground biomass was reduced by (7.39±1.79) t·hm -2 in CF3 scenario (fire intensity increased by 230%) at the entire simulation period. There were significantly different responses between coniferous and broadleaved species under future climate warming scenarios, in that the simulated biomass for both Larix gmelinii and Betula platyphylla showed decreasing trend with climate change, whereas the simulated biomass for Pinus sylvestris var. mongolica, Picea koraiensis and Populus davidiana showed increasing trend at different degrees during the entire simulation period. There was a time lag for the direct effect of climate warming on biomass for coniferous and broadleaved species. The response time of coniferous species to climate warming was 25-30 years, which was longer than that for broadleaf species. The forest landscape in the Great Xing'an Mountains was sensitive to the interactive effect of climate warming (high CO 2 emissions) and high intensity fire disturbance. Future climate warming and high intensity forest fire disturbance would significantly change the composition and structure of forest ecosystem.

  19. How will climate change affect watershed mercury export in a representative Coastal Plain watershed?

    NASA Astrophysics Data System (ADS)

    Golden, H. E.; Knightes, C. D.; Conrads, P. A.; Feaster, T.; Davis, G. M.; Benedict, S. T.; Bradley, P. M.

    2012-12-01

    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.

  20. Tailored scenarios for streamflow climate change impacts based on the perturbation of precipitation and evapotranspiration

    NASA Astrophysics Data System (ADS)

    Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel

    2015-04-01

    It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.

  1. Simulating climate change with interactive stratospheric ozone

    NASA Astrophysics Data System (ADS)

    Lin, P.; Ming, Y.

    2017-12-01

    We compare the simulated climate changes with and without interactive ozone in GFDL AM4. We also compare the simulations with a fully interactive stratospheric chemistry scheme versus those with a simplified scheme in which ozone is treated as a passive tracer. Despite its simplicity, the ozone tracer is sufficient to represent the ozone changes in response to changes in the stratospheric circulation as well as the zonally asymmetric distribution of ozone concentration. With interactive ozone, the model simulates a stronger cooling in the tropical lower stratosphere and less stratospheric moistening in response to surface warming. We further investigate how the different stratospheric response translate into different responses in the tropospheric circulations.

  2. Uncertain soil moisture feedbacks in model projections of Sahel precipitation

    NASA Astrophysics Data System (ADS)

    Berg, Alexis; Lintner, Benjamin R.; Findell, Kirsten; Giannini, Alessandra

    2017-06-01

    Given the uncertainties in climate model projections of Sahel precipitation, at the northern edge of the West African Monsoon, understanding the factors governing projected precipitation changes in this semiarid region is crucial. This study investigates how long-term soil moisture changes projected under climate change may feedback on projected changes of Sahel rainfall, using simulations with and without soil moisture change from five climate models participating in the Global Land Atmosphere Coupling Experiment-Coupled Model Intercomparison Project phase 5 experiment. In four out of five models analyzed, soil moisture feedbacks significantly influence the projected West African precipitation response to warming; however, the sign of these feedbacks differs across the models. These results demonstrate that reducing uncertainties across model projections of the West African Monsoon requires, among other factors, improved mechanistic understanding and constraint of simulated land-atmosphere feedbacks, even at the large spatial scales considered here.Plain Language SummaryClimate model projections of Sahel rainfall remain notoriously uncertain; understanding the physical processes responsible for this uncertainty is thus crucial. Our study focuses on analyzing the feedbacks of soil moisture changes on model projections of the West African Monsoon under global warming. Soil moisture-atmosphere interactions have been shown in prior studies to play an important role in this region, but the potential feedbacks of long-term soil moisture changes on projected precipitation changes have not been investigated specifically. To isolate these feedbacks, we use targeted simulations from five climate models, with and without soil moisture change. Importantly, we find that climate models exhibit soil moisture-precipitation feedbacks of different sign in this region: in some models soil moisture changes amplify precipitation changes (positive feedback), in others they dampen them (negative feedback). The impact of those feedbacks is in some cases of comparable amplitude to the projected precipitation changes themselves. In other words, we show, over a subset of climate models, how land-atmosphere interactions may be a cause of uncertainty in model projections of precipitation; we emphasize the need to evaluate these processes carefully in current and next-generation climate model simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JHyd..412....3L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JHyd..412....3L"><span>Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale 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>Li, Qiaoling; Ishidaira, Hiroshi</p> <p>2012-01-01</p> <p>SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH potentially provides a powerful tool for simulating vegetation response to climate changes in the biosphere hydrological cycle.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3119/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3119/"><span>Watershed scale response to climate change--Trout Lake Basin, Wisconsin</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>Walker, John F.; Hunt, Randall J.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Trout River Basin at Trout Lake in northern Wisconsin.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3127/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3127/"><span>Watershed scale response to climate change--Clear Creek Basin, Iowa</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>Christiansen, Daniel E.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Clear Creek Basin, near Coralville, Iowa.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3125/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3125/"><span>Watershed scale response to climate change--Feather River Basin, California</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>Koczot, Kathryn M.; Markstrom, Steven L.; Hay, Lauren E.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Feather River Basin, California.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3124/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3124/"><span>Watershed scale response to climate change--South Fork Flathead River Basin, Montana</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>Chase, Katherine J.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the South Fork Flathead River Basin, Montana.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3128/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3128/"><span>Watershed scale response to climate change--Cathance Stream Basin, Maine</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>Dudley, Robert W.; Hay, Lauren E.; Markstrom, Steven L.; Hodgkins, Glenn A.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Cathance Stream Basin, Maine.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3122/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3122/"><span>Watershed scale response to climate change--Pomperaug River Watershed, Connecticut</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>Bjerklie, David M.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Pomperaug River Basin at Southbury, Connecticut.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3118/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3118/"><span>Watershed scale response to climate change--Starkweather Coulee Basin, North Dakota</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>Vining, Kevin C.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Starkweather Coulee Basin near Webster, North Dakota.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3121/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3121/"><span>Watershed scale response to climate change--Sagehen Creek Basin, California</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.; Hay, Lauren E.; Regan, R. Steven</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Sagehen Creek Basin near Truckee, California.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3120/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3120/"><span>Watershed scale response to climate change--Sprague River Basin, Oregon</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>Risley, John; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Sprague River Basin near Chiloquin, Oregon.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3129/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3129/"><span>Watershed scale response to climate change--Black Earth Creek Basin, Wisconsin</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>Hunt, Randall J.; Walker, John F.; Westenbroek, Steven M.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Black Earth Creek Basin, Wisconsin.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3126/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3126/"><span>Watershed scale response to climate change--East River Basin, Colorado</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>Battaglin, William A.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the East River Basin, Colorado.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3123/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3123/"><span>Watershed scale response to climate change--Naches River Basin, Washington</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>Mastin, Mark C.; Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Naches River Basin below Tieton River in Washington.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/fs/2011/3116/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/fs/2011/3116/"><span>Watershed scale response to climate change--Flint River Basin, Georgia</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>Hay, Lauren E.; Markstrom, Steven L.</p> <p>2012-01-01</p> <p>Fourteen basins for which the Precipitation Runoff Modeling System has been calibrated and evaluated were selected as study sites. Precipitation Runoff Modeling System is a deterministic, distributed parameter watershed model developed to evaluate the effects of various combinations of precipitation, temperature, and land use on streamflow and general basin hydrology. Output from five General Circulation Model simulations and four emission scenarios were used to develop an ensemble of climate-change scenarios for each basin. These ensembles were simulated with the corresponding Precipitation Runoff Modeling System model. This fact sheet summarizes the hydrologic effect and sensitivity of the Precipitation Runoff Modeling System simulations to climate change for the Flint River Basin at Montezuma, Georgia.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=148843&keyword=india&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=148843&keyword=india&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>SIMULATING REGIONAL-SCALE AIR QUALITY WITH DYNAMIC CHANGES IN REGIONAL CLIMATE AND CHEMICAL BOUNDARY CONDITIONS</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>This poster compares air quality modeling simulations under current climate and a future (approximately 2050) climate scenario. Differences in predicted ozone episodes and daily average PM<SUB>2.5</SUB> concentrations are presented, along with vertical ozone profiles. Modeling ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160007389','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160007389"><span>"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation</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>Taylor, Patrick C.; Baker, Noel C.</p> <p>2015-01-01</p> <p>Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27976449','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27976449"><span>Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands.</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>Tietjen, Britta; Schlaepfer, Daniel R; Bradford, John B; Lauenroth, William K; Hall, Sonia A; Duniway, Michael C; Hochstrasser, Tamara; Jia, Gensuo; Munson, Seth M; Pyke, David A; Wilson, Scott D</p> <p>2017-07-01</p> <p>Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change-induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems. © 2017 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70182226','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70182226"><span>Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands</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>Tietjen, Britta; Schlaepfer, Daniel R.; Bradford, John B.; Laurenroth, William K.; Hall, Sonia A.; Duniway, Michael C.; Hochstrasser, Tamara; Jia, Gensuo; Munson, Seth M.; Pyke, David A.; Wilson, Scott D.</p> <p>2017-01-01</p> <p>Drylands occur world-wide and are particularly vulnerable to climate change since dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability, and also change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding.We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation.Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, i.e. leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems.</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('http://adsabs.harvard.edu/abs/2017HESS...21..183Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017HESS...21..183Y"><span>Effects of land use/land cover and climate changes on surface runoff in a semi-humid and semi-arid transition zone in northwest 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>Yin, Jing; He, Fan; Jiu Xiong, Yu; Qiu, Guo Yu</p> <p>2017-01-01</p> <p>Water resources, which are considerably affected by land use/land cover (LULC) and climate changes, are a key limiting factor in highly vulnerable ecosystems in arid and semi-arid regions. The impacts of LULC and climate changes on water resources must be assessed in these areas. However, conflicting results regarding the effects of LULC and climate changes on runoff have been reported in relatively large basins, such as the Jinghe River basin (JRB), which is a typical catchment (> 45 000 km2) located in a semi-humid and arid transition zone on the central Loess Plateau, northwest China. In this study, we focused on quantifying both the combined and isolated impacts of LULC and climate changes on surface runoff. We hypothesized that under climatic warming and drying conditions, LULC changes, which are primarily caused by intensive human activities such as the Grain for Green Program, will considerably alter runoff in the JRB. The Soil and Water Assessment Tool (SWAT) was adopted to perform simulations. The simulated results indicated that although runoff increased very little between the 1970s and the 2000s due to the combined effects of LULC and climate changes, LULC and climate changes affected surface runoff differently in each decade, e.g., runoff increased with increased precipitation between the 1970s and the 1980s (precipitation contributed to 88 % of the runoff increase). Thereafter, runoff decreased and was increasingly influenced by LULC changes, which contributed to 44 % of the runoff changes between the 1980s and 1990s and 71 % of the runoff changes between the 1990s and 2000s. Our findings revealed that large-scale LULC under the Grain for Green Program has had an important effect on the hydrological cycle since the late 1990s. Additionally, the conflicting findings regarding the effects of LULC and climate changes on runoff in relatively large basins are likely caused by uncertainties in hydrological simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC31D..05M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC31D..05M"><span>Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural 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>MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.</p> <p>2013-12-01</p> <p>Representative Agricultural Pathways (RAPs) are projections of plausible future biophysical and socio-economic conditions used to carry out climate impact assessments for agriculture. The development of RAPs iss motivated by the fact that the various global and regional models used for agricultural climate change impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation or public availability. These practices have hampered attempts at model inter-comparison, improvement, and synthesis of model results across studies. This paper aims to (1) present RAPs developed for the principal wheat-producing region of the Pacific Northwest, and to (2) combine these RAPs with downscaled climate data, crop model simulations and economic model simulations to assess climate change impacts on winter wheat production and farm income. This research was carried out as part of a project funded by the USDA known as the Regional Approaches to Climate Change in the Pacific Northwest (REACCH). The REACCH study region encompasses the major winter wheat production area in Pacific Northwest and preliminary research shows that farmers producing winter wheat could benefit from future climate change. However, the future world is uncertain in many dimensions, including commodity and input prices, production technology, and policies, as well as increased probability of disturbances (pests and diseases) associated with a changing climate. Many of these factors cannot be modeled, so they are represented in the regional RAPS. The regional RAPS are linked to global agricultural and shared social-economic pathways, and used along with climate change projections to simulate future outcomes for the wheat-based farms in the REACCH region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=state+AND+climate&pg=5&id=EJ1045667','ERIC'); return false;" href="https://eric.ed.gov/?q=state+AND+climate&pg=5&id=EJ1045667"><span>Simulating Global Climate Summits</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>Vesperman, Dean P.; Haste, Turtle; Alrivy, Stéphane</p> <p>2014-01-01</p> <p>One of the most persistent and controversial issues facing the global community is climate change. With the creation of the UN Framework Convention on Climate Change (UNFCCC) in 1992 and the Kyoto Protocol (1997), the global community established some common ground on how to address this issue. However, the last several climate summits have failed…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.B43D0269L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.B43D0269L"><span>Modeling Forest Composition and Carbon Dynamics Under Projected Climate-Fire Interactions in the Sierra Nevada, California</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>Liang, S.; Hurteau, M. D.; Westerling, A. L.</p> <p>2014-12-01</p> <p>The Sierra Nevada Mountains are occupied by a diversity of forest types that sort by elevation. The interaction of changing climate and altered disturbance regimes (e.g. fire) has the potential to drive changes in forest distribution as a function of species-specific response. Quantifying the effects of these drivers on species distributions and productivity under future climate-fire interactions is necessary for informing mitigation and adaptation efforts. In this study, we assimilated forest inventory and soil survey data and species life history traits into a landscape model, LANDIS-II, to quantify the response of forest dynamics to the interaction of climate change and large wildfire frequency in the Sierra Nevada. We ran 100-year simulations forced with historical climate and climate projections from three models (GFDL, CNRM and CCSM3) driven by the A2 emission scenario. We found that non-growing season NPP is greatly enhanced by 15%-150%, depending on the specific climate projection. The greatest increase occurs in subalpine forests. Species-specific response varied as a function of life history characteristics. The distribution of drought and fire-tolerant species, such as ponderosa pine, expanded by 7.3-9.6% from initial conditions, while drought and fire-intolerant species, such as white fir, showed little change in the absence of fire. Changes in wildfire size and frequency influence species distributions by altering the successional stage of burned patches. The range of responses to different climate models demonstrates the sensitivity of these forests to climate variability. The scale of climate projections relative to the scale of forest simulations presents a source of uncertainty, particularly at the ecotone between forest types and for identifying topographically mediated climate refugia. Improving simulations will likely require higher resolution climate projections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21737120','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21737120"><span>Effects of climate change on the wash-off of volatile organic compounds from urban roads.</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>Mahbub, Parvez; Goonetilleke, Ashantha; Ayoko, Godwin A; Egodawatta, Prasanna</p> <p>2011-09-01</p> <p>The predicted changes in rainfall characteristics due to climate change could adversely affect stormwater quality in highly urbanised coastal areas throughout the world. This in turn will exert a significant influence on the discharge of pollutants to estuarine and marine waters. Hence, an in-depth analysis of the effects of such changes on the wash-off of volatile organic compounds (VOCs) from urban roads in the Gold Coast region in Australia was undertaken. The rainfall characteristics were simulated using a rainfall simulator. Principal Component Analysis (PCA) and Multicriteria Decision tools such as PROMETHEE and GAIA were employed to understand the VOC wash-off under climate change. It was found that low, low to moderate and high rain events due to climate change will affect the wash-off of toluene, ethylbenzene, meta-xylene, para-xylene and ortho-xylene from urban roads in Gold Coast. Total organic carbon (TOC) was identified as predominant carrier of toluene, meta-xylene and para-xylene in <1 μm to 150 μm fractions and for ethylbenzene in 150 μm to >300 μm fractions under such dominant rain events due to climate change. However, ortho-xylene did not show such affinity towards either TOC or TSS (total suspended solids) under the simulated climatic conditions. Copyright © 2011 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=264517&keyword=temperature+AND+variability&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=264517&keyword=temperature+AND+variability&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>Relative Sensitivity of Simulated Nitrogen Discharge to Projected Changes in Climate and Land Cover for Two Watersheds in North Carolina, USA</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>We investigated the effects of projected changes in land cover and climate (precipitation, temperature and atmospheric carbon dioxide [CO2] concentrations) on simulated nitrate (NO3) and organic nitrogen (ORGN) discharge for two watersheds within the Neuse River Basin, NC for yea...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=315500','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=315500"><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.ars.usda.gov/research/publications/find-a-publication/">USDA-ARS?s Scientific Manuscript database</a></p> <p></p> <p></p> <p>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...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26251975','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26251975"><span>Climate change and maize yield in southern Africa: what can farm management do?</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>Rurinda, Jairos; van Wijk, Mark T; Mapfumo, Paul; Descheemaeker, Katrien; Supit, Iwan; Giller, Ken E</p> <p>2015-12-01</p> <p>There is concern that food insecurity will increase in southern Africa due to climate change. We quantified the response of maize yield to projected climate change and to three key management options - planting date, fertilizer use and cultivar choice - using the crop simulation model, agricultural production systems simulator (APSIM), at two contrasting sites in Zimbabwe. Three climate periods up to 2100 were selected to cover both near- and long-term climates. Future climate data under two radiative forcing scenarios were generated from five global circulation models. The temperature is projected to increase significantly in Zimbabwe by 2100 with no significant change in mean annual total rainfall. When planting before mid-December with a high fertilizer rate, the simulated average grain yield for all three maize cultivars declined by 13% for the periods 2010-2039 and 2040-2069 and by 20% for 2070-2099 compared with the baseline climate, under low radiative forcing. Larger declines in yield of up to 32% were predicted for 2070-2099 with high radiative forcing. Despite differences in annual rainfall, similar trends in yield changes were observed for the two sites studied, Hwedza and Makoni. The yield response to delay in planting was nonlinear. Fertilizer increased yield significantly under both baseline and future climates. The response of maize to mineral nitrogen decreased with progressing climate change, implying a decrease in the optimal fertilizer rate in the future. Our results suggest that in the near future, improved crop and soil fertility management will remain important for enhanced maize yield. Towards the end of the 21st century, however, none of the farm management options tested in the study can avoid large yield losses in southern Africa due to climate change. There is a need to transform the current cropping systems of southern Africa to offset the negative impacts of climate change. © 2015 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H32E..01E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H32E..01E"><span>Assessment of the Impact of Climate Change on the Water Balances and Flooding Conditions of Peninsular Malaysia watersheds by a Coupled Numerical Climate Model - Watershed Hydrology 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>Ercan, A.; Kavvas, M. L.; Ishida, K.; Chen, Z. Q.; Amin, M. Z. M.; Shaaban, A. J.</p> <p>2017-12-01</p> <p>Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over various watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model that utilized an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century were dynamically downscaled to 6 km resolution over Peninsular Malaysia by a regional numerical climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over the selected watersheds of Peninsular Malaysia. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions at the selected watersheds during the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90 years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant at the selected watersheds. Furthermore, the flood frequency analyses for the selected watersheds indicate an overall increasing trend in the second half of the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25826311','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25826311"><span>Modelling recent and future climatic suitability for fasciolosis 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>Caminade, Cyril; van Dijk, Jan; Baylis, Matthew; Williams, Diana</p> <p>2015-03-19</p> <p>Fasciola hepatica is a parasitic worm responsible for fasciolosis in grazed ruminants in Europe. The free-living stages of this parasite are sensitive to temperature and soil moisture, as are the intermediate snail hosts the parasite depends on for its life-cycle. We used a climate-driven disease model in order to assess the impact of recent and potential future climate changes on the incidence of fasciolosis and to estimate the related uncertainties at the scale of the European landmass. The current climate appears to be highly suitable for fasciolosis throughout the European Union with the exception of some parts of the Mediterranean region. Simulated climatic suitability for fasciolosis significantly increased during the 2000s in central and northwestern Europe, which is consistent with an observed increased in ruminant infections. The simulation showed that recent trends are likely to continue in the future with the estimated pattern of climate change for northern Europe, possibly extending the season suitable for development of the parasite in the environment by up to four months. For southern Europe, the simulated burden of disease may be lower, but the projected climate change will increase the risk during the winter months, since the simulated changes in temperature and moisture support the development of the free-living and intra-molluscan stages between November and March. In the event of predicted climate change, F. hepatica will present a serious risk to the health, welfare and productivity of all ruminant livestock. Improved, bespoke control programmes, both at farm and region levels, will then become imperative if problems, such as resistance of the parasite associated with increased drug use, are to be mitigated.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AGUFM.A61C0088K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AGUFM.A61C0088K"><span>Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator</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>Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.</p> <p>2002-12-01</p> <p>The fastest supercomputer of the world, the Earth Simulator (total peak performance 40TFLOPS) has recently been available for climate researches in Yokohama, Japan. We are planning to conduct a series of future climate change projection experiments on the Earth Simulator with a high-resolution coupled ocean-atmosphere climate model. The main scientific aims for the experiments are to investigate 1) the change in global ocean circulation with an eddy-permitting ocean model, 2) the regional details of the climate change including Asian monsoon rainfall pattern, tropical cyclones and so on, and 3) the change in natural climate variability with a high-resolution model of the coupled ocean-atmosphere system. To meet these aims, an atmospheric GCM, CCSR/NIES AGCM, with T106(~1.1o) horizontal resolution and 56 vertical layers is to be coupled with an oceanic GCM, COCO, with ~ 0.28ox 0.19o horizontal resolution and 48 vertical layers. This coupled ocean-atmosphere climate model, named MIROC, also includes a land-surface model, a dynamic-thermodynamic seaice model, and a river routing model. The poles of the oceanic model grid system are rotated from the geographic poles so that they are placed in Greenland and Antarctic land masses to avoild the singularity of the grid system. Each of the atmospheric and the oceanic parts of the model is parallelized with the Message Passing Interface (MPI) technique. The coupling of the two is to be done with a Multi Program Multi Data (MPMD) fashion. A 100-model-year integration will be possible in one actual month with 720 vector processors (which is only 14% of the full resources of the Earth Simulator).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A54A..07S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A54A..07S"><span>The impact of past and future climate change on global human mortality due to ozone and PM2.5 outdoor air pollution</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>Silva, R.; West, J.; Anenberg, S.; Lamarque, J.; Shindell, D. T.; Bergmann, D. J.; Berntsen, T.; Cameron-Smith, P. J.; Collins, B.; Ghan, S. J.; Josse, B.; Nagashima, T.; Naik, V.; Plummer, D.; Rodriguez, J. M.; Szopa, S.; Zeng, G.</p> <p>2012-12-01</p> <p>Climate change can adversely affect air quality, through changes in meteorology, atmospheric chemistry, and emissions. Future changes in air pollutant emissions will also profoundly influence air quality. These changes in air quality can affect human health, as exposure to ground-level ozone and fine particulate matter (PM2.5) has been associated with premature human mortality. Here we will quantify the global mortality impacts of past and future climate change, considering the effects of climate change on air quality isolated from emission changes. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has simulated the past and future surface concentrations of ozone and PM2.5 from each of several GCMs, for emissions from 1850 ("preindustrial") to 2000 ("present-day"), and for the IPCC AR5 Representative Concentration Pathways (RCPs) scenarios to 2100. We will use ozone and PM2.5 concentrations from simulations from five or more global models of atmospheric dynamics and chemistry, for a base year (present-day), pre-industrial conditions, and future scenarios, considering changes in climate and emissions. We will assess the mortality impacts of past climate change by using one simulation ensemble with present emissions and climate and one with present emissions but 1850 climate. We will similarly quantify the potential impacts of future climate change under the four RCP scenarios in 2030, 2050 and 2100. All model outputs will be regridded to the same resolution to estimate multi-model medians and range in each grid cell. Resulting premature deaths will be calculated using these medians along with epidemiologically-derived concentration-response functions, and present-day or future projections of population and baseline mortality rates, considering aging and transitioning disease rates over time. The spatial distributions of current and future global premature mortalities due to ozone and PM2.5 outdoor air pollution will be presented separately. These results will strengthen our understanding of the impacts of climate change today, and in future years considering different plausible scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159714','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159714"><span>Climate change impacts on the temperature and magnitude of groundwater discharge from shallow, unconfined aquifers</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>Kurylyk, Barret L.; MacQuarrie, Kerry T.B; Voss, Clifford I.</p> <p>2014-01-01</p> <p>Cold groundwater discharge to streams and rivers can provide critical thermal refuge for threatened salmonids and other aquatic species during warm summer periods. Climate change may influence groundwater temperature and flow rates, which may in turn impact riverine ecosystems. This study evaluates the potential impact of climate change on the timing, magnitude, and temperature of groundwater discharge from small, unconfined aquifers that undergo seasonal freezing and thawing. Seven downscaled climate scenarios for 2046–2065 were utilized to drive surficial water and energy balance models (HELP3 and ForHyM2) to obtain future projections for daily ground surface temperature and groundwater recharge. These future surface conditions were then applied as boundary conditions to drive subsurface simulations of variably saturated groundwater flow and energy transport. The subsurface simulations were performed with the U.S. Geological Survey finite element model SUTRA that was recently modified to include the dynamic freeze-thaw process. The SUTRA simulations indicate a potential rise in the magnitude (up to 34%) and temperature (up to 3.6°C) of groundwater discharge to the adjacent river during the summer months due to projected increases in air temperature and precipitation. The thermal response of groundwater to climate change is shown to be strongly dependent on the aquifer dimensions. Thus, the simulations demonstrate that the thermal sensitivity of aquifers and baseflow-dominated streams to decadal climate change may be more complex than previously thought. Furthermore, the results indicate that the probability of exceeding critical temperature thresholds within groundwater-sourced thermal refugia may significantly increase under the most extreme climate scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A53E2302N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A53E2302N"><span>On the role of ozone feedback in the ENSO amplitude response 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>Nowack, P. J.; Braesicke, P.; Abraham, N. L.; Pyle, J. A.</p> <p>2017-12-01</p> <p>The El Niño-Southern Oscillation (ENSO) in the tropical Pacific is of key importance to global climate and weather. However, climate models still disagree on the ENSO's response under climate change. Here we show that typical model representations of ozone can have a first-order impact on ENSO amplitude projections in climate sensitivity simulations (i.e. standard abrupt 4xCO2). We mainly explain this effect by the lapse rate adjustment of the tropical troposphere to ozone changes in the upper troposphere and lower stratosphere (UTLS) under 4xCO2. The ozone-induced lapse rate changes modify the Walker circulation response to the CO2 forcing and consequently tropical Pacific surface temperature gradients. Therefore, not including ozone feedbacks increases the number of extreme ENSO events in our model. In addition, we demonstrate that even if ozone changes in the tropical UTLS are included in the simulations, the neglect of the ozone response in the middle-upper stratosphere still leads to significantly larger ENSO amplitudes (compared to simulations run with a fully interactive atmospheric chemistry scheme). Climate modeling studies of the ENSO often neglect changes in ozone. Our results imply that this could affect the inter-model spread found in ENSO projections and, more generally, surface climate change simulations. We discuss the additional complexity in quantifying such ozone-related effects that arises from the apparent model dependency of chemistry-climate feedbacks and, possibly, their range of surface climate impacts. In conclusion, we highlight the need to understand better the coupling between ozone, the tropospheric circulation, and climate variability. Reference: Nowack PJ, Braesicke P, Abraham NL, and Pyle JA (2017), On the role of ozone feedback in the ENSO amplitude response under global warming, Geophys. Res. Lett. 44, 3858-3866, doi:10.1002/2016GL072418.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012EGUGA..14.3858D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012EGUGA..14.3858D"><span>A Simple Climate Model Program for High School Education</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>Dommenget, D.</p> <p>2012-04-01</p> <p>The future climate change projections of the IPCC AR4 are based on GCM simulations, which give a distinct global warming pattern, with an arctic winter amplification, an equilibrium land sea contrast and an inter-hemispheric warming gradient. While these simulations are the most important tool of the IPCC predictions, the conceptual understanding of these predicted structures of climate change are very difficult to reach if only based on these highly complex GCM simulations and they are not accessible for ordinary people. In this study presented here we will introduce a very simple gridded globally resolved energy balance model based on strongly simplified physical processes, which is capable of simulating the main characteristics of global warming. The model shall give a bridge between the 1-dimensional energy balance models and the fully coupled 4-dimensional complex GCMs. It runs on standard PC computers computing globally resolved climate simulation with 2yrs per second or 100,000yrs per day. The program can compute typical global warming scenarios in a few minutes on a standard PC. The computer code is only 730 line long with very simple formulations that high school students should be able to understand. The simple model's climate sensitivity and the spatial structure of the warming pattern is within the uncertainties of the IPCC AR4 models simulations. It is capable of simulating the arctic winter amplification, the equilibrium land sea contrast and the inter-hemispheric warming gradient with good agreement to the IPCC AR4 models in amplitude and structure. The program can be used to do sensitivity studies in which students can change something (e.g. reduce the solar radiation, take away the clouds or make snow black) and see how it effects the climate or the climate response to changes in greenhouse gases. This program is available for every one and could be the basis for high school education. Partners for a high school project are wanted!</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21516892','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21516892"><span>Effects of biotic feedback and harvest management on boreal forest fire activity 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>Krawchuk, Meg A; Cumming, Steve G</p> <p>2011-01-01</p> <p>Predictions of future fire activity over Canada's boreal forests have primarily been generated from climate data following assumptions that direct effects of weather will stand alone in contributing to changes in burning. However, this assumption needs explicit testing. First, areas recently burned can be less likely to burn again in the near term, and this endogenous regulation suggests the potential for self-limiting, negative biotic feedback to regional climate-driven increases in fire. Second, forest harvest is ongoing, and resulting changes in vegetation structure have been shown to affect fire activity. Consequently, we tested the assumption that fire activity will be driven by changes in fire weather without regulation by biotic feedback or regional harvest-driven changes in vegetation structure in the mixedwood boreal forest of Alberta, Canada, using a simulation experiment that includes the interaction of fire, stand dynamics, climate change, and clear cut harvest management. We found that climate change projected with fire weather indices calculated from the Canadian Regional Climate Model increased fire activity, as expected, and our simulations established evidence that the magnitude of regional increase in fire was sufficient to generate negative feedback to subsequent fire activity. We illustrate a 39% (1.39-fold) increase in fire initiation and 47% (1.47-fold) increase in area burned when climate and stand dynamics were included in simulations, yet 48% (1.48-fold) and 61% (1.61-fold) increases, respectively, when climate was considered alone. Thus, although biotic feedbacks reduced burned area estimates in important ways, they were secondary to the direct effect of climate on fire. We then show that ongoing harvest management in this region changed landscape composition in a way that led to reduced fire activity, even in the context of climate change. Although forest harvesting resulted in decreased regional fire activity when compared to unharvested conditions, forest composition and age structure was shifted substantially, illustrating a trade-off between management goals to minimize fire and conservation goals to emulate natural disturbance.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26217782','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26217782"><span>Hourly test reference weather data in the changing climate of Finland for building energy simulations.</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>Jylhä, Kirsti; Ruosteenoja, Kimmo; Jokisalo, Juha; Pilli-Sihvola, Karoliina; Kalamees, Targo; Mäkelä, Hanna; Hyvönen, Reijo; Drebs, Achim</p> <p>2015-09-01</p> <p>Dynamic building energy simulations need hourly weather data as input. The same high temporal resolution is required for assessments of future heating and cooling energy demand. The data presented in this article concern current typical values and estimated future changes in outdoor air temperature, wind speed, relative humidity and global, diffuse and normal solar radiation components. Simulated annual and seasonal delivered energy consumptions for heating of spaces, heating of ventilation supply air and cooling of spaces in the current and future climatic conditions are also presented for an example house, with district heating and a mechanical space cooling system. We provide details on how the synthetic future weather files were created and utilised as input data for dynamic building energy simulations by the IDA Indoor Climate and Energy program and also for calculations of heating and cooling degree-day sums. The information supplied here is related to the research article titled "Energy demand for the heating and cooling of residential houses in Finland in a changing climate" [1].</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010avh..confE..21P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010avh..confE..21P"><span>Groundwater recharge simulation under the steady-state and transient climate conditions</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>Pozdniakov, S.; Lykhina, N.</p> <p>2010-03-01</p> <p>Groundwater recharge simulation under the steady-state and transient climate conditions Diffusive groundwater recharge is a vertical water flux through the water table, i.e. through the boundary between the unsaturated and saturated zones. This flux features temporal and spatial changes due to variations in the climatic conditions, landscape the state of vegetation, and the spatial variability of vadoze zone characteristics. In a changing climate the non-steady state series of climatic characteristics will affect on the groundwater recharge.. A well-tested approach to calculating water flux through the vadoze zone is the application of Richard’s equations for a heterogeneous one-domain porosity continuum with specially formulated atmospheric boundary conditions at the ground surface. In this approach the climatic parameters are reflected in upper boundary conditions, while the recharge series is the flux through the low boundary. In this work developed by authors code Surfbal that simulates water cycle at surface of topsoil to take into account the various condition of precipitation transformation at the surface in different seasons under different vegetation cover including snow accumulation in winter and melting in spring is used to generate upper boundary condition at surface of topsoil for world-wide known Hydrus-1D code (Simunek et al, 2008). To estimate the proposal climate change effect we performed Surfbal and Hydrus simulation using the steady state climatic condition and transient condition due to global warming on example of Moscow region, Russia. The following scenario of climate change in 21 century in Moscow region was selected: the annual temperature will increase on 4C during 100 year and annual precipitation will increase on 10% (Solomon et al, 2007). Within the year the maximum increasing of temperature and precipitation falls on winter time, while in middle of summer temperature will remain almost the same as observed now and monthly precipitation. For simulating climate input the weather generator LARSWG (Semenov and Barrow 1997) was trained for generation daily meteorological records for both steady state and transient climatic conditions and two 100 year of meteorological series of minimum and maximum of air temperature, solar radiation and precipitation were generated. The numerical experiment for studying of transient climate on groundwater was performed for typical vadoze zone parameters of western part of Moscow Artesian basin. As the result, the 100 years series of recharge were simulated. Examination of stochastic properties of simulated time-series and comparative analysis series for the transient and for the steady state conditions shows the trend of increasing of recharge in this region in transient climate. Analysis of daily and monthly simulated water balance shows that this increasing is result of winter snow melting and winter infiltration into thaw topsoil. This work was supported by Russian Foundation for Basic Research via grant 08-05-00720a REFERENCES Semenov M.A and Barrow E.M., 1997. Use of a stochastic weather generator in the development of climate change scenarios. Climatic Change, 35:397-414 Šimůnek, J., M. Th. van Genuchten, and M. Šejna, 2008. Development and applications of the HYDRUS and STANMOD software packages, and related codes, Vadose Zone Journal, doi:10.2136/VZJ2007.0077, Special Issue "Vadose Zone Modeling", 7(2), 587-600. Solomon, S., D. Qin, M. Manning, Technical Summary. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H43L1800A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H43L1800A"><span>Climate Change Impacts on Sediment Transport In a Lowland Watershed System: Controlling Processes and Projection</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>al Aamery, N. M. H.; Mahoney, D. T.; Fox, J.</p> <p>2017-12-01</p> <p>Future climate change projections suggest extreme impacts on watershed hydrologic systems for some regions of the world including pronounced increases in surface runoff and instream flows. Yet, there remains a lack of research focused on how future changes in hydrologic extremes, as well as relative hydrologic mean changes, impact sediment redistribution within a watershed and sediment flux from a watershed. The authors hypothesized that variations in mean and extreme changes in turn may impact sediments in depositional and erosional dominance in a manner that may not be obvious to the watershed manager. Therefore, the objectives of this study were to investigate the inner processes connecting the combined effect of extreme climate change projections on the vegetation, upland erosion, and instream processes to produce changes in sediment redistribution within watersheds. To do so, research methods were carried out by the authors including simulating sediment processes in forecast and hindcast periods for a lowland watershed system. Publically available climate realizations from several climate factors and the Soil Water Assessment Tool (SWAT) were used to predict hydrologic conditions for the South Elkhorn Watershed in central Kentucky, USA to 2050. The results of the simulated extreme and mean hydrological components were used in simulating upland erosion with the connectivity processes consideration and thereafter used in building and simulating the instream erosion and deposition of sediment processes with the consideration of surface fine grain lamina (SFGL) layer controlling the benthic ecosystem. Results are used to suggest the dominance of erosional and depositional redistribution of sediments under different scenarios associated with extreme and mean hydrologic forecasting. The results are discussed in reference to the benthic ecology of the stream system providing insight on how water managers might consider sediment redistribution in a changing climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/46455','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/46455"><span>SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva</p> <p>2014-01-01</p> <p>Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...</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('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310604&keyword=topography&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=310604&keyword=topography&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>: “Developing Regional Modeling Techniques Applicable for Simulating Future Climate Conditions in the Carolinas”</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>Global climate models (GCMs) are currently used to obtain information about future changes in the large-scale climate. However, such simulations are typically done at coarse spatial resolutions, with model grid boxes on the order of 100 km on a horizontal side. Therefore, techniq...</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.osti.gov/biblio/1008259-impact-geoengineered-aerosols-troposphere-stratosphere','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1008259-impact-geoengineered-aerosols-troposphere-stratosphere"><span>Impact of geoengineered aerosols on the troposphere and stratosphere</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>Tilmes, S.; Garcia, Rolando R.; Kinnison, Douglas E.</p> <p>2009-06-27</p> <p>A coupled chemistry climate model, the Whole Atmosphere Community Climate Model was used to perform a transient climate simulation to quantify the impact of geoengineered aerosols on atmospheric processes. In contrast to previous model studies, the impact on stratospheric chemistry, including heterogeneous chemistry in the polar regions, is considered in this simulation. In the geoengineering simulation, a constant stratospheric distribution of volcanic-sized, liquid sulfate aerosols is imposed in the period 2020–2050, corresponding to an injection of 2 Tg S/a. The aerosol cools the troposphere compared to a baseline simulation. Assuming an Intergovernmental Panel on Climate Change A1B emission scenario, globalmore » warming is delayed by about 40 years in the troposphere with respect to the baseline scenario. Large local changes of precipitation and temperatures may occur as a result of geoengineering. Comparison with simulations carried out with the Community Atmosphere Model indicates the importance of stratospheric processes for estimating the impact of stratospheric aerosols on the Earth’s climate. Changes in stratospheric dynamics and chemistry, especially faster heterogeneous reactions, reduce the recovery of the ozone layer in middle and high latitudes for the Southern Hemisphere. In the geoengineering case, the recovery of the Antarctic ozone hole is delayed by about 30 years on the basis of this model simulation. For the Northern Hemisphere, a onefold to twofold increase of the chemical ozone depletion occurs owing to a simulated stronger polar vortex and colder temperatures compared to the baseline simulation, in agreement with observational estimates.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC13A0942W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC13A0942W"><span>Predicting the Impacts of Climate Change on Central American Agriculture</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>Winter, J. M.; Ruane, A. C.; Rosenzweig, C.</p> <p>2011-12-01</p> <p>Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.</p> </li> <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('http://adsabs.harvard.edu/abs/2015ESDD....6.1339P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESDD....6.1339P"><span>Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, 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>Paradis, D.; Vigneault, H.; Lefebvre, R.; Savard, M. M.; Ballard, J.-M.; Qian, B.</p> <p>2015-08-01</p> <p>Nitrate (N-NO3) concentration in groundwater, the sole source of potable water in Prince Edward Island (PEI, Canada), currently exceeds the 10 mg L-1 (N-NO3) health threshold for drinking water in 6 % of domestic wells. Increasing climatic and socio-economic pressures on PEI agriculture may further deteriorate groundwater quality. This study assesses how groundwater nitrate concentrations could evolve due to the forecasted climate change and its related potential changes in agricultural practices. For this purpose, a tridimensional numerical groundwater flow and mass transport model was developed for the aquifer system of the entire Island (5660 km2). A number of different groundwater flow and mass transport simulations were made to evaluate the potential impact of the projected climate change and agricultural adaptation. According to the simulations for year 2050, N-NO3 concentration would increase due to two main causes: (1) the progressive attainment of steady-state conditions related to present-day nitrogen loadings, and (2) the increase in nitrogen loadings due to changes in agricultural practices provoked by future climatic conditions. The combined effects of equilibration with loadings, climate and agricultural adaptation would lead to a 25 to 32 % increase in N-NO3 concentration over the Island aquifer system. Climate change alone (practices maintained at their current level) would contribute only 0 to 6 % to that increase according to the various climate scenarios. Moreover, simulated trends in groundwater N-NO3 concentration suggest that an increased number of domestic wells (more than doubling) would exceed the nitrate drinking water criteria. This study underlines the need to develop and apply better agricultural management practices to ensure sustainability of long-term groundwater resources. The simulations also show that observable benefits from positive changes in agricultural practices would be delayed in time due to the slow dynamics of nitrate transport within the aquifer system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1914903S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914903S"><span>Interactions between tectonics, climate and vegetation during the Cretaceous. A context for the diversification of Angiosperms.</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>Sepulchre, Pierre; Chaboureau, Anne-Claire; Donnadieu, Yannick; Franc, Alain; Ladant, Jean-Baptiste</p> <p>2017-04-01</p> <p>It has long been thought that the Angiosperms diversification occurred within a context of warmer-than-present and equable climate during the Cretaceous. However, during the last decade, the view of a uniformely warm Cretaceous climate has been challenged both by paleoclimate proxies and numerical simulations. Among the processes likely affecting climate during this time, atmospheric pCO2 and tectonics appear to be pivotal to drive temperature and precipitation changes, while the feedbacks from vegetation cover changes on the hydrological cycles remain to be explored. Here we attempt to provide a review of the main studies exploring climate-vegetation interactions during the Cretaceous. Then we present climate simulations aiming at quantifying the impact of landmasses redistribution on climate and vegetation distribution from 225 Ma to 70 Ma. In our simulations, the Pangea breakup triggers the decrease of arid belts from the Triassic to the Cretaceous and a subsequent onset of humid conditions during the late Cretaceous. Positioning angiosperm-bearing fossil sites on our paleo-bioclimatic maps confirm that the rise of flowering plants occured within a context of changing climate. With additional simulations in which we modified physiological parameterizations of the vegetation, we explore the combined impact of paleogeography and shift to angiosperms-dominated land surfaces on climate at the regional and global scales. This gives us the opportunity to test earlier ideas that the angiosperms takeover could have benefited from a positive feedback induced by their particular transpiration capacities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16..903N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16..903N"><span>A modelling approach to estimate carbon emissions from D.R.C. deforestation</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>Najdovski, Nicolas; Poulter, Benjamin; Defourny, Pierre; Moreau, Inès; Maignan, Fabienne; Ciais, Philippe; Verhegghen, Astrid; Kibambe Lubamba, Jean-Paul; Jungers, Quentin; De Weirdt, Marjolein; Verbeeck, Hans; MacBean, Natasha; Peylin, Philippe</p> <p>2014-05-01</p> <p>With its 1.8 million squared kilometres, the Congo basin dense forest represents the second largest contiguous forest of the world. These extensive forest ecosystems play a significant role in the regulation of global climate by their potential carbon dioxide emissions and carbon storage. Under a stable climate, the vegetation, assumed to be at the equilibrium, is known to present neutral emissions over a year with seasonal variations. However, modifications in temperatures, precipitations, CO2 atmospheric concentrations have the potential to modify this balance leading to higher or lower biomass storage. In addition, deforestation and forest degradation have played a significant role over the past several decades and are expected to become increasingly important in the future. Here, we quantify the relative effects of deforestation and 21st century climate change on carbon emissions in Congo Basin over the next three decades (2005-2035). Carbon dioxide emissions are estimated using a series of moderate resolution (10 km) vegetation maps merged with spatially explicit deforestation projections and developed to work with a prognostic carbon cycle model. The inversion of the deforestation model allowed hindcast land-use patterns back to 1800 by using land cover change rates based on the HYDE database. Simulations were made over the Democratic Republic of Congo (DRC) using the ORCHIDEE dynamic global vegetation model with climate forcing from the CMIP5 Representative Concentration Pathway 8.5 scenario for the HadGEM2. Two simulations were made, a reference simulation with land cover fixed at 2005 and a land cover change simulation with changing climate and CO2, to quantify the net land cover change emissions and climate emissions directly. Because of the relatively high resolution of the model simulations, the spatial patterns of human-driven carbon losses can be tracked in the context of climate change, providing information for mitigation and vulnerability activities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1455H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1455H"><span>Hydrological modeling as an evaluation tool of EURO-CORDEX climate projections and bias correction methods</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>Hakala, Kirsti; Addor, Nans; Seibert, Jan</p> <p>2017-04-01</p> <p>Streamflow stemming from Switzerland's mountainous landscape will be influenced by climate change, which will pose significant challenges to the water management and policy sector. In climate change impact research, the determination of future streamflow is impeded by different sources of uncertainty, which propagate through the model chain. In this research, we explicitly considered the following sources of uncertainty: (1) climate models, (2) downscaling of the climate projections to the catchment scale, (3) bias correction method and (4) parameterization of the hydrological model. We utilize climate projections at the 0.11 degree 12.5 km resolution from the EURO-CORDEX project, which are the most recent climate projections for the European domain. EURO-CORDEX is comprised of regional climate model (RCM) simulations, which have been downscaled from global climate models (GCMs) from the CMIP5 archive, using both dynamical and statistical techniques. Uncertainties are explored by applying a modeling chain involving 14 GCM-RCMs to ten Swiss catchments. We utilize the rainfall-runoff model HBV Light, which has been widely used in operational hydrological forecasting. The Lindström measure, a combination of model efficiency and volume error, was used as an objective function to calibrate HBV Light. Ten best sets of parameters are then achieved by calibrating using the genetic algorithm and Powell optimization (GAP) method. The GAP optimization method is based on the evolution of parameter sets, which works by selecting and recombining high performing parameter sets with each other. Once HBV is calibrated, we then perform a quantitative comparison of the influence of biases inherited from climate model simulations to the biases stemming from the hydrological model. The evaluation is conducted over two time periods: i) 1980-2009 to characterize the simulation realism under the current climate and ii) 2070-2099 to identify the magnitude of the projected change of streamflow under the climate scenarios RCP4.5 and RCP8.5. We utilize two techniques for correcting biases in the climate model output: quantile mapping and a new method, frequency bias correction. The FBC method matches the frequencies between observed and GCM-RCM data. In this way, it can be used to correct for all time scales, which is a known limitation of quantile mapping. A novel approach for the evaluation of the climate simulations and bias correction methods was then applied. Streamflow can be thought of as the "great integrator" of uncertainties. The ability, or the lack thereof, to correctly simulate streamflow is a way to assess the realism of the bias-corrected climate simulations. Long-term monthly mean as well as high and low flow metrics are used to evaluate the realism of the simulations under current climate and to gauge the impacts of climate change on streamflow. Preliminary results show that under present climate, calibration of the hydrological model comprises of a much smaller band of uncertainty in the modeling chain as compared to the bias correction of the GCM-RCMs. Therefore, for future time periods, we expect the bias correction of climate model data to have a greater influence on projected changes in streamflow than the calibration of the hydrological model.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMPA53B0281K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMPA53B0281K"><span>Reliability of the North America CORDEX and NARCCAP simulations in the context of uncertainty in 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>Karmalkar, A.</p> <p>2017-12-01</p> <p>Ensembles of dynamically downscaled climate change simulations are routinely used to capture uncertainty in projections at regional scales. I assess the reliability of two such ensembles for North America - NARCCAP and NA-CORDEX - by investigating the impact of model selection on representing uncertainty in regional projections, and the ability of the regional climate models (RCMs) to provide reliable information. These aspects - discussed for the six regions used in the US National Climate Assessment - provide an important perspective on the interpretation of downscaled results. I show that selecting general circulation models for downscaling based on their equilibrium climate sensitivities is a reasonable choice, but the six models chosen for NA-CORDEX do a poor job at representing uncertainty in winter temperature and precipitation projections in many parts of the eastern US, which lead to overconfident projections. The RCM performance is highly variable across models, regions, and seasons and the ability of the RCMs to provide improved seasonal mean performance relative to their parent GCMs seems limited in both RCM ensembles. Additionally, the ability of the RCMs to simulate historical climates is not strongly related to their ability to simulate climate change across the ensemble. This finding suggests limited use of models' historical performance to constrain their projections. Given these challenges in dynamical downscaling, the RCM results should not be used in isolation. Information on how well the RCM ensembles represent known uncertainties in regional climate change projections discussed here needs to be communicated clearly to inform maagement decisions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812690B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812690B"><span>Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological 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>Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten</p> <p>2016-04-01</p> <p>Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2004AGUSM.H23E..03J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2004AGUSM.H23E..03J"><span>Response of Groundwater Recharge to Potential Future Climate Change in the Grand River 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>Jyrkama, M. I.; Sykes, J. F.</p> <p>2004-05-01</p> <p>The Grand River watershed is situated in south-western Ontario, draining an area of nearly 7000 square kilometres into Lake Erie. Approximately eighty percent of the population in the watershed derive their drinking water from groundwater sources. Quantifying the recharge input to the groundwater system and the impact of climate variability due to climate change is, therefore, essential for ensuring the quantity and sustainability of the watershed's drinking water resources in the future. The primary goal of this study is to investigate the impact of potential future climate changes on groundwater recharge in the Grand River watershed. The physically based hydrologic model HELP3 is used in conjunction with GIS to simulate the past conditions and future changes in evapotranspiration, potential surface runoff, and groundwater recharge rates as a result of projected changes in the regions climate. The climate change projections are based on the general predictions reported by the Intergovernmental Panel on Climate Change (IPCC) in 2001. Forty years of daily historical weather data are used as the reference condition. The impact of climate change on the hydrologic cycle over a forty year study period is modelled by perturbing the HELP3 model input parameters using predicted future changes in precipitation, temperature, and solar radiation. The changes in land use and vegetation cover over time were not considered in the study. The results of the study indicate that the overall simulated rate of groundwater recharge is predicted to increase in the watershed as a result of the projected future climate change. Warmer winter temperatures will reduce the extent and duration of ground frost and shift the springmelt from spring toward winter months, allowing more water to infiltrate into the ground. This results in decreased surface runoff, higher infiltration, and subsequently increased groundwater recharge. The predicted higher intensity and frequency of future precipitation will not only contribute significantly to increased surface runoff, but also results in higher evapotranspiration and groundwater recharge rates due to increased amounts of available water. Changes in the incoming solar radiation have a minimal impact on the simulated hydrologic processes. The overall simulated average annual recharge in the watershed is predicted to increase by approximately 100 mm/year over the next forty years from 189 mm/year to 289 mm/year.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1361174-assessing-climate-change-impacts-benefits-mitigation-uncertainties-major-global-forest-regions-under-multiple-socioeconomic-emissions-scenarios','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1361174-assessing-climate-change-impacts-benefits-mitigation-uncertainties-major-global-forest-regions-under-multiple-socioeconomic-emissions-scenarios"><span>Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Kim, John B.; Monier, Erwan; Sohngen, Brent; ...</p> <p>2017-03-28</p> <p>We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ERL....12d5001K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ERL....12d5001K"><span>Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions 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>Kim, John B.; Monier, Erwan; Sohngen, Brent; Pitts, G. Stephen; Drapek, Ray; McFarland, James; Ohrel, Sara; Cole, Jefferson</p> <p>2017-04-01</p> <p>We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO2 fertilization effects may considerably reduce the range of projections.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1361174','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1361174"><span>Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios</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>Kim, John B.; Monier, Erwan; Sohngen, Brent</p> <p></p> <p>We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2 °C global mean warming from pre-industrial by 2100. Evaluating the outcomesmore » of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world’s forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Finally, our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://onlinelibrary.wiley.com/doi/10.1111/cobi.12163/abstract','USGSPUBS'); return false;" href="http://onlinelibrary.wiley.com/doi/10.1111/cobi.12163/abstract"><span>Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions</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>Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,</p> <p>2013-01-01</p> <p>Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017BGeo...14.4355F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017BGeo...14.4355F"><span>The influence of El Niño-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming 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>Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian</p> <p>2017-09-01</p> <p>The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.9420V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.9420V"><span>Assessment of bias correction under transient 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>Van Schaeybroeck, Bert; Vannitsem, Stéphane</p> <p>2015-04-01</p> <p>Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PIAHS.371..195L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PIAHS.371..195L"><span>Revisiting historical climatic signals to better explore the future: prospects of water cycle changes in Central Sahel</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>Leauthaud, C.; Demarty, J.; Cappelaere, B.; Grippa, M.; Kergoat, L.; Velluet, C.; Guichard, F.; Mougin, E.; Chelbi, S.; Sultan, B.</p> <p>2015-06-01</p> <p>Rainfall and climatic conditions are the main drivers of natural and cultivated vegetation productivity in the semiarid region of Central Sahel. In a context of decreasing cultivable area per capita, understanding and predicting changes in the water cycle are crucial. Yet, it remains challenging to project future climatic conditions in West Africa since there is no consensus on the sign of future precipitation changes in simulations coming from climate models. The Sahel region has experienced severe climatic changes in the past 60 years that can provide a first basis to understand the response of the water cycle to non-stationary conditions in this part of the world. The objective of this study was to better understand the response of the water cycle to highly variable climatic regimes in Central Sahel using historical climate records and the coupling of a land surface energy and water model with a vegetation model that, when combined, simulated the Sahelian water, energy and vegetation cycles. To do so, we relied on a reconstructed long-term climate series in Niamey, Republic of Niger, in which three precipitation regimes can be distinguished with a relative deficit exceeding 25% for the driest period compared to the wettest period. Two temperature scenarios (+2 and +4 °C) consistent with future warming scenarios were superimposed to this climatic signal to generate six virtual future 20-year climate time series. Simulations by the two coupled models forced by these virtual scenarios showed a strong response of the water budget and its components to temperature and precipitation changes, including decreases in transpiration, runoff and drainage for all scenarios but those with highest precipitation. Such climatic changes also strongly impacted soil temperature and moisture. This study illustrates the potential of using the strong climatic variations recorded in the past decades to better understand potential future climate variations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC31F1173L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC31F1173L"><span>Signal to noise quantification of regional climate 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>Li, S.; Rupp, D. E.; Mote, P.</p> <p>2016-12-01</p> <p>One of the biggest challenges in interpreting climate model outputs for impacts studies and adaptation planning is understanding the sources of disagreement among models (which is often used imperfectly as a stand-in for system uncertainty). Internal variability is a primary source of uncertainty in climate projections, especially for precipitation, for which models disagree about even the sign of changes in large areas like the continental US. Taking advantage of a large initial-condition ensemble of regional climate simulations, this study quantifies the magnitude of changes forced by increasing greenhouse gas concentrations relative to internal variability. Results come from a large initial-condition ensemble of regional climate model simulations generated by weather@home, a citizen science computing platform, where the western United States climate was simulated for the recent past (1985-2014) and future (2030-2059) using a 25-km horizontal resolution regional climate model (HadRM3P) nested in global atmospheric model (HadAM3P). We quantify grid point level signal-to-noise not just in temperature and precipitation responses, but also the energy and moisture flux terms that are related to temperature and precipitation responses, to provide important insights regarding uncertainty in climate change projections at local and regional scales. These results will aid modelers in determining appropriate ensemble sizes for different climate variables and help users of climate model output with interpreting climate model projections.</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('http://adsabs.harvard.edu/abs/2013AGUFMGC11F..07S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC11F..07S"><span>Using historical and projected future climate model simulations as drivers of agricultural and biological models (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>Stefanova, L. B.</p> <p>2013-12-01</p> <p>Climate model evaluation is frequently performed as a first step in analyzing climate change simulations. Atmospheric scientists are accustomed to evaluating climate models through the assessment of model climatology and biases, the models' representation of large-scale modes of variability (such as ENSO, PDO, AMO, etc) and the relationship between these modes and local variability (e.g. the connection between ENSO and the wintertime precipitation in the Southeast US). While these provide valuable information about the fidelity of historical and projected climate model simulations from an atmospheric scientist's point of view, the application of climate model data to fields such as agriculture, ecology and biology may require additional analyses focused on the particular application's requirements and sensitivities. Typically, historical climate simulations are used to determine a mapping between the model and observed climate, either through a simple (additive for temperature or multiplicative for precipitation) or a more sophisticated (such as quantile matching) bias correction on a monthly or seasonal time scale. Plants, animals and humans however are not directly affected by monthly or seasonal means. To assess the impact of projected climate change on living organisms and related industries (e.g. agriculture, forestry, conservation, utilities, etc.), derivative measures such as the heating degree-days (HDD), cooling degree-days (CDD), growing degree-days (GDD), accumulated chill hours (ACH), wet season onset (WSO) and duration (WSD), among others, are frequently useful. We will present a comparison of the projected changes in such derivative measures calculated by applying: (a) the traditional temperature/precipitation bias correction described above versus (b) a bias correction based on the mapping between the historical model and observed derivative measures themselves. In addition, we will present and discuss examples of various application-based climate model evaluations, such as: (a) agricultural crop yield estimates and (b) species population viability estimates modeled using observed climate data vs. historical climate simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC31A0988M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC31A0988M"><span>Merging Methods to Manage Uncertainty: Combining Simulation Modeling and Scenario Planning to Inform Resource 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>Miller, B. W.; Schuurman, G. W.; Symstad, A.; Fisichelli, N. A.; Frid, L.</p> <p>2017-12-01</p> <p>Managing natural resources in this era of anthropogenic climate change is fraught with uncertainties around how ecosystems will respond to management actions and a changing climate. Scenario planning (oftentimes implemented as a qualitative, participatory exercise for exploring multiple possible futures) is a valuable tool for addressing this challenge. However, this approach may face limits in resolving responses of complex systems to altered climate and management conditions, and may not provide the scientific credibility that managers often require to support actions that depart from current practice. Quantitative information on projected climate changes and ecological responses is rapidly growing and evolving, but this information is often not at a scale or in a form that is `actionable' for resource managers. We describe a project that sought to create usable information for resource managers in the northern Great Plains by combining qualitative and quantitative methods. In particular, researchers, resource managers, and climate adaptation specialists co-produced a simulation model in conjunction with scenario planning workshops to inform natural resource management in southwest South Dakota. Scenario planning for a wide range of resources facilitated open-minded thinking about a set of divergent and challenging, yet relevant and plausible, climate scenarios and management alternatives that could be implemented in the simulation. With stakeholder input throughout the process, we built a simulation of key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between herd sizes and vegetation composition, and between the short- versus long-term costs of invasive species management. It also identified impactful uncertainties related to the effects of fire and grazing on vegetation. Ultimately, this integrative and iterative approach yielded counter-intuitive and surprising findings, and resulted in a more tractable set of possible futures for resource management planning.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25757292','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25757292"><span>[Simulating climate change effect on aboveground carbon sequestration rates of main broadleaved trees in the Xiaoxing'an Mountains area, Northeast China].</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>Ma, Jun; Bu, Rencang; Deng, Hua-Wei; Hu, Yuan-Man; Qin, Qin; Han, Feng-Lin</p> <p>2014-09-01</p> <p>LANDIS Pro 7.0 model was used to simulate the dynamics of aboveground biomass of ten broadleaved tree species in the Xiao Xing' an Mountains area under current and various climate change scenarios from 2000 to 2200, and carbon content coefficients (CCCs) were coupled to cal- culate the aboveground carbon sequestration rates (ACSRs) of these species. The results showed that in the initial year of simulation, the biomasses and their proportions of Fraxinus mandshurica, Phellodendron amurense, Quercus mongolica, Ulmus propinqua, and Acer mono were relatively low, while those of Betula costata, Betula platyphylla, and Populus davidiana were higher. A trend of rise after decline occurred in ACSR for pioneer species in the mid and late periods of simulation years, but ACSRs for the other broadleaved tree species were considerably complex. The ACSRs of Q. mongolica and Tilla amurensis fluctuated in the ranges of -0.05-0.25 t · hm(-2) · 10 a(-1) and 0.16-1.29 t · hm(-2) · 10 a(-1) in simulation years, respectively. The ACSRs of F. mandshurica, U. propinqua, A. mono, and B. costata showed a trend of decline after rise in late simulation years. There were significant differences in ACSR for P. amurense and B. davurica among various climate change scenarios in the periods of 2050-2100 and 2150-2200, while no significant difference in ACSR for the other species would be detected. Difference of sensitivity of various species in ACSR for future climate scenarios in the Small Khingan Mountains area existed. However, the un- certainty of future climates would not yield significant difference in ACSR for most broadleaved tree species. Moreover, a time lag would exist in the process of climate change effects on temperate forest's ACSR.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1813025J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1813025J"><span>High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale 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>Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis</p> <p>2016-04-01</p> <p>The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018HESS...22.1411T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018HESS...22.1411T"><span>Land-use change may exacerbate climate change impacts on water resources in the Ganges 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>Tsarouchi, Gina; Buytaert, Wouter</p> <p>2018-02-01</p> <p>Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000-2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000-2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030-2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JHyd..549..534C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JHyd..549..534C"><span>Impacts of weighting climate models for hydro-meteorological climate change 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>Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel</p> <p>2017-06-01</p> <p>Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC21A1056O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC21A1056O"><span>Climate change indices for Greenland applied directly for other arctic regions - Enhanced and utilized climate information from one high resolution RCM downscaling for Greenland evaluated through pattern scaling and CMIP5</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>Olesen, M.; Christensen, J. H.; Boberg, F.</p> <p>2016-12-01</p> <p>Climate change indices for Greenland applied directly for other arctic regions - Enhanced and utilized climate information from one high resolution RCM downscaling for Greenland evaluated through pattern scaling and CMIP5Climate change affects the Greenlandic society both advantageously and disadvantageously. Changes in temperature and precipitation patterns may result in changes in a number of derived society related climate indices, such as the length of growing season or the number of annual dry days or a combination of the two - indices of substantial importance to society in a climate adaptation context.Detailed climate indices require high resolution downscaling. We have carried out a very high resolution (5 km) simulation with the regional climate model HIRHAM5, forced by the global model EC-Earth. Evaluation of RCM output is usually done with an ensemble of downscaled output with multiple RCM's and GCM's. Here we have introduced and tested a new technique; a translation of the robustness of an ensemble of GCM models from CMIP5 into the specific index from the HIRHAM5 downscaling through a correlation between absolute temperatures and its corresponding index values from the HIRHAM5 output.The procedure is basically conducted in two steps: First, the correlation between temperature and a given index for the HIRHAM5 simulation by a best fit to a second order polynomial is identified. Second, the standard deviation from the CMIP5 simulations is introduced to show the corresponding standard deviation of the index from the HIRHAM5 run. The change of specific climate indices due to global warming will then be possible to evaluate elsewhere corresponding to the change in absolute temperature.Results based on selected indices with focus on the future climate in Greenland calculated for the rcp4.5 and rcp8.5 scenarios will be presented.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014E%26ES...18a2106H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014E%26ES...18a2106H"><span>Simulation of Land-Cover Change in Taipei Metropolitan Area under 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>Huang, Kuo-Ching; Huang, Thomas C. C.</p> <p>2014-02-01</p> <p>Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25666284','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25666284"><span>Direct and indirect effects of climate change on herbicide leaching--a regional scale assessment in Sweden.</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>Steffens, Karin; Jarvis, Nicholas; Lewan, Elisabet; Lindström, Bodil; Kreuger, Jenny; Kjellström, Erik; Moeys, Julien</p> <p>2015-05-01</p> <p>Climate change is not only likely to improve conditions for crop production in Sweden, but also to increase weed pressure and the need for herbicides. This study aimed at assessing and contrasting the direct and indirect effects of climate change on herbicide leaching to groundwater in a major crop production region in south-west Sweden with the help of the regional pesticide fate and transport model MACRO-SE. We simulated 37 out of the 41 herbicides that are currently approved for use in Sweden on eight major crop types for the 24 most common soil types in the region. The results were aggregated accounting for the fractional coverage of the crop and the area sprayed with a particular herbicide. For simulations of the future, we used projections of five different climate models as model driving data and assessed three different future scenarios: (A) only changes in climate, (B) changes in climate and land-use (altered crop distribution), and (C) changes in climate, land-use, and an increase in herbicide use. The model successfully distinguished between leachable and non-leachable compounds (88% correctly classified) in a qualitative comparison against regional-scale monitoring data. Leaching was dominated by only a few herbicides and crops under current climate and agronomic conditions. The model simulations suggest that the direct effects of an increase in temperature, which enhances degradation, and precipitation which promotes leaching, cancel each other at a regional scale, resulting in a slight decrease in leachate concentrations in a future climate. However, the area at risk of groundwater contamination doubled when indirect effects of changes in land-use and herbicide use, were considered. We therefore concluded that it is important to consider the indirect effects of climate change alongside the direct effects and that effective mitigation strategies and strict regulation are required to secure future (drinking) water resources. Copyright © 2014 Elsevier B.V. All rights reserved.</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('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://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310513&keyword=climate+AND+adaptation&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=310513&keyword=climate+AND+adaptation&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>Simulating the hydrologic impacts of land-cover and climate changes in a semi-arid watershed</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>Changes in climate and land cover are principal variables affecting watershed hydrology. This paper uses a cell-based model to examine the hydrologic impacts of climate and land cover changes in the semi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevad...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70189332','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70189332"><span>Climate-induced warming of lakes can be either amplified or suppressed by trends in water clarity</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>Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Hansen, Gretchen J. A.</p> <p>2016-01-01</p> <p>Climate change is rapidly warming aquatic ecosystems including lakes and reservoirs. However, variability in lake characteristics can modulate how lakes respond to climate. Water clarity is especially important both because it influences the depth range over which heat is absorbed, and because it is changing in many lakes. Here, we show that simulated long-term water clarity trends influence how both surface and bottom water temperatures of lakes and reservoirs respond to climate change. Clarity changes can either amplify or suppress climate-induced warming, depending on lake depth and the direction of clarity change. Using a process-based model to simulate 1894 north temperate lakes from 1979 to 2012, we show that a scenario of decreasing clarity at a conservative yet widely observed rate of 0.92% yr−1 warmed surface waters and cooled bottom waters at rates comparable in magnitude to climate-induced warming. For lakes deeper than 6.5 m, decreasing clarity was sufficient to fully offset the effects of climate-induced warming on median whole-lake mean temperatures. Conversely, a scenario increasing clarity at the same rate cooled surface waters and warmed bottom waters relative to baseline warming rates. Furthermore, in 43% of lakes, increasing clarity more than doubled baseline bottom temperature warming rates. Long-term empirical observations of water temperature in lakes with and without clarity trends support these simulation results. Together, these results demonstrate that water clarity trends may be as important as rising air temperatures in determining how waterbodies respond to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/659000-changes-extremes-climate-simulated-ccc-gcm2-under-co-sub-doubling','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/659000-changes-extremes-climate-simulated-ccc-gcm2-under-co-sub-doubling"><span>Changes in the extremes of the climate simulated by CCC GCM2 under CO{sub 2} doubling</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>Zwiers, F.W.; Kharin, V.V.</p> <p></p> <p>Changes due to CO{sub 2} doubling in the extremes of the surface climate as simulated by the second-generation circulation model of the Canadian Centre for Climate Modelling and Analysis are studied in two 20-yr equilibrium simulations. Extreme values of screen temperature, precipitation, and near-surface wind in the control climate are compared to those estimated from 17 yr of the NCEP-NCAR reanalysis data and from some Canadian station data. The extremes of screen temperature are reasonably well reproduced in the control climate. Their changes under CO{sub 2} doubling can be connected with other physical changes such as surface albedo changes duemore » to the reduction of snow and sea ice cover as well as a decrease of soil moisture in the warmer world. The signal in the extremes of daily precipitation and near-surface wind speed due to CO{sub 2} doubling is less obvious. The precipitation extremes increase almost everywhere over the globe. The strongest change, over northwest India, is related to the intensification of the summer monsoon in this region in the warmer world. The modest reduction of wind extremes in the Tropics and middle latitudes is consistent with the reduction of the meridional temperature gradient in the 2{times}CO{sub 2} climate. The larger wind extremes occur in the areas where sea ice has retreated.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1000040','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1000040"><span>Regional-Scale Climate Change: Observations and Model Simulations</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>Bradley, Raymond S; Diaz, Henry F</p> <p>2010-12-14</p> <p>This collaborative proposal addressed key issues in understanding the Earth's climate system, as highlighted by the U.S. Climate Science Program. The research focused on documenting past climatic changes and on assessing future climatic changes based on suites of global and regional climate models. Geographically, our emphasis was on the mountainous regions of the world, with a particular focus on the Neotropics of Central America and the Hawaiian Islands. Mountain regions are zones where large variations in ecosystems occur due to the strong climate zonation forced by the topography. These areas are particularly susceptible to changes in critical ecological thresholds, andmore » we conducted studies of changes in phonological indicators based on various climatic thresholds.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMGC11B0982J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMGC11B0982J"><span>Climate implications of including albedo effects in terrestrial carbon policy</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>Jones, A. D.; Collins, W.; Torn, M. S.; Calvin, K. V.</p> <p>2012-12-01</p> <p>Proposed strategies for managing terrestrial carbon in order to mitigate anthropogenic climate change, such as financial incentives for afforestation, soil carbon sequestration, or biofuel production, largely ignore the direct effects of land use change on climate via biophysical processes that alter surface energy and water budgets. Subsequent influences on temperature, hydrology, and atmospheric circulation at regional and global scales could potentially help or hinder climate stabilization efforts. Because these policies often rely on payments or credits expressed in units of CO2-equivalents, accounting for biophysical effects would require a metric for comparing the strength of biophysical climate perturbation from land use change to that of emitting CO2. One such candidate metric that has been suggested in the literature on land use impacts is radiative forcing, which underlies the global warming potential metric used to compare the climate effects of various greenhouse gases with one another. Expressing land use change in units of radiative forcing is possible because albedo change results in a net top-of-atmosphere radiative flux change. However, this approach has also been critiqued on theoretical grounds because not all climatic changes associated with land use change are principally radiative in nature, e.g. changes in hydrology or the vertical distribution of heat within the atmosphere, and because the spatial scale of land use change forcing differs from that of well-mixed greenhouse gases. To explore the potential magnitude of this discrepancy in the context of plausible scenarios of future land use change, we conduct three simulations with the Community Climate System Model 4 (CCSM4) utilizing a slab ocean model. Each simulation examines the effect of a stepwise change in forcing relative to a pre-industrial control simulation: 1) widespread conversion of forest land to crops resulting in approximately 1 W/m2 global-mean radiative forcing from albedo change, 2) an increase in CO2 concentrations that exactly balances the forcing from land use change at the global level, and 3) a simulation combining the first two effects, resulting in net zero global-mean forcing as would occur in an idealized carbon cap-and-trade scheme that accounts for the albedo effect of land use change. The pattern of land use change that we examine is derived from an integrated assessment model that accounts for population, demographic, technological, and policy changes over the 21st century. We find significant differences in the pattern of climate change associated with each of these forcing scenarios, demonstrating the non-additivity of radiative forcing from land-use change and greenhouse gases in the context of a hypothetical scenario of future land use change. These results have implications for the development of land use and climate policies.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=256499','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=256499"><span>Trend and uncertainty analysis of simulated climate change impacts with multiple GCMs and emission scenarios</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>Impacts of climate change on hydrology, soil erosion, and wheat production during 2010-2039 at El Reno in central Oklahoma, USA, were simulated using the Water Erosion Prediction Project (WEPP) model. Projections from four GCMs (CCSR/NIES, CGCM2, CSIRO-Mk2, and HadCM3) under three emissions scenari...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=313368','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=313368"><span>Farm simulation: a tool for evaluating the mitigation of greenhouse gas emissions and the adaptation of dairy production to climate change</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>Process-level modeling at the farm scale provides a tool for evaluating both strategies for mitigating greenhouse gas emissions and strategies for adapting to climate change. The Integrated Farm System Model (IFSM) simulates representative crop, beef or dairy farms over many years of weather to pred...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=310324&Lab=NERL&keyword=simulation+AND+processes&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=310324&Lab=NERL&keyword=simulation+AND+processes&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>Evaluating relative sensitivity of SWAT-simulated nitrogen discharge to projected climate and land cover changes for two watersheds in North Carolina, USA</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>We investigated how projected changes in land cover and climate affected simulated nitrate (NO3−) and organic nitrogen (ORGN) discharge for two watersheds within the Neuse River Basin North Carolina, USA for years 2010 to 2070. We applied the Soil and Water Assessment Tool ...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=255872&keyword=salmon&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=255872&keyword=salmon&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>Evaluations of alternative methods for monitoring and estimating responses of salmon productivity in the North Pacific to future climatic change and other processes: A simulation study</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>Estimation of the relative influence of climate change, compared to other human activities, on dynamics of Pacific salmon (Oncorhynchus spp.) populations can help management agencies take appropriate management actions. We used empirically based simulation modelling of 48 sockeye...</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('https://pubs.er.usgs.gov/publication/70041624','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70041624"><span>Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon</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>Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.</p> <p>2013-01-01</p> <p>We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFMEP33B0856B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFMEP33B0856B"><span>Modelling the Holderness coast, eastern England: Past, present and 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>Barkwith, A.; Limber, P. W.; Thomas, C. W.; Murray, A.; Jordan, H. M.; Ellis, M. A.</p> <p>2012-12-01</p> <p>The Holderness coast of eastern Yorkshire, England, is the most rapidly eroding coastline in Europe. Erosion can locally exceed 10 m in a single year and rates average 0.5 to 3 m yr-1, generally increasing from north to south. Pinned in the north by a chalk headland, the soft till coastline has a characteristic open spiral form terminated by a spit to the south. Erosion currently threatens local communities and infrastructure, including nationally important gas installations. Interventions to restrict local erosion usually result in enhanced erosion in adjacent, unprotected sections of coast, mirroring morphology seen on the large scale. We have initiated a modelling study to investigate the key controls on the form and evolution of this coastline, and its response to climate change, building on the Coastline Evolution Model (CEM) developed at Duke University, NC. We have adapted the CEM to permit an ensemble of simulations to be undertaken, based upon modified offshore wave climates, initial conditions and forcing factors. The CEM follows a standard 1d approach, where the cross-shore is collapsed into a single data point, allowing the planform shoreline shape and dynamics to be simulated. The model facilitates study of a coast with variable erosion rates, and enables simulation of coastline evolution when sediment is supplied from an eroding shoreface. Additionally, the CEM is adapted to use an observed two year, offshore wave climate data set as input. Initial work focussed on reconstruction of current coastline shape from an ensemble of hypothetical early Holocene shoreface positions and past wave climates. First order reconstruction of shoreline shape was achieved using several differing initial conditions and wave climates. For the majority of successful simulations, a steady state was noted for proceeding years, where erosion proceeds at an equal rate along the length of the coast south of the headland. Together with a sensitivity analysis, the derivation of the current coastline provided initial conditions for the second phase of the work: simulating the morphological response of the Holderness coastline to possible future changes in climate over the next century. An ensemble of future possible wave climate perturbations was generated from predictions of the likely response of the North Sea to future climate change over the next century, and applied linearly to the observed wave climate as each simulation progressed. The ensemble output was compared to a baseline simulation, run for a century under current wave climate, to assess the impact of predicted future climate on coastal erosion. Although this study does not currently take into account the changes in storm frequency, rises in sea level or the anthropogenic inputs that could influence the results, the initial output indicates erosional rates over the next century are likely to be retarded for the Holderness coastline under a changing climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24043872','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24043872"><span>The Early Eocene equable climate problem: can perturbations of climate model parameters identify possible solutions?</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>Sagoo, Navjit; Valdes, Paul; Flecker, Rachel; Gregoire, Lauren J</p> <p>2013-10-28</p> <p>Geological data for the Early Eocene (56-47.8 Ma) indicate extensive global warming, with very warm temperatures at both poles. However, despite numerous attempts to simulate this warmth, there are remarkable data-model differences in the prediction of these polar surface temperatures, resulting in the so-called 'equable climate problem'. In this paper, for the first time an ensemble with a perturbed climate-sensitive model parameters approach has been applied to modelling the Early Eocene climate. We performed more than 100 simulations with perturbed physics parameters, and identified two simulations that have an optimal fit with the proxy data. We have simulated the warmth of the Early Eocene at 560 ppmv CO2, which is a much lower CO2 level than many other models. We investigate the changes in atmospheric circulation, cloud properties and ocean circulation that are common to these simulations and how they differ from the remaining simulations in order to understand what mechanisms contribute to the polar warming. The parameter set from one of the optimal Early Eocene simulations also produces a favourable fit for the last glacial maximum boundary climate and outperforms the control parameter set for the present day. Although this does not 'prove' that this model is correct, it is very encouraging that there is a parameter set that creates a climate model able to simulate well very different palaeoclimates and the present-day climate. Interestingly, to achieve the great warmth of the Early Eocene this version of the model does not have a strong future climate change Charney climate sensitivity. It produces a Charney climate sensitivity of 2.7(°)C, whereas the mean value of the 18 models in the IPCC Fourth Assessment Report (AR4) is 3.26(°)C±0.69(°)C. Thus, this value is within the range and below the mean of the models included in the AR4.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70021201','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70021201"><span>Modeling the effects of land use and climate change on riverine smallmouth bass</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>Peterson, J.T.; Kwak, T.J.</p> <p>1999-01-01</p> <p>Anthropogenic changes in temperature and stream flow, associated with watershed land use and climate change, are critical influences on the distribution and abundance of riverine fishes. To project the effects of changing land use and climate, we modeled a smallmouth bass (Micropterus dolomieu) population in a midwestern USA, large river- floodplain ecosystem under historical (1915-1925), present (1977-1990), and future (2060, influenced by climate change) temperature and flow regimes. The age-structured model included parameters for temperature and river discharge during critical seasonal periods, fish population dynamics, and fishing harvest. Model relationships were developed from empirical field data collected over a 13-yr period. Sensitivity analyses indicated that discharge during the spawning/rearing period had a greater effect on adult density and fishing yield than did spawning/rearing temperature or winter discharge. Simulations for 100 years projected a 139% greater mean fish density under a historical flow regime (64.9 fish/ha) than that estimated for the present (27.1 fish/ha) with a sustainable fishing harvest under both flow regimes. Simulations under future climate-change-induced temperature and flow regimes with present land use projected a 69% decrease in mean fish density (8.5 fish/ha) from present and an unstable population that went extinct during 56% of the simulations. However, when simulated under a future climate-altered temperature and flow regime with historical land use, the population increased by 66% (45.0 fish/ha) from present and sustained a harvest. Our findings suggest that land-use changes may be a greater detriment to riverine fishes than projected climate change and that the combined effects of both factors may lead to local species extinction. However, the negative effects of increased temperature and precipitation associated with future global warming could be mitigated by river channel, floodplain, and watershed restoration.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp..106K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp..106K"><span>Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent</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>Kang, Suchul; Im, Eun-Soon; Eltahir, Elfatih A. B.</p> <p>2018-03-01</p> <p>In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976-2005, RCP4.5 and RCP8.5: 2071-2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC13C1098T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC13C1098T"><span>Effectiveness and Tradeoffs between Portfolios of Adaptation Strategies Addressing Future Climate and Socioeconomic Uncertainties in California's Central Valley</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>Tansey, M. K.; Van Lienden, B.; Das, T.; Munevar, A.; Young, C. A.; Flores-Lopez, F.; Huntington, J. L.</p> <p>2013-12-01</p> <p>The Central Valley of California is one of the major agricultural areas in the United States. The Central Valley Project (CVP) is operated by the Bureau of Reclamation to serve multiple purposes including generating approximately 4.3 million gigawatt hours of hydropower and providing, on average, 5 million acre-feet of water per year to irrigate approximately 3 million acres of land in the Sacramento, San Joaquin, and Tulare Lake basins, 600,000 acre-feet per year of water for urban users, and 800,000 acre-feet of annual supplies for environmental purposes. The development of effective adaptation and mitigation strategies requires assessing multiple risks including potential climate changes as well as uncertainties in future socioeconomic conditions. In this study, a scenario-based analytical approach was employed by combining three potential 21st century socioeconomic futures with six representative climate and sea level change projections developed using a transient hybrid delta ensemble method from an archive of 112 bias corrected spatially downscaled CMIP3 global climate model simulations to form 18 future socioeconomic-climate scenarios. To better simulate the effects of climate changes on agricultural water demands, analyses of historical agricultural meteorological station records were employed to develop estimates of future changes in solar radiation and atmospheric humidity from the GCM simulated temperature and precipitation. Projected changes in atmospheric carbon dioxide were computed directly by weighting SRES emissions scenarios included in each representative climate projection. These results were used as inputs to a calibrated crop water use, growth and yield model to simulate the effects of climate changes on the evapotranspiration and yields of major crops grown in the Central Valley. Existing hydrologic, reservoir operations, water quality, hydropower, greenhouse gas (GHG) emissions and both urban and agricultural economic models were integrated into a suite of decision support tools to assess the impacts of future socioeconomic-climate uncertainties on key performance metrics for the CVP, State Water Project and other Central Valley water management systems under current regulatory requirements. Four thematic portfolios consisting of regional and local adaptation strategies including changes in reservoir operations, increased water conservation, storage and conveyance were developed and simulated to evaluate their potential effectiveness in meeting delivery reliability, water quality, environmental, hydropower, GHG, urban and agricultural economic performance criteria. The results indicate that the portfolios exhibit a considerable range of effectiveness depending on the socioeconomic-climate scenario. For most criteria, the portfolios were more sensitive to climate projections than socioeconomic assumptions. However, the results demonstrate that important tradeoffs occur between portfolios depending on the performance criteria considered.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMED31E..07T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMED31E..07T"><span>Impacts Of Global/Regional Climate Changes On Environment And Health: Need For Integrated Research And Education Collaboration (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>Tuluri, F.</p> <p>2013-12-01</p> <p>The realization of long term changes in climate in research community has to go beyond the comfort zone through climate literacy in academics. Higher education on climate change is the platform to bring together the otherwise disconnected factors such as effective discovery, decision making, innovation, interdisciplinary collaboration, Climate change is a complex process that may be due to natural internal processes within the climate system, or to variations in natural or anthropogenic (human-driven) external forcing. Global climate change indicates a change in either the mean state of the climate or in its variability, persisting for several decades or longer. This includes changes in average weather conditions on Earth, such as a change in average global temperature, as well as changes in how frequently regions experience heat waves, droughts, floods, storms, and other extreme weather. It is important to examine the effects of climate variations on human health and disorders in order to take preventive measures. Similarly, the influence of climate changes on animal management practices, pests and pest management systems, and high value crops such as citrus and vegetables is also equally important for investigation. New genetic agricultural varieties must be explored, and pilot studies should examine biotechnology transfer. Recent climate model improvements have resulted in an enhanced ability to simulate many aspects of climate variability and extremes. However, they are still characterized by systematic errors and limitations in accurately simulating more precisely regional climate conditions. The present situations warrant developing climate literacy on the synergistic impacts of environmental change, and improve development, testing and validation of integrated stress impacts through computer modeling. In the present study we present a detailed study of the current status on the impacts of global/regional climate changes on environment and health with a view to highlighting the need for integrated research and education collaboration at national and global level.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3536B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3536B"><span>Implications of land use change in tropical West Africa 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>Brücher, Tim; Claussen, Martin</p> <p>2015-04-01</p> <p>Northern Africa, and the Sahel in particular, are highly vulnerable to climate change, due to strong exposure to increasing temperature, precipitation variability, and population growth. A major link between climate and humans in this region is land use and associated land cover change, mainly where subsistence farming prevails. But how strongly does climate change affect land use and how strongly does land use feeds back into climate change? To which extent may climate-induced water, food and wood shortages exacerbate conflict potential and lead changes in land use and to migration? Estimates of possible changes in African climate vary among the Earth System Models participating in the recent Coupled Model Intercomparison (CMIP5) exercise, except for the region adjacent to the Mediterranean Sea, where a significant decrease of precipitation emerges. While all models agree in a strong temperature increase, rainfall uncertainties for most parts of the Sahara, Sahel, and Sudan are higher. Here we present results of complementary experiments based on extreme and idealized land use change scenarios within a future climate.. We use the MPI-ESM forced with a strong green house gas scenario (RCP8.5) and apply an additional land use forcing by varying largely the intensity and kind of agricultural practice. By these transient experiments (until 2100) we elaborate the additional impact on climate due to strong land use forcing. However, the differences are mostly insignificant. The greenhouse gas caused temperature increase and the high variability in the West African Monsoon rainfall superposes the minor changes in climate due to land use. While simulated climate key variables like precipitation and temperature are not distinguishable from the CMIP5 RCP8.5 results, an additional greening is simulated, when crops are demanded. Crops have lower water usage than pastureland has. This benefits available soil water, which is taken up by the natural vegetation and makes it more productive. Given the limitations of an ESM, the findings of our study show that changes in the kind and intensity of land use have minor effects on the climate. Consequently, implications of extreme land use on e.g. human security, conflict or migration can be investigated in offline simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26438281','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26438281"><span>Shortwave forcing and feedbacks in Last Glacial Maximum and Mid-Holocene PMIP3 simulations.</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>Braconnot, Pascale; Kageyama, Masa</p> <p>2015-11-13</p> <p>Simulations of the climates of the Last Glacial Maximum (LGM), 21 000 years ago, and of the Mid-Holocene (MH), 6000 years ago, allow an analysis of climate feedbacks in climate states that are radically different from today. The analyses of cloud and surface albedo feedbacks show that the shortwave cloud feedback is a major driver of differences between model results. Similar behaviours appear when comparing the LGM and MH simulated changes, highlighting the fingerprint of model physics. Even though the different feedbacks show similarities between the different climate periods, the fact that their relative strength differs from one climate to the other prevents a direct comparison of past and future climate sensitivity. The land-surface feedback also shows large disparities among models even though they all produce positive sea-ice and snow feedbacks. Models have very different sensitivities when considering the vegetation feedback. This feedback has a regional pattern that differs significantly between models and depends on their level of complexity and model biases. Analyses of the MH climate in two versions of the IPSL model provide further indication on the possibilities to assess the role of model biases and model physics on simulated climate changes using past climates for which observations can be used to assess the model results. © 2015 The Author(s).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.usgs.gov/of/2011/1238/','USGSPUBS'); return false;" href="https://pubs.usgs.gov/of/2011/1238/"><span>Dynamically downscaled climate simulations over North America: Methods, evaluation, and supporting documentation for users</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.; Alder, J.R.; Allan, A.M.</p> <p>2011-01-01</p> <p>We have completed an array of high-resolution simulations of present and future climate over Western North America (WNA) and Eastern North America (ENA) by dynamically downscaling global climate simulations using a regional climate model, RegCM3. The simulations are intended to provide long time series of internally consistent surface and atmospheric variables for use in climate-related research. In addition to providing high-resolution weather and climate data for the past, present, and future, we have developed an integrated data flow and methodology for processing, summarizing, viewing, and delivering the climate datasets to a wide range of potential users. Our simulations were run over 50- and 15-kilometer model grids in an attempt to capture more of the climatic detail associated with processes such as topographic forcing than can be captured by general circulation models (GCMs). The simulations were run using output from four GCMs. All simulations span the present (for example, 1968-1999), common periods of the future (2040-2069), and two simulations continuously cover 2010-2099. The trace gas concentrations in our simulations were the same as those of the GCMs: the IPCC 20th century time series for 1968-1999 and the A2 time series for simulations of the future. We demonstrate that RegCM3 is capable of producing present day annual and seasonal climatologies of air temperature and precipitation that are in good agreement with observations. Important features of the high-resolution climatology of temperature, precipitation, snow water equivalent (SWE), and soil moisture are consistently reproduced in all model runs over WNA and ENA. The simulations provide a potential range of future climate change for selected decades and display common patterns of the direction and magnitude of changes. As expected, there are some model to model differences that limit interpretability and give rise to uncertainties. Here, we provide background information about the GCMs and the RegCM3, a basic evaluation of the model output and examples of simulated future climate. We also provide information needed to access the web applications for visualizing and downloading the data, and give complete metadata that describe the variables in the datasets.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.3243S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.3243S"><span>Climate and marine biogeochemistry during the Holocene from transient model 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>Segschneider, Joachim; Schneider, Birgit; Khon, Vyacheslav</p> <p>2018-06-01</p> <p>Climate and marine biogeochemistry changes over the Holocene are investigated based on transient global climate and biogeochemistry model simulations over the last 9500 years. The simulations are forced by accelerated and non-accelerated orbital parameters, respectively, and atmospheric pCO2, CH4, and N2O. The analysis focusses on key climatic parameters of relevance to the marine biogeochemistry, and on the physical and biogeochemical processes that drive atmosphere-ocean carbon fluxes and changes in the oxygen minimum zones (OMZs). The simulated global mean ocean temperature is characterized by a mid-Holocene cooling and a late Holocene warming, a common feature among Holocene climate simulations which, however, contradicts a proxy-derived mid-Holocene climate optimum. As the most significant result, and only in the non-accelerated simulation, we find a substantial increase in volume of the OMZ in the eastern equatorial Pacific (EEP) continuing into the late Holocene. The concurrent increase in apparent oxygen utilization (AOU) and age of the water mass within the EEP OMZ can be attributed to a weakening of the deep northward inflow into the Pacific. This results in a large-scale mid-to-late Holocene increase in AOU in most of the Pacific and hence the source regions of the EEP OMZ waters. The simulated expansion of the EEP OMZ raises the question of whether the deoxygenation that has been observed over the last 5 decades could be a - perhaps accelerated - continuation of an orbitally driven decline in oxygen. Changes in global mean biological production and export of detritus remain of the order of 10 %, with generally lower values in the mid-Holocene. The simulated atmosphere-ocean CO2 flux would result in atmospheric pCO2 changes of similar magnitudes to those observed for the Holocene, but with different timing. More technically, as the increase in EEP OMZ volume can only be simulated with the non-accelerated model simulation, non-accelerated model simulations are required for an analysis of the marine biogeochemistry in the Holocene. Notably, the long control experiment also displays similar magnitude variability to the transient experiment for some parameters. This indicates that also long control runs are required when investigating Holocene climate and marine biogeochemistry, and that some of the Holocene variations could be attributed to internal variability of the atmosphere-ocean system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1713823V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1713823V"><span>Latest research related to climate change analysis with applications in impact studies over the territory of Serbia</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>Vukovic, Ana; Vujadinovic, Mirjam; Djurdjevic, Vladimir; Cvetkovic, Bojan; Djordjevic, Marija; Ruml, Mirjana; Rankovic-Vasic, Zorica; Przic, Zoran; Stojicic, Djurdja; Krzic, Aleksandra; Rajkovic, Borivoj</p> <p>2015-04-01</p> <p>Serbia is a country with relatively small scale terrain features with economy mostly based on local landowners' agricultural production. Climate change analysis must be downscaled accordingly, to recognize climatological features of the farmlands. Climate model simulations and impact studies significantly contribute to the future strategic planning in economic development and therefore impact analysis must be approached with high level of confidence. This paper includes research related to climate change and impacts in Serbia resulted from cooperative work of the modeling and user community. Dynamical downscaling of climate projections for the 21st century with multi-model approach and statistical bias correction are done in order to prepare model results for impact studies. Presented results are from simulations performed using regional EBU-POM model, which is forced with A1B and A2 SRES/IPCC (2007) with comparative analysis with other regional models and from the latest high resolution NMMB simulations forced with RCP8.5 IPCC scenario (2012). Application of bias correction of the model results is necessary when calculated indices are not linearly dependent on the model results and delta approach in presenting results with respect to present climate simulations is insufficient. This is most important during the summer over the north part of the country where model bias produce much higher temperatures and less precipitation, which is known as "summer drying problem" and is common in regional models' simulations over the Pannonian valley. Some of the results, which are already observed in present climate, like higher temperatures and disturbance in the precipitation pattern, lead to present and future advancement of the start of the vegetation period toward earlier dates, associated with an increased risk of the late spring frost, extended vegetation period, disturbed preparation for the rest period, increased duration and frequency of the draught periods, etc. Based on the projected climate changes an application is proposed of the ensemble seasonal forecasts for early preparation in case of upcoming unfavorable weather conditions. This paper was realized as a part of the projects "Studying climate change and its influence on the environment: impacts, adaptation and mitigation" (43007) and "Assessment of climate change impacts on water resources in Serbia" (37005) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011-2015.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/18757275','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/18757275"><span>Global and Arctic climate engineering: numerical model studies.</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>Caldeira, Ken; Wood, Lowell</p> <p>2008-11-13</p> <p>We perform numerical simulations of the atmosphere, sea ice and upper ocean to examine possible effects of diminishing incoming solar radiation, insolation, on the climate system. We simulate both global and Arctic climate engineering in idealized scenarios in which insolation is diminished above the top of the atmosphere. We consider the Arctic scenarios because climate change is manifesting most strongly there. Our results indicate that, while such simple insolation modulation is unlikely to perfectly reverse the effects of greenhouse gas warming, over a broad range of measures considering both temperature and water, an engineered high CO2 climate can be made much more similar to the low CO2 climate than would be a high CO2 climate in the absence of such engineering. At high latitudes, there is less sunlight deflected per unit albedo change but climate system feedbacks operate more powerfully there. These two effects largely cancel each other, making the global mean temperature response per unit top-of-atmosphere albedo change relatively insensitive to latitude. Implementing insolation modulation appears to be feasible.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMPA13B..06W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMPA13B..06W"><span>Climate Change Resilience Planning at the Department of Energy's Savannah River Site</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.; Johnson, A.</p> <p>2015-12-01</p> <p>The Savannah River National Laboratory (SRNL) is developing a site sustainability plan for the Department of Energy's Savannah River Site (SRS) in South Carolina in accordance with Executive Order 13693, which charges each DOE agency with "identifying and addressing projected impacts of climate change" and "calculating the potential cost and risk to mission associated with agency operations". The plan will comprise i) projections of climate change, ii) surveys of site managers to estimate the effects of climate change on site operations, and iii) a determination of adaptive actions. Climate change projections for SRS are obtained from multiple sources, including an online repository of downscaled global climate model (GCM) simulations of future climate and downscaled GCM simulations produced at SRNL. Taken together, we have projected data for temperature, precipitation, humidity, and wind - all variables with a strong influence on site operations. SRNL is working to engage site facility managers and facilitate a "bottom up" approach to climate change resilience planning, where the needs and priorities of stakeholders are addressed throughout the process. We make use of the Vulnerability Assessment Scoring Tool, an Excel-based program designed to accept as input various climate scenarios ('exposure'), the susceptibility of assets to climate change ('sensitivity'), and the ability of these assets to cope with climate change ('adaptive capacity'). These are combined to produce a series of scores that highlight vulnerabilities. Working with site managers, we have selected the most important assets, estimated their expected response to climate change, and prepared a report highlighting the most endangered facilities. Primary risks include increased energy consumption, decreased water availability, increased forest fire danger, natural resource degradation, and compromised outdoor worker safety in a warmer and more humid climate. Results of this study will aid in driving future management decisions and promoting sustainable practices at SRS.</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.ncbi.nlm.nih.gov/pubmed/29628526','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29628526"><span>The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes.</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>Thom, Dominik; Rammer, Werner; Seidl, Rupert</p> <p>2017-11-01</p> <p>Currently, the temperate forest biome cools the earth's climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (-10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JESS..127...37W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JESS..127...37W"><span>Assessing the response of runoff to climate change and human activities for a typical basin in the Northern Taihang Mountain, 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>Wang, Jinfeng; Gao, Yanchuan; Wang, Sheng</p> <p>2018-04-01</p> <p>Climate change and human activities are the two main factors on runoff change. Quantifying the contribution of climate change and human activities on runoff change is important for water resources planning and management. In this study, the variation trend and abrupt change point of hydro-meteorological factors during 1960-2012 were detected by using the Mann-Kendall test and Pettitt change-point statistics. Then the runoff was simulated by SWAT model. The contribution of climate change and human activities on runoff change was calculated based on the SWAT model and the elasticity coefficient method. The results showed that in contrast to the increasing trend for annual temperature, the significant decreasing trends were detected for annual runoff and precipitation, with an abrupt change point in 1982. The simulated results of SWAT had good consistency with observed ones, and the values of R2 and E_{NS} all exceeded 0.75. The two methods used for assessing the contribution of climate change and human activities on runoff reduction yielded consistent results. The contribution of climate change (precipitation reduction and temperature rise) was {˜ }37.5%, while the contribution of human activities (the increase of economic forest and built-up land, hydrologic projects) was {˜ }62.5%.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23787302','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23787302"><span>Impact of urban WWTP and CSO fluxes on river peak flow extremes under current and future climate conditions.</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>Keupers, Ingrid; Willems, Patrick</p> <p>2013-01-01</p> <p>The impact of urban water fluxes on the river system outflow of the Grote Nete catchment (Belgium) was studied. First the impact of the Waste Water Treatment Plant (WWTP) and the Combined Sewer Overflow (CSO) outflows on the river system for the current climatic conditions was determined by simulating the urban fluxes as point sources in a detailed, hydrodynamic river model. Comparison was made of the simulation results on peak flow extremes with and without the urban point sources. In a second step, the impact of climate change scenarios on the urban fluxes and the consequent impacts on the river flow extremes were studied. It is shown that the change in the 10-year return period hourly peak flow discharge due to climate change (-14% to +45%) was in the same order of magnitude as the change due to the urban fluxes (+5%) in current climate conditions. Different climate change scenarios do not change the impact of the urban fluxes much except for the climate scenario that involves a strong increase in rainfall extremes in summer. This scenario leads to a strong increase of the impact of the urban fluxes on the river system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/33551','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/33551"><span>Streamflow response to climate and landuse changes in a coastal watershed in North Carolina</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>S. Qi; G. Sun; Y. Wang; S.G. McNulty; J.A. Moore Myers</p> <p>2009-01-01</p> <p>It is essential to examine the sensitivity of hydrologic responses to climate and landuse change across different physiographic regions in order to formulate sound water management policies for local response to projected global change. This study used the a simulation model to examine the potential impacts of climate and landuse changes on streamflow of the...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26482823','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26482823"><span>Climate-driven changes to the spatio-temporal distribution of the parasitic nematode, Haemonchus contortus, in sheep 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>Rose, Hannah; Caminade, Cyril; Bolajoko, Muhammad Bashir; Phelan, Paul; van Dijk, Jan; Baylis, Matthew; Williams, Diana; Morgan, Eric R</p> <p>2016-03-01</p> <p>Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio-temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q0 , adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan-European spatio-temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q0 simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within-host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q0 simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2-3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations. © 2015 John Wiley & Sons Ltd.</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://pubs.er.usgs.gov/publication/70101005','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70101005"><span>An integrated land change model for projecting future climate and land change scenarios</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>Wimberly, Michael; Sohl, Terry L.; Lamsal, Aashis; Liu, Zhihua; Hawbaker, Todd J.</p> <p>2013-01-01</p> <p>Climate change will have myriad effects on ecosystems worldwide, and natural and anthropogenic disturbances will be key drivers of these dynamics. In addition to climatic effects, continual expansion of human settlement into fire-prone forests will alter fire regimes, increase human vulnerability, and constrain future forest management options. There is a need for modeling tools to support the simulation and assessment of new management strategies over large regions in the context of changing climate, shifting development patterns, and an expanding wildland-urban interface. To address this need, we developed a prototype land change simulator that combines human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and incorporates novel feedbacks between human land use and disturbance regimes. The prototype model was implemented in a test region encompassing the Denver metropolitan area along with its surrounding forested and agricultural landscapes. Initial results document the feasibility of integrated land change modeling at a regional scale but also highlighted conceptual and technical challenges for this type of model integration. Ongoing development will focus on improving climate sensitivities and modeling constraints imposed by climate change and human population growth on forest management activities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1113664W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1113664W"><span>Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily 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>Williams, C. J. R.; Kniveton, D. R.; Layberry, R.</p> <p>2009-04-01</p> <p>It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.</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.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('http://adsabs.harvard.edu/abs/2017EGUGA..1914354T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1914354T"><span>CMIP5-downscaled projections for the NW European Shelf Seas: initial results and insights into uncertainties</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>Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom</p> <p>2017-04-01</p> <p>The North Sea, and wider Northwest European Shelf seas (NWS) are economically, environmentally, and culturally important for a number of European countries. They are protected by European legislation, often with specific reference to the potential impacts of climate change. Coastal climate change projections are an important source of information for effective management of European Shelf Seas. For example, potential changes in the marine environment are a key component of the climate change risk assessments (CCRAs) carried out under the UK Climate Change Act We use the NEMO shelf seas model combined with CMIP5 climate model and EURO-CORDEX regional atmospheric model data to generate new simulations of the NWS. Building on previous work using a climate model perturbed physics ensemble and the POLCOMS, this new model setup is used to provide first indication of the uncertainties associated with: (i) the driving climate model; (ii) the atmospheric downscaling model (iii) the shelf seas downscaling model; (iv) the choice of climate change scenario. Our analysis considers a range of physical marine impacts and the drivers of coastal variability and change, including sea level and the propagation of open ocean signals onto the shelf. The simulations are being carried out as part of the UK Climate Projections 2018 (UKCP18) and will feed into the following UK CCRA.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24748331','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24748331"><span>Sensitivity of global and regional terrestrial carbon storage to the direct CO2 effect and climate change based on the CMIP5 model intercomparison.</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, Jing; Dan, Li; Huang, Mei</p> <p>2014-01-01</p> <p>Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04 PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3991598','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3991598"><span>Sensitivity of Global and Regional Terrestrial Carbon Storage to the Direct CO2 Effect and Climate Change Based on the CMIP5 Model Intercomparison</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>Peng, Jing; Dan, Li; Huang, Mei</p> <p>2014-01-01</p> <p>Global and regional land carbon storage has been significantly affected by increasing atmospheric CO2 concentration and climate change. Based on fully coupled climate-carbon-cycle simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), we investigate sensitivities of land carbon storage to rising atmospheric CO2 concentration and climate change over the world and 21 regions during the 130 years. Overall, the simulations suggest that consistently spatial positive effects of the increasing CO2 concentrations on land carbon storage are expressed with a multi-model averaged value of 1.04PgC per ppm. The stronger positive values are mainly located in the broad areas of temperate and tropical forest, especially in Amazon basin and western Africa. However, large heterogeneity distributed for sensitivities of land carbon storage to climate change. Climate change causes decrease in land carbon storage in most tropics and the Southern Hemisphere. In these regions, decrease in soil moisture (MRSO) and enhanced drought somewhat contribute to such a decrease accompanied with rising temperature. Conversely, an increase in land carbon storage has been observed in high latitude and altitude regions (e.g., northern Asia and Tibet). The model simulations also suggest that global negative impacts of climate change on land carbon storage are predominantly attributed to decrease in land carbon storage in tropics. Although current warming can lead to an increase in land storage of high latitudes of Northern Hemisphere due to elevated vegetation growth, a risk of exacerbated future climate change may be induced due to release of carbon from tropics. PMID:24748331</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28207766','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28207766"><span>Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems.</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>Templer, Pamela H; Reinmann, Andrew B; Sanders-DeMott, Rebecca; Sorensen, Patrick O; Juice, Stephanie M; Bowles, Francis; Sofen, Laura E; Harrison, Jamie L; Halm, Ian; Rustad, Lindsey; Martin, Mary E; Grant, Nicholas</p> <p>2017-01-01</p> <p>Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5313155','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5313155"><span>Climate Change Across Seasons Experiment (CCASE): A new method for simulating future climate in seasonally snow-covered ecosystems</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>Templer, Pamela H.; Reinmann, Andrew B.; Sanders-DeMott, Rebecca; Sorensen, Patrick O.; Juice, Stephanie M.; Bowles, Francis; Sofen, Laura E.; Harrison, Jamie L.; Halm, Ian; Rustad, Lindsey; Martin, Mary E.; Grant, Nicholas</p> <p>2017-01-01</p> <p>Climate models project an increase in mean annual air temperatures and a reduction in the depth and duration of winter snowpack for many mid and high latitude and high elevation seasonally snow-covered ecosystems over the next century. The combined effects of these changes in climate will lead to warmer soils in the growing season and increased frequency of soil freeze-thaw cycles (FTCs) in winter due to the loss of a continuous, insulating snowpack. Previous experiments have warmed soils or removed snow via shoveling or with shelters to mimic projected declines in the winter snowpack. To our knowledge, no experiment has examined the interactive effects of declining snowpack and increased frequency of soil FTCs, combined with soil warming in the snow-free season on terrestrial ecosystems. In addition, none have mimicked directly the projected increase in soil FTC frequency in tall statured forests that is expected as a result of a loss of insulating snow in winter. We established the Climate Change Across Seasons Experiment (CCASE) at Hubbard Brook Experimental Forest in the White Mountains of New Hampshire in 2012 to assess the combined effects of these changes in climate on a variety of pedoclimate conditions, biogeochemical processes, and ecology of northern hardwood forests. This paper demonstrates the feasibility of creating soil FTC events in a tall statured ecosystem in winter to simulate the projected increase in soil FTC frequency over the next century and combines this projected change in winter climate with ecosystem warming throughout the snow-free season. Together, this experiment provides a new and more comprehensive approach for climate change experiments that can be adopted in other seasonally snow-covered ecosystems to simulate expected changes resulting from global air temperature rise. PMID:28207766</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/6043439-simulation-growth-adirondack-conifers-relation-global-climate-change','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/6043439-simulation-growth-adirondack-conifers-relation-global-climate-change"><span>Simulation of growth of Adirondack conifers in relation to global climate change</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>Pan, Y.; Raynal, D.J.</p> <p>1993-06-01</p> <p>Several conifer species grown in plantations in the southeastern Adirondack mountains of New York were chosen to model tree growth. In the models, annual xylem growth was decomposed into several components that reflect various intrinsic or extrinsic factors. Growth signals indicative of climatic effects were used to construct response functions using both multivariate analysis and Kalman filter methods. Two models were used to simulate tree growth response to future CO[sub 2]-induced climate change projected by GCMs. The comparable results of both models indicate that different conifer species have individualistic growth responses to future climatic change. The response behaviors of treesmore » are affected greatly by local stand conditions. The results suggest possible changes in future growth and distributions of naturally occurring conifers in this region.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1347844-cross-scale-intercomparison-climate-change-impacts-simulated-regional-global-hydrological-models-eleven-large-river-basins','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1347844-cross-scale-intercomparison-climate-change-impacts-simulated-regional-global-hydrological-models-eleven-large-river-basins"><span>Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins</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>Hattermann, F. F.; Krysanova, V.; Gosling, S. N.</p> <p></p> <p>Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC23B0916D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC23B0916D"><span>Characterizing Vegetation Model Skill and Uncertainty in Simulated Ecosystem Response to Climate Change 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>Drapek, R. J.; Kim, J. B.</p> <p>2013-12-01</p> <p>We simulated ecosystem response to climate change in the USA and Canada at a 5 arc-minute grid resolution using the MC1 dynamic global vegetation model and nine CMIP3 future climate projections as input. The climate projections were produced by 3 GCMs simulating 3 SRES emissions scenarios. We examined MC1 outputs for the conterminous USA by summarizing them by EPA level II and III ecoregions to characterize model skill and evaluate the magnitude and uncertainties of simulated ecosystem response to climate change. First, we evaluated model skill by comparing outputs from the recent historical period with benchmark datasets. Distribution of potential natural vegetation simulated by MC1 was compared with Kuchler's map. Above ground live carbon simulated by MC1 was compared with the National Biomass and Carbon Dataset. Fire return intervals calculated by MC1 were compared with maximum and minimum values compiled for the United States. Each EPA Level III Ecoregion was scored for average agreement with corresponding benchmark data and an average score was calculated for all three types of output. Greatest agreement with benchmark data happened in the Western Cordillera, the Ozark / Ouachita-Appalachian Forests, and the Southeastern USA Plains (EPA Level II Ecoregions). The lowest agreement happened in the Everglades and the Tamaulipas-Texas Semiarid Plain. For simulated ecosystem response to future climate projections we examined MC1 output for shifts in vegetation type, vegetation carbon, runoff, and biomass consumed by fire. Each ecoregion was scored for the amount of change from historical conditions for each variable and an average score was calculated. Smallest changes were forecast for Western Cordillera and Marine West Coast Forest ecosystems. Largest changes were forecast for the Cold Deserts, the Mixed Wood Plains, and the Central USA Plains. By combining scores of model skill for the historical period for each EPA Level 3 Ecoregion with scores representing the magnitude of ecosystem changes in the future, we identified high and low uncertainty ecoregions. The largest anticipated changes and the lowest measures of model skill coincide in the Central USA Plains and the Mixed Wood Plains. The combination of low model skill and high degree of ecosystem change elevate the importance of our uncertainty in this ecoregion. The highest projected changes coincide with relatively high model skill in the Cold Deserts. Climate adaptation efforts are the most likely to pay off in these regions. Finally, highest model skill and lowest anticipated changes coincide in the Western Cordillera and the Marine West Coast Forests. These regions may be relatively low-risk for climate change impacts when compared to the other ecoregions. These results represent only the first step in this type of analysis; there exist many ways to strengthen it. One, MC1 calibrations can be optimized using a structured optimization technique. Two, a larger set of climate projections can be used to capture a fuller range of GCMs and emissions scenarios. And three, employing an ensemble of vegetation models would make the analysis more robust.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.3766O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.3766O"><span>Climate impacts on palm oil yields in the Nigerian Niger Delta</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>Okoro, Stanley U.; Schickhoff, Udo; Boehner, Juergen; Schneider, Uwe A.; Huth, Neil</p> <p>2016-04-01</p> <p>Palm oil production has increased in recent decades and is estimated to increase further. The optimal role of palm oil production, however, is controversial because of resource conflicts with alternative land uses. Local conditions and climate change affect resource competition and the desirability of palm oil production. Based on this, crop yield simulations using different climate model output under different climate scenarios could be important tool in addressing the problem of uncertainty quantification among different climate model outputs. Previous studies on this region have focused mostly on single experimental fields, not considering variations in Agro-Ecological Zones, climatic conditions, varieties and management practices and, in most cases not extending to various IPCC climate scenarios and were mostly based on single climate model output. Furthermore, the uncertainty quantification of the climate- impact model has rarely been investigated on this region. To this end we use the biophysical simulation model APSIM (Agricultural Production Systems Simulator) to simulate the regional climate impact on oil palm yield over the Nigerian Niger Delta. We also examine whether the use of crop yield model output ensemble reduces the uncertainty rather than the use of climate model output ensemble. The results could serve as a baseline for policy makers in this region in understanding the interaction between potentials of energy crop production of the region as well as its food security and other negative feedbacks that could be associated with bioenergy from oil palm. Keywords: Climate Change, Climate impacts, Land use and Crop yields.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy...49.1547S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy...49.1547S"><span>High resolution projections for the western Iberian coastal low level jet in 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>Soares, Pedro M. M.; Lima, Daniela C. A.; Cardoso, Rita M.; Semedo, Alvaro</p> <p>2017-09-01</p> <p>The Iberian coastal low-level jet (CLLJ) is one of the less studied boundary layer wind jet features in the Eastern Boundary Currents Systems (EBCS). These regions are amongst the most productive ocean ecosystems, where the atmosphere-land-ocean feedbacks, which include marine boundary layer clouds, coastal jets, upwelling and inland soil temperature and moisture, play an important role in defining the regional climate along the sub-tropical mid-latitude western coastal areas. Recently, the present climate western Iberian CLLJ properties were extensively described using a high resolution regional climate hindcast simulation. A summer maximum frequency of occurrence above 30 % was found, with mean maximum wind speeds around 15 ms-1, between 300 and 400 m heights (at the jet core). Since the 1990s the climate change impact on the EBCS is being studied, nevertheless some lack of consensus still persists regarding the evolution of upwelling and other components of the climate system in these areas. However, recently some authors have shown that changes are to be expected concerning the timing, intensity and spatial homogeneity of coastal upwelling, in response to future warming, especially at higher latitudes, namely in Iberia and Canaries. In this study, the first climate change assessment study regarding the Western Iberian CLLJ, using a high resolution (9 km) regional climate simulation, is presented. The properties of this CLLJ are studied and compared using two 30 years simulations: one historical simulation for the 1971-2000 period, and another simulation for future climate, in agreement with the RCP8.5 scenario, for the 2071-2100 period. Robust and consistent changes are found: (1) the hourly frequency of occurrence of the CLLJ is expected to increase in summer along the western Iberian coast, from mean maximum values of around 35 % to approximately 50 %; (2) the relative increase of the CLLJ frequency of occurrence is higher in the north off western Iberia; (3) the occurrence of the CLLJ covers larger areas both latitudinal and longitudinal; (4) the CLLJ season is lengthened extending to May and September; and, (5) there are shifts for higher occurrences of higher wind speeds and for the jet core to occur at higher heights.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009GMS...186..273M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009GMS...186..273M"><span>Global warming and climate change in Amazonia: Climate-vegetation feedback and impacts on water resources</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>Marengo, José; Nobre, Carlos A.; Betts, Richard A.; Cox, Peter M.; Sampaio, Gilvan; Salazar, Luis</p> <p></p> <p>This chapter constitutes an updated review of long-term climate variability and change in the Amazon region, based on observational data spanning more than 50 years of records and on climate-change modeling studies. We start with the early experiments on Amazon deforestation in the late 1970s, and the evolution of these experiments to the latest studies on greenhouse gases emission scenarios and land use changes until the end of the twenty-first century. The "Amazon dieback" simulated by the HadCM3 model occurs after a "tipping point" of CO2 concentration and warming. Experiments on Amazon deforestation and change of climate suggest that once a critical deforestation threshold (or tipping point) of 40-50% forest loss is reached in eastern Amazonia, climate would change in a way which is dangerous for the remaining forest. This may favor a collapse of the tropical forest, with a substitution of the forest by savanna-type vegetation. The concept of "dangerous climate change," as a climate change, which induces positive feedback, which accelerate the change, is strongly linked to the occurrence of tipping points, and it can be explained as the presence of feedback between climate change and the carbon cycle, particularly involving a weakening of the current terrestrial carbon sink and a possible reversal from a sink (as in present climate) to a source by the year 2050. We must, therefore, currently consider the drying simulated by the Hadley Centre model(s) as having a finite probability under global warming, with a potentially enormous impact, but with some degree of uncertainty.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC33A1095D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC33A1095D"><span>Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic 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>Dubrovsky, M.; Trnka, M.; Skalak, P.</p> <p>2013-12-01</p> <p>The regional-scale simulations of weather-sensitive processes (e.g. hydrology, agriculture and forestry) for the present and/or future climate often require high resolution meteorological inputs in terms of the time series of selected surface weather characteristics (typically temperature, precipitation, solar radiation, humidity, wind) for a set of stations or on a regular grid. As even the latest Global and Regional Climate Models (GCMs and RCMs) do not provide realistic representation of statistical structure of the surface weather, the model outputs must be postprocessed (downscaled) to achieve the desired statistical structure of the weather data before being used as an input to the follow-up simulation models. One of the downscaling approaches, which is employed also here, is based on a weather generator (WG), which is calibrated using the observed weather series, interpolated, and then modified according to the GCM- or RCM-based climate change scenarios. The present contribution, in which the parametric daily weather generator M&Rfi is linked to the high-resolution RCM output (ALADIN-Climate/CZ model) and GCM-based climate change scenarios, consists of two parts: The first part focuses on a methodology. Firstly, the gridded WG representing the baseline climate is created by merging information from observations and high resolution RCM outputs. In this procedure, WG is calibrated with RCM-simulated multi-variate weather series, and the grid specific WG parameters are then de-biased by spatially interpolated correction factors based on comparison of WG parameters calibrated with RCM-simulated weather series vs. spatially scarcer observations. To represent the future climate, the WG parameters are modified according to the 'WG-friendly' climate change scenarios. These scenarios are defined in terms of changes in WG parameters and include - apart from changes in the means - changes in WG parameters, which represent the additional characteristics of the weather series (e.g. probability of wet day occurrence and lag-1 autocorrelation of daily mean temperature). The WG-friendly scenarios for the present experiment are based on comparison of future vs baseline surface weather series simulated by GCMs from a CMIP3 database. The second part will present results of climate change impact study based on an above methodology applied to Central Europe. The changes in selected climatic (focusing on the extreme precipitation and temperature characteristics) and agroclimatic (including number of days during vegetation season with heat and drought stresses) characteristics will be analysed. In discussing the results, the emphasis will be put on 'added value' of various aspects of above methodology (e.g. inclusion of changes in 'advanced' WG parameters into the climate change scenarios). Acknowledgements: The present experiment is made within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), and VALUE (COST ES 1102 action).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A11O..02M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A11O..02M"><span>Mechanisms of elevation-dependent warming over complex terrain in high-resolution simulations 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>Minder, J. R.; Letcher, T.; Liu, C.</p> <p>2016-12-01</p> <p>Numerous observational and modeling studies have suggested that over mountainous terrain certain elevations can experience systematically enhanced rates of near-surface climate warming relative to the surrounding region, a phenomenon referred to as elevation-dependent warming (EDW). In many of these studies high-elevation locations were found to experience the fastest warming rates. A variety of physical mechanisms for EDW have been proposed but there is no consensus as to the dominant cause. We examine EDW in regional climate model (RCM) simulations with very high horizontal resolution (4-km horizontal grid). The simulation domain centers on the Rocky Mountains and intermountain west of the United States. Climate change simulations are conducted using the "pseudo global warming" framework to focus on the regional response to large-scale thermodynamic and radiative climate changes representative of mid-century anthropogenic global climate change. Substantial EDW is found in these simulations. Warming varies with elevation by up to 1°C depending on the season considered. The structure of EDW is only weakly sensitive to variations in horizontal grid spacing ranging from 4 to 36 km. The snow-albedo feedback (SAF) plays a major role in causing the simulated EDW. The elevation band of maximum warming varies seasonally, mostly following the margin of the seasonal snowpack where snow cover and albedo reductions are maximized under climate warming. Additional simulations where the SAF is artificially suppressed demonstrate that EDW variations of up to 0.6°C can be attributed to the SAF. Simulations with a suppressed SAF still exhibit EDW variations up to 0.8°C that must be explained by other mechanisms. This remaining EDW shows a near linear increase in warming with elevation in most months and does not appear to be inherited from the profile of large-scale free-tropospheric warming. Simple theoretical calculations suggest that the non-linear dependence of surface emission on temperature offers one promising mechanism. The role of water vapor and cloud feedbacks are also considered as alternative mechanisms.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817703W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817703W"><span>Detailed climate-change projections for urban land-use change and green-house gas increases for Belgium with COSMO-CLM coupled to TERRA_URB</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>Wouters, Hendrik; Vanden Broucke, Sam; van Lipzig, Nicole; Demuzere, Matthias</p> <p>2016-04-01</p> <p>Recent research clearly show that climate modelling at high resolution - which resolve the deep convection, the detailed orography and land-use including urbanization - leads to better modelling performance with respect to temperatures, the boundary-layer, clouds and precipitation. The increasing computational power enables the climate research community to address climate-change projections with higher accuracy and much more detail. In the framework of the CORDEX.be project aiming for coherent high-resolution micro-ensemble projections for Belgium employing different GCMs and RCMs, the KU Leuven contributes by means of the downscaling of EC-EARTH global climate model projections (provided by the Royal Meteorological Institute of the Netherlands) to the Belgian domain. The downscaling is obtained with regional climate simulations at 12.5km resolution over Europe (CORDEX-EU domain) and at 2.8km resolution over Belgium (CORDEX.be domain) using COSMO-CLM coupled to urban land-surface parametrization TERRA_URB. This is done for the present-day (1975-2005) and future (2040 → 2070 and 2070 → 2100). In these high-resolution runs, both GHG changes (in accordance to RCP8.5) and urban land-use changes (in accordance to a business-as-usual urban expansion scenario) are taken into account. Based on these simulations, it is shown how climate-change statistics are modified when going from coarse resolution modelling to high-resolution modelling. The climate-change statistics of particular interest are the changes in number of extreme precipitation events and extreme heat waves in cities. Hereby, it is futher investigated for the robustness of the signal change between the course and high-resolution and whether a (statistical) translation is possible. The different simulations also allow to address the relative impact and synergy between the urban expansion and increased GHG on the climate-change statistics. Hereby, it is investigated for which climate-change statistics the urban heat island and urban expansion is relevant, and to what extent the urban expansion can be included in the coarse-to-high resolution translation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=154803&keyword=510&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=154803&keyword=510&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>EXAMINING THE IMPACT OF CLIMATE CHANGE ON REGIONAL AIR QUALITY OVER THE UNITED STATES</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>This presentation summarizes recent results produced in support of the assessment of climate change impacts on ozone and particulate matter over the continental United States. Preliminary findings of climate scenario, meteorologically-drive emissions and air quality simulation a...</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('http://adsabs.harvard.edu/abs/2009EGUGA..1112317W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112317W"><span>Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily 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>Williams, C.; Kniveton, D.; Layberry, R.</p> <p>2009-04-01</p> <p>It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1910329A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1910329A"><span>Atmospheric dynamical changes as a contributor to deglacial climate variability: results from an ensemble of transient deglacial 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>Andres, Heather; Tarasov, Lev</p> <p>2017-04-01</p> <p>The atmosphere is often assumed to play a passive role in centennial- to millennial-timescale climate variations of the last deglaciation due to its short response times ( years) and the absence of abrupt changes in external climate forcings. Nevertheless, atmospheric dynamical responses to changes in ice sheet topography and albedo can affect the entire Northern Hemisphere through the altering of Rossby stationary wave patterns and changes to the North Atlantic eddy-driven jet. These responses appear sensitive to the particular configuration of Northern Hemisphere land ice, so small changes have the potential to reorganize atmospheric circulation with impacts on precipitation distributions, ocean surface currents and sea ice extent. Indirect proxy evidence, idealized theoretical studies, and "snapshot" simulations performed at different periods during the last glacial cycle indicate that between the Last Glacial Maximum and the preindustrial period the North Atlantic eddy-driven jet weakened, became less zonally-oriented, and exhibited greater variability. How the transition (or transitions) between the glacial atmospheric state and the interglacial state occurred is less clear. To address this question, we performed an ensemble of transient simulations of the last deglaciation using the Planet Simulator coupled atmosphere-ocean-vegetation-sea ice model (PlaSim, at an atmospheric resolution of T42) forced by variants of the GLAC1-D deglacial ice sheet chronology. We characterize simulated changes in stationary wave patterns over this period as well as changes in the strength and position of the North Atlantic eddy-driven jet. In particular, we document the range of timescales for these changes and compare the simulated climate signatures of these transitions to data archives of precipitation and sea ice extent.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA619998','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA619998"><span>Cryospheric Research in China</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2015-03-30</p> <p>marine monitoring for environment and security, using satellite Earth observation technologies), the WCRP/CliC Project (an international cooperative...BIOME4) to simulate the responses of biome distribution to future climate change in China. The simulation results suggest that regional climate</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70187427','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70187427"><span>Designing ecological climate change impact assessments to reflect key climatic drivers</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>Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.</p> <p>2017-01-01</p> <p>Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28173628','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28173628"><span>Designing ecological climate change impact assessments to reflect key climatic 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>Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T</p> <p>2017-07-01</p> <p>Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1212949R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1212949R"><span>Impact of global warming on tropical cyclone genesis in coupled and forced simulations: role of SST spatial anomalies</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>Royer, Jean-François; Chauvin, Fabrice; Daloz, Anne-Sophie</p> <p>2010-05-01</p> <p>The response of tropical cyclones (TC) activity to global warming has not yet reached a clear consensus in the Fourth Assessment Report (AR4) published by the Intergovernmental Panel on Climate Change (IPCC, 2007) or in the recent scientific literature. Observed series are neither long nor reliable enough for a statistically significant detection and attribution of past TC trends, and coupled climate models give widely divergent results for the future evolution of TC activity in the different ocean basins. The potential importance of the spatial structure of the future SST warming has been pointed out by Chauvin et al. (2006) in simulations performed at CNRM with the ARPEGE-Climat GCM. The current presentation describes a new set of simulations that have been performed with the ARPEGE-Climat model to try to understand the possible role of SST patterns in the TC cyclogenesis response in 15 CMIP3 coupled simulations analysed by Royer et al (2009). The new simulations have been performed with the atmospheric component of the ARPEGE-Climat GCM forced in 10 year simulations by the SST patterns from each of 15 CMIP3 simulations with different climate model at the end of the 21st century according to scenario A2. The TC analysis is based on the computation of a Convective Yearly Genesis Parameter (CYGP) and the Genesis Potential Index (GPI). The computed genesis indices for each of the ARPEGE-Climat forced simulations is compared with the indices computed directly from the initial coupled simulation. The influence of SST patterns can then be more easily assessed since all the ARPEGE-Climat simulations are performed with the same atmospheric model, whereas the original simulations used models with different parameterization and resolutions. The analysis shows that CYGP or GPI anomalies obtained with ARPEGE are as variable between each other as those obtained originally by the different IPCC models. The variety of SST patterns used to force ARPEGE explains a large part of the dispersion, though for a given SST pattern, ARPEGE does not necessarily reproduce the anomaly produced originally by the IPCC model which produced the SST anomaly. Many factors can contribute to this discrepancy, but the most prominent seems to be the absence of coupling between the forced atmospheric ARPEGE simulation and the underlying ocean. When the atmospheric model is forced by prescribed SST anomalies some retroactions between cyclogenesis and ocean are missing. There are however areas over the globe were models agree about the CYGP or GPI anomalies induced by global warming, such as the Indian Ocean that shows a better coherency in the coupled and forced responses. This could be an indication that interaction between ocean and atmosphere is not as strong there as in the other basins. Details of the results for all the other ocean basins will be presented. References: Chauvin F. and J.-F. Royer and M. Déqué , 2006: Response of hurricane-type vortices to global warming as simulated by ARPEGE-Climat at high resolution. Climate Dynamics 27(4), 377-399. IPCC [Intergovernmental Panel for Climate Change], Climate change 2007: The physical science basis, in: S. Solomon et al. (eds.), Cambridge University Press. Royer JF, F Chauvin, 2009: Response of tropical cyclogenesis to global warming in an IPCC AR-4 scenario assessed by a modified yearly genesis parameter. "Hurricanes and Climate Change", J. B. Elsner and T. H. Jagger (Eds.), Springer, ISBN: 978-0-387-09409-0, pp 213-234.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20180002900&hterms=ECS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DECS','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20180002900&hterms=ECS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DECS"><span>Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity from Observations</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>Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.</p> <p>2018-01-01</p> <p>An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2-radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GeoRL..45.1595M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GeoRL..45.1595M"><span>Internal Variability and Disequilibrium Confound Estimates of Climate Sensitivity From Observations</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>Marvel, Kate; Pincus, Robert; Schmidt, Gavin A.; Miller, Ron L.</p> <p>2018-02-01</p> <p>An emerging literature suggests that estimates of equilibrium climate sensitivity (ECS) derived from recent observations and energy balance models are biased low because models project more positive climate feedback in the far future. Here we use simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to show that across models, ECS inferred from the recent historical period (1979-2005) is indeed almost uniformly lower than that inferred from simulations subject to abrupt increases in CO2 radiative forcing. However, ECS inferred from simulations in which sea surface temperatures are prescribed according to observations is lower still. ECS inferred from simulations with prescribed sea surface temperatures is strongly linked to changes to tropical marine low clouds. However, feedbacks from these clouds are a weak constraint on long-term model ECS. One interpretation is that observations of recent climate changes constitute a poor direct proxy for long-term sensitivity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70036333','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70036333"><span>Modeling the spatial-temporal dynamics of net primary production in Yangtze River Basin using IBIS model</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>Zhang, Z.; Jiang, H.; Liu, J.; Zhu, Q.; Wei, X.; Jiang, Z.; Zhou, G.; Zhang, X.; Han, J.</p> <p>2011-01-01</p> <p>The climate change has significantly affected the carbon cycling in Yangtze River Basin. To better understand the alternation pattern for the relationship between carbon cycling and climate change, the net primary production (NPP) were simulated in the study area from 1956 to 2006 by using the Integrated Biosphere Simulator (IBIS). The results showed that the average annual NPP per square meter was about 0.518 kg C in Yangtze River Basin. The high NPP levels were mainly distributed in the southeast area of Sichuan, and the highest value reached 1.05 kg C/m2. The NPP increased based on the simulated temporal trends. The spatiotemporal variability of the NPP in the vegetation types was obvious, and it was depended on the climate and soil condition. We found the drought climate was one of critical factor that impacts the alterations of the NPP in the area by the simulation. ?? 2011 IEEE.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70031272','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70031272"><span>Forest dynamics in Oregon landscapes: Evaluation and application of an individual-based model</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>Busing, R.T.; Solomon, A.M.; McKane, R.B.; Burdick, C.A.</p> <p>2007-01-01</p> <p>The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies. ?? 2007 by the Ecological Society of America.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC31D..07T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC31D..07T"><span>Improving plot- and regional-scale crop models for simulating impacts of climate variability and 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>Tao, F.; Rötter, R.</p> <p>2013-12-01</p> <p>Many studies on global climate report that climate variability is increasing with more frequent and intense extreme events1. There are quite large uncertainties from both the plot- and regional-scale models in simulating impacts of climate variability and extremes on crop development, growth and productivity2,3. One key to reducing the uncertainties is better exploitation of experimental data to eliminate crop model deficiencies and develop better algorithms that more adequately capture the impacts of extreme events, such as high temperature and drought, on crop performance4,5. In the present study, in a first step, the inter-annual variability in wheat yield and climate from 1971 to 2012 in Finland was investigated. Using statistical approaches the impacts of climate variability and extremes on wheat growth and productivity were quantified. In a second step, a plot-scale model, WOFOST6, and a regional-scale crop model, MCWLA7, were calibrated and validated, and applied to simulate wheat growth and yield variability from 1971-2012. Next, the estimated impacts of high temperature stress, cold damage, and drought stress on crop growth and productivity based on the statistical approaches, and on crop simulation models WOFOST and MCWLA were compared. Then, the impact mechanisms of climate extremes on crop growth and productivity in the WOFOST model and MCWLA model were identified, and subsequently, the various algorithm and impact functions were fitted against the long-term crop trial data. Finally, the impact mechanisms, algorithms and functions in WOFOST model and MCWLA model were improved to better simulate the impacts of climate variability and extremes, particularly high temperature stress, cold damage and drought stress for location-specific and large area climate impact assessments. Our studies provide a good example of how to improve, in parallel, the plot- and regional-scale models for simulating impacts of climate variability and extremes, as needed for better informed decision-making on adaptation strategies. References 1. Coumou, D. & Rahmstorf, S. A decade of extremes. Nature Clim. Change, 2, 491-496 (2012). 2. Rötter, R. P., Carter, T. R., Olesen, J. E. & Porter, J. R. Crop-climate models need an overhaul. Nature Clim. Change, 1, 175-177 (2011). 3. Asseng, S. et al., Uncertainty in simulating wheat yields under climate change. Nature Clim. Change. 10.1038/nclimate1916. (2013). 4. Porter, J.R., & Semenov, M., Crop responses to climatic variation . Trans. R. Soc. B., 360, 2021-2035 (2005). 5. Porter, J.R. & Christensen, S. Deconstructing crop processes and models via identities. Plant, Cell and Environment . doi: 10.1111/pce.12107 (2013). 6. Boogaard, H.L., van Diepen C.A., Rötter R.P., Cabrera J.M. & van Laar H.H. User's guide for the WOFOST 7.1 crop growth simulation model and Control Center 1.5, Alterra, Wageningen, The Netherlands. (1998) 7. Tao, F. & Zhang, Z. Climate change, wheat productivity and water use in the North China Plain: a new super-ensemble-based probabilistic projection. Agric. Forest Meteorol., 170, 146-165. (2013).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1611327Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1611327Z"><span>Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic 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>Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick</p> <p>2014-05-01</p> <p>Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the albedo feedback dominates simulated warming in spring in all three scenarios, while in summer, evapotranspiration feedback, governing the partitioning of the return energy flux from the surface to the atmosphere into latent and sensible heat, exerts evaporative cooling effects, the magnitude of which depends on the severity of climate change, in turn driven by the underlying GHG emissions pathway, resulting in shift in the sign of net biophysical at higher levels of warming. Spatially, western Siberia is identified as the most susceptible location, experiencing the potential to reverse biophysical feedbacks in all seasons. We further analyze how the pattern of vegetation shifts triggers different signs of net effects of biophysical feedbacks.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016IJBm...60...21L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016IJBm...60...21L"><span>Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain</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>Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo</p> <p>2016-01-01</p> <p>Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3˜3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0˜19.4 %) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha-1 year-1, except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25962358','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25962358"><span>Effects of changing climate and cultivar on the phenology and yield of winter wheat in the North China Plain.</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>Li, Kenan; Yang, Xiaoguang; Tian, Hanqin; Pan, Shufen; Liu, Zhijuan; Lu, Shuo</p> <p>2016-01-01</p> <p>Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4%) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (-3.3 to -54.8 kg ha(-1) year(-1), except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AGUFM.A33A0242G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AGUFM.A33A0242G"><span>The North American Regional Climate Change Assessment Program (NARCCAP): Status and results</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>Gutowski, W. J.</p> <p>2009-12-01</p> <p>NARCCAP is a multi-institutional program that is investigating systematically the uncertainties in regional scale simulations of contemporary climate and projections of future climate. NARCCAP is supported by multiple federal agencies. NARCCAP is producing an ensemble of high-resolution climate-change scenarios by nesting multiple RCMs in reanalyses and multiple atmosphere-ocean GCM simulations of contemporary and future-scenario climates. The RCM domains cover the contiguous U.S., northern Mexico, and most of Canada. The simulation suite also includes time-slice, high resolution GCMs that use sea-surface temperatures from parent atmosphere-ocean GCMs. The baseline resolution of the RCMs and time-slice GCMs is 50 km. Simulations use three sources of boundary conditions: National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) AMIP-II Reanalysis, GCMs simulating contemporary climate and GCMs using the A2 SRES emission scenario for the twenty-first century. Simulations cover 1979-2004 and 2038-2060, with the first 3 years discarded for spin-up. The resulting RCM and time-slice simulations offer opportunity for extensive analysis of RCM simulations as well as a basis for multiple high-resolution climate scenarios for climate change impacts assessments. Geophysical statisticians are developing measures of uncertainty from the ensemble. To enable very high-resolution simulations of specific regions, both RCM and high-resolution time-slice simulations are saving output needed for further downscaling. All output is publically available to the climate analysis and the climate impacts assessment community, through an archiving and data-distribution plan. Some initial results show that the models closely reproduce ENSO-related precipitation variations in coastal California, where the correlation between the simulated and observed monthly time series exceeds 0.94 for all models. The strong El Nino events of 1982-83 and 1997-98 are well reproduced for the Pacific coastal region of the U.S. in all models. ENSO signals are less well reproduced in other regions. The models also produce well extreme monthly precipitation in coastal California and the Upper Midwest. Model performance tends to deteriorate from west to east across the domain, or roughly from the inflow boundary toward the outflow boundary. This deterioration with distance from the inflow boundary is ameliorated to some extent in models formulated such that large-scale information is included in the model solution, whether implemented by spectral nudging or by use of a perturbation form of the governing equations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A23D2380K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A23D2380K"><span>Future projections of total snowfall and heavy snowfall in Japan simulated by large ensemble 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>Kawase, H.; Sasaki, H.; Murata, A.; Nosaka, M.; Ito, R.; Dairaku, K.; Sasai, T.; Yamazaki, T.; Sugimoto, S.; Watanabe, S.; Fujita, M.; Kawazoe, S.; Okada, Y.; Ishii, M.; Mizuta, R.; Takayabu, I.</p> <p>2017-12-01</p> <p>We performed large ensemble climate experiments to investigate future changes in extreme weather events using Meteorological Research Institute-Atmospheric General Circulation Model (MRI-AGCM) with about 60 km grid spacing and Non-Hydrostatic Regional Climate Model with 20 km grid spacing (NHRCM20). The global climate simulations are prescribed by the past and future sea surface temperature (SST). Two future climate simulations are conducted so that the global-mean surface air temperature rise 2 K and 4 K from the pre-industrial period. The non-warming simulations are also conducted by MRI-AGCM and NHRCM20. We focus on the future changes in snowfall in Japan. In winter, the Sea of Japan coast experiences heavy snowfall due to East Asian winter monsoon. The cold and dry air from the continent obtains abundant moisture from the warm Sea of Japan, causing enormous amount of snowfall especially in the mountainous area. The NHRCM20 showed winter total snowfall decreases in the most parts of Japan. In contrast, extremely heavy daily snowfall could increase at mountainous areas in the Central Japan and Northern parts of Japan when strong cold air outbreak occurs and the convergence zone appears over the Sea of Japan. The warmer Sea of Japan in the future climate could supply more moisture than that in the present climate, indicating that the cumulus convections could be enhanced around the convergence zone in the Sea of Japan. However, the horizontal resolution of 20 km is not enough to resolve Japan`s complex topography. Therefore, dynamical downscaling with 5 km grid spacing (NHRCM05) is also conducted using NHRCM20. The NHRCM05 does a better job simulating the regional boundary of snowfall and shows more detailed changes in future snowfall characteristics. The future changes in total and extremely heavy snowfall depend on the regions, elevations, and synoptic conditions around Japan.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22633462','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22633462"><span>Regional projections of North Indian climate for adaptation studies.</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>Mathison, Camilla; Wiltshire, Andrew; Dimri, A P; Falloon, Pete; Jacob, Daniela; Kumar, Pankaj; Moors, Eddy; Ridley, Jeff; Siderius, Christian; Stoffel, Markus; Yasunari, T</p> <p>2013-12-01</p> <p>Adaptation is increasingly important for regions around the world where large changes in climate could have an impact on populations and industry. The Brahmaputra-Ganges catchments have a large population, a main industry of agriculture and a growing hydro-power industry, making the region susceptible to changes in the Indian Summer Monsoon, annually the main water source. The HighNoon project has completed four regional climate model simulations for India and the Himalaya at high resolution (25km) from 1960 to 2100 to provide an ensemble of simulations for the region. In this paper we have assessed the ensemble for these catchments, comparing the simulations with observations, to give credence that the simulations provide a realistic representation of atmospheric processes and therefore future climate. We have illustrated how these simulations could be used to provide information on potential future climate impacts and therefore aid decision-making using climatology and threshold analysis. The ensemble analysis shows an increase in temperature between the baseline (1970-2000) and the 2050s (2040-2070) of between 2 and 4°C and an increase in the number of days with maximum temperatures above 28°C and 35°C. There is less certainty for precipitation and runoff which show considerable variability, even in this relatively small ensemble, spanning zero. The HighNoon ensemble is the most complete data for the region providing useful information on a wide range of variables for the regional climate of the Brahmaputra-Ganges region, however there are processes not yet included in the models that could have an impact on the simulations of future climate. We have discussed these processes and show that the range from the HighNoon ensemble is similar in magnitude to potential changes in projections where these processes are included. Therefore strategies for adaptation must be robust and flexible allowing for advances in the science and natural environmental changes. Copyright © 2012 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70191918','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70191918"><span>An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California</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>Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Frid, Leonardo; Zhu, Zhiliang</p> <p>2015-01-01</p> <p>Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120016751','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120016751"><span>Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations</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>Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.</p> <p>2012-01-01</p> <p>Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A24D..07B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A24D..07B"><span>Convection-Resolving Climate Change Simulations: Intensification of Heavy Hourly Precipitation 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>Ban, N.; Schmidli, J.; Schar, C.</p> <p>2014-12-01</p> <p>Reliable climate-change projections of extreme precipitation events are of great interest to decision makers, due to potentially important hydrological impacts such as floods, land slides and debris flows. Low-resolution climate models generally project increases of heavy precipitation events with climate change, but there are large uncertainties related to the limited spatial resolution and the parameterized representation of atmospheric convection. Here we employ a convection-resolving version of the COSMO model across an extended region (1100 km x 1100 km) covering the European Alps to investigate the differences between parameterized and explicit convection in climate-change scenarios. We conduct 10-year long integrations at resolutions of 12 and 2km. Validation using ERA-Interim driven simulations reveals major improvements with the 2km resolution, in particular regarding the diurnal cycle of mean precipitation and the representation of hourly extremes. In addition, 2km simulations replicate the observed super-adiabatic scaling at precipitation stations, i.e. peak hourly events increase faster with temperature than the Clausius-Clapeyron scaling of 7%/K (see Ban et al. 2014). Convection-resolving climate change scenarios are conducted using control (1991-2000) and scenario (2081-2090) simulations driven by a CMIP5 GCM (i.e. the MPI-ESM-LR) under the IPCC RCP8.5 scenario. Comparison between 12 and 2km resolutions with parameterized and explicit convection, respectively, reveals close agreement in terms of mean summer precipitation amounts (decrease by 30%), and regarding slight increases of heavy day-long events (amounting to 15% for 90th-percentile for wet-day precipitation). However, the different resolutions yield large differences regarding extreme hourly precipitation, with the 2km version projecting substantially faster increases of heavy hourly precipitation events (about 30% increases for 90th-percentile hourly events). Ban, N., J. Schmidli and C. Schӓr (2014): Evaluation of the convection-resolving regional climate modeling approach in decade-long simulations. J. Geophys. Res. Atmos.,119, 7889-7907, doi:10.1002/2014JD021478</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/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('https://www.osti.gov/servlets/purl/1170412','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1170412"><span>Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios</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>Brunsell, Nathaniel; Mechem, David; Ma, Chunsheng</p> <p></p> <p>Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive tomore » alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=300912&keyword=mit&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=300912&keyword=mit&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>Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality</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>We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...</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('http://hdl.handle.net/2060/20150000805','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000805"><span>Development of the GEOS-5 Atmospheric General Circulation Model: Evolution from MERRA to MERRA2.</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>Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio</p> <p>2014-01-01</p> <p>The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the GEOS-5 (Goddard Earth Observing System Model - 5) Atmospheric General Circulation Model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO's MERRA2 reanalysis, the global mesoscale "nature run", the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean-atmosphere and coupled atmosphere-chemistry simulations. The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased re-evaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of "resolution aware" parameters related to the moist physics were shown to result in improvements at higher resolutions, and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..882R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..882R"><span>Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over 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>Rasmussen, K. L.; Prein, A. F.; Rasmussen, R. M.; Ikeda, K.; Liu, C.</p> <p>2017-11-01</p> <p>Novel high-resolution convection-permitting regional climate simulations over the US employing the pseudo-global warming approach are used to investigate changes in the convective population and thermodynamic environments in a future climate. Two continuous 13-year simulations were conducted using (1) ERA-Interim reanalysis and (2) ERA-Interim reanalysis plus a climate perturbation for the RCP8.5 scenario. The simulations adequately reproduce the observed precipitation diurnal cycle, indicating that they capture organized and propagating convection that most climate models cannot adequately represent. This study shows that weak to moderate convection will decrease and strong convection will increase in frequency in a future climate. Analysis of the thermodynamic environments supporting convection shows that both convective available potential energy (CAPE) and convective inhibition (CIN) increase downstream of the Rockies in a future climate. Previous studies suggest that CAPE will increase in a warming climate, however a corresponding increase in CIN acts as a balancing force to shift the convective population by suppressing weak to moderate convection and provides an environment where CAPE can build to extreme levels that may result in more frequent severe convection. An idealized investigation of fundamental changes in the thermodynamic environment was conducted by shifting a standard atmospheric profile by ± 5 °C. When temperature is increased, both CAPE and CIN increase in magnitude, while the opposite is true for decreased temperatures. Thus, even in the absence of synoptic and mesoscale variations, a warmer climate will provide more CAPE and CIN that will shift the convective population, likely impacting water and energy budgets on Earth.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=308303','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=308303"><span>Simulated impact of climate change on hydrology of multiple watersheds using traditional and recommended snowmelt runoff model methodology</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>For more than three decades, researchers have utilized the Snowmelt Runoff Model (SRM) to test the impacts of climate change on streamflow of snow-fed systems. In this study, the hydrological effects of climate change are modeled over three sequential years using SRM with both typical and recommende...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24248352','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24248352"><span>Spontaneous abrupt climate change due to an atmospheric blocking-sea-ice-ocean feedback in an unforced climate model simulation.</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>Drijfhout, Sybren; Gleeson, Emily; Dijkstra, Henk A; Livina, Valerie</p> <p>2013-12-03</p> <p>Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little Ice Age. The event was simulated in the preindustrial control run of a high-resolution climate model, without imposing external perturbations. Initial cooling started with a period of enhanced atmospheric blocking over the eastern subpolar gyre. In response, a southward progression of the sea-ice margin occurred, and the sea-level pressure anomaly was locked to the sea-ice margin through thermal forcing. The cold-core high steered more cold air to the area, reinforcing the sea-ice concentration anomaly east of Greenland. The sea-ice surplus was carried southward by ocean currents around the tip of Greenland. South of 70 °N, sea ice already started melting and the associated freshwater anomaly was carried to the Labrador Sea, shutting off deep convection. There, surface waters were exposed longer to atmospheric cooling and sea surface temperature dropped, causing an even larger thermally forced high above the Labrador Sea. In consequence, east of Greenland, anomalous winds changed from north to south, terminating the event with similar abruptness to its onset. Our results imply that only climate models that possess sufficient resolution to correctly represent atmospheric blocking, in combination with a sensitive sea-ice model, are able to simulate this kind of abrupt climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3856815','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3856815"><span>Spontaneous abrupt climate change due to an atmospheric blocking–sea-ice–ocean feedback in an unforced climate model simulation</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>Drijfhout, Sybren; Gleeson, Emily; Dijkstra, Henk A.; Livina, Valerie</p> <p>2013-01-01</p> <p>Abrupt climate change is abundant in geological records, but climate models rarely have been able to simulate such events in response to realistic forcing. Here we report on a spontaneous abrupt cooling event, lasting for more than a century, with a temperature anomaly similar to that of the Little Ice Age. The event was simulated in the preindustrial control run of a high-resolution climate model, without imposing external perturbations. Initial cooling started with a period of enhanced atmospheric blocking over the eastern subpolar gyre. In response, a southward progression of the sea-ice margin occurred, and the sea-level pressure anomaly was locked to the sea-ice margin through thermal forcing. The cold-core high steered more cold air to the area, reinforcing the sea-ice concentration anomaly east of Greenland. The sea-ice surplus was carried southward by ocean currents around the tip of Greenland. South of 70°N, sea ice already started melting and the associated freshwater anomaly was carried to the Labrador Sea, shutting off deep convection. There, surface waters were exposed longer to atmospheric cooling and sea surface temperature dropped, causing an even larger thermally forced high above the Labrador Sea. In consequence, east of Greenland, anomalous winds changed from north to south, terminating the event with similar abruptness to its onset. Our results imply that only climate models that possess sufficient resolution to correctly represent atmospheric blocking, in combination with a sensitive sea-ice model, are able to simulate this kind of abrupt climate change. PMID:24248352</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23557671','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23557671"><span>Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.</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>Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark</p> <p>2013-06-15</p> <p>We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. Copyright © 2013 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4878477','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4878477"><span>Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana</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>Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna</p> <p>2016-01-01</p> <p>Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27140640','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27140640"><span>Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.</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>Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna</p> <p>2016-05-17</p> <p>Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.7925O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.7925O"><span>The evolution of the Brewer-Dobson Circulation from 1960-2100 in simulations with the Chemistry Climate Model EMAC</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>Oberländer, Sophie; Langematz, Ulrike; Kubin, Anne; Abalichin, Janna; Meul, Stefanie; Jöckel, Patrick; Brühl, Christoph</p> <p>2010-05-01</p> <p>First results of research performed within the new DFG Research Unit Stratospheric Change and its Role for Climate Prediction (SHARP) will be presented. SHARP investigates past and future changes in stratospheric dynamics and composition to improve the understanding of global climate change and the accuracy of climate change predictions. SHARP combines the efforts of eight German research institutes and expertise in state-of-the-art climate modelling and observations. Within the scope of the scientific sub-project SHARP-BDC (Brewer-Dobson-Circulation) the past and future evolution of the BDC in an atmosphere with changing composition will be analysed. Radiosonde data show an annual mean cooling of the tropical lower stratosphere over the past few decades (Thompson and Solomon, 2005). Several independent model simulations indicate an acceleration of the BDC due to higher greenhouse gas (GHG) concentrations with direct impact on the exchange of air masses between the troposphere and stratosphere (e.g., Butchart et al, 2006). In contrast, from balloon-born measurements no significant acceleration in the BDC could be identified (Engel et al, 2008). This disagreement between observations and model analyses motivates further studies. For the future, expected changes in planetary wave generation and propagation in an atmosphere with increasing GHG concentrations are a major source of uncertainty for predicting future levels of stratospheric composition. To analyse and interpret the past and future evolution of the BDC, results from a transient multi-decadal simulation with the Chemistry-Climate Model (CCM) EMAC will be presented. The model has been integrated from 1960 to 2100 following the SCN2d scenario recommendations of the SPARC CCMVal initiative for the temporal evolution of GHGs, ozone depleting substances and sea surface temperatures as well as sea ice. The role of increasing GHG concentrations for the BDC will be assessed by comparing the SCN2d-results with a ‘non-climate change' (NCC) simulation, in which greenhouse gases have been kept fixed at their 1960 concentrations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4932881','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4932881"><span>Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD</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>Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.</p> <p>2016-01-01</p> <p>Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27377537','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27377537"><span>Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.</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>Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W</p> <p>2016-07-05</p> <p>Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27713106','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27713106"><span>An Analysis of the Potential Impact of Climate Change on Dengue Transmission in the Southeastern 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>Butterworth, Melinda K; Morin, Cory W; Comrie, Andrew C</p> <p>2017-04-01</p> <p>Dengue fever, caused by a mosquito-transmitted virus, is an increasing health concern in the Americas. Meteorological variables such as temperature and precipitation can affect disease distribution and abundance through biophysical impacts on the vector and on the virus. Such tightly coupled links may facilitate further spread of dengue fever under a changing climate. In the southeastern United States, the dengue vector is widely established and exists on the current fringe of dengue transmission. We assessed projected climate change-driven shifts in dengue transmission risk in this region. We used a dynamic mosquito population and virus transmission model driven by meteorological data to simulate Aedes aegypti populations and dengue cases in 23 locations in the southeastern United States under current climate conditions and future climate projections. We compared estimates for each location with simulations based on observed data from San Juan, Puerto Rico, where dengue is endemic. Our simulations based on current climate data suggest that dengue transmission at levels similar to those in San Juan is possible at several U.S. locations during the summer months, particularly in southern Florida and Texas. Simulations that include climate change projections suggest that conditions may become suitable for virus transmission in a larger number of locations and for a longer period of time during each year. However, in contrast with San Juan, U.S. locations would not sustain year-round dengue transmission according to our model. Our findings suggest that Dengue virus (DENV) transmission is limited by low winter temperatures in the mainland United States, which are likely to prevent its permanent establishment. Although future climate conditions may increase the length of the mosquito season in many locations, projected increases in dengue transmission are limited to the southernmost locations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H42B..05G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H42B..05G"><span>Why we shouldn't underestimate the impact of plant functional diversity</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>Groner, V.; Raddatz, T.; Reick, C. H.; Claussen, M.</p> <p>2017-12-01</p> <p>We present a series of coupled land-atmosphere simulations with different combinations of plant functional types (PFTs) from mid-Holocene to preindustrial to show how plant functional diversity affects simulated climate-vegetation interaction under changing environmental conditions in subtropical Africa. Scientists nowadays agree that the establishment of the ``green'' Sahara was triggered by external changes in the Earth's orbit and amplified by internal feedback mechanisms. The timing and abruptness of the transition to the ``desert'' state are in turn still under debate. While some previous studies indicated an abrupt collapse of vegetation implying a strong climate-vegetation feedback, others suggested a gradual vegetation decline thereby questioning the existence of a strong climate-vegetation feedback. However, none of these studies explicitly accounted for the role of plant diversity. We show that the introduction or removal of a single PFT can bring about significant impacts on the simulated climate-vegetation system response to changing orbital forcing. While simulations with the standard set of PFTs show a gradual decrease of precipitation and vegetation cover over time, the reduction of plant functional diversity can cause either an abrupt decline of both variables or an even slower response to the external forcing. PFT composition seems to be the decisive factor for the system response to external forcing, and an increase in plant functional diversity does not necessarily increase the stability of the climate-vegetation system. From this we conclude that accounting for plant functional diversity in future studies - not only on palaeo climates - could significantly improve the understanding of climate-vegetation interaction in semi-arid regions, the predictability of the vegetation response to changing climate, and respectively, of the resulting feedback on precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27111095','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27111095"><span>Biological responses to environmental heterogeneity under future ocean conditions.</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>Boyd, Philip W; Cornwall, Christopher E; Davison, Andrew; Doney, Scott C; Fourquez, Marion; Hurd, Catriona L; Lima, Ivan D; McMinn, Andrew</p> <p>2016-08-01</p> <p>Organisms are projected to face unprecedented rates of change in future ocean conditions due to anthropogenic climate-change. At present, marine life encounters a wide range of environmental heterogeneity from natural fluctuations to mean climate change. Manipulation studies suggest that biota from more variable marine environments have more phenotypic plasticity to tolerate environmental heterogeneity. Here, we consider current strategies employed by a range of representative organisms across various habitats - from short-lived phytoplankton to long-lived corals - in response to environmental heterogeneity. We then discuss how, if and when organismal responses (acclimate/migrate/adapt) may be altered by shifts in the magnitude of the mean climate-change signal relative to that for natural fluctuations projected for coming decades. The findings from both novel climate-change modelling simulations and prior biological manipulation studies, in which natural fluctuations are superimposed on those of mean change, provide valuable insights into organismal responses to environmental heterogeneity. Manipulations reveal that different experimental outcomes are evident between climate-change treatments which include natural fluctuations vs. those which do not. Modelling simulations project that the magnitude of climate variability, along with mean climate change, will increase in coming decades, and hence environmental heterogeneity will increase, illustrating the need for more realistic biological manipulation experiments that include natural fluctuations. However, simulations also strongly suggest that the timescales over which the mean climate-change signature will become dominant, relative to natural fluctuations, will vary for individual properties, being most rapid for CO2 (~10 years from present day) to 4 decades for nutrients. We conclude that the strategies used by biota to respond to shifts in environmental heterogeneity may be complex, as they will have to physiologically straddle wide-ranging timescales in the alteration of ocean conditions, including the need to adapt to rapidly rising CO2 and also acclimate to environmental heterogeneity in more slowly changing properties such as warming. © 2016 John Wiley & Sons Ltd.</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.osti.gov/biblio/947036-predicting-future-threats-long-term-survival-gila-trout-using-high-resolution-simulation-climate-change','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/947036-predicting-future-threats-long-term-survival-gila-trout-using-high-resolution-simulation-climate-change"><span>Predicting future threats to the long-term survival of Gila Trout using a high-resolution simulation of climate change</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>Kennedy, Thomas L.; Gutzler, David S.; Leung, Lai R.</p> <p>2008-11-20</p> <p>Regional climates are a major factor in determining the distribution of many species. Anthropogenic inputs of greenhouse gases into the atmosphere have been predicted to cause rapid climatic changes in the next 50-100 years. Species such as the Gila Trout (Onchorhynchus gilae) that have small ranges, limited dispersal capabilities, and narrow physiological tolerances will become increasingly susceptible to extinction as their climate envelope changes. This study uses a regional climate change simulation (Leung et al. 2004) to determine changes in the climate envelope for Gila Trout, which is sensitive to maximum temperature, associated with a plausible scenario for greenhouse gasmore » increases. The model predicts approximately a 2° C increase in temperature and a doubling by the mid 21st Century in the annual number of days during which temperature exceeds 37°C, and a 25% increase in the number of days above 32°C, across the current geographical range of Gila Trout. At the same time summer rainfall decreases by more than 20%. These climate changes would reduce their available habitat by decreasing the size of their climate envelope. Warmer temperatures coupled with a decrease in summer precipitation would also tend to increase the intensity and frequency of forest fires that are a major threat to their survival. The climate envelope approach utilized here could be used to assess climate change threats to other rare species with limited ranges and dispersal capabilities.« 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_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/2013AGUFM.A41H0179S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A41H0179S"><span>The effect of future outdoor air pollution on human health and the contribution 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>Silva, R.; West, J. J.; Lamarque, J.; Shindell, D.; Collins, W.; Dalsoren, S. B.; Faluvegi, G. S.; Folberth, G.; Horowitz, L. W.; Nagashima, T.; Naik, V.; Rumbold, S.; Skeie, R.; Sudo, K.; Takemura, T.; Bergmann, D. J.; Cameron-Smith, P. J.; Cionni, I.; Doherty, R. M.; Eyring, V.; Josse, B.; MacKenzie, I. A.; Plummer, D.; Righi, M.; Stevenson, D. S.; Strode, S. A.; Szopa, S.; Zeng, G.</p> <p>2013-12-01</p> <p>At present, exposure to outdoor air pollution from ozone and fine particulate matter (PM2.5) causes over 2 million deaths per year, due to respiratory and cardiovascular diseases and lung cancer. Future ambient concentrations of ozone and PM2.5 will be affected by both air pollutant emissions and climate change. Here we estimate the potential impact of future outdoor air pollution on premature human mortality, and isolate the contribution of future climate change due to its effect on air quality. We use modeled present-day (2000) and future global ozone and PM2.5 concentrations from simulations with an ensemble of chemistry-climate models from the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Future air pollution was modeled for global greenhouse gas and air pollutant emissions in the four IPCC AR5 Representative Concentration Pathway (RCP) scenarios, for 2030, 2050 and 2100. All model outputs are regridded to a common 0.5°x0.5° horizontal resolution. Future premature mortality is estimated for each RCP scenario and year based on changes in concentrations of ozone and PM2.5 relative to 2000. Using a health impact function, changes in concentrations for each RCP scenario are combined with future population and cause-specific baseline mortality rates as projected by a single independent scenario in which the global incidence of cardiopulmonary diseases is expected to increase. The effect of climate change is isolated by considering the difference between air pollutant concentrations from simulations with 2000 emissions and a future year climate and simulations with 2000 emissions and climate. Uncertainties in the results reflect the uncertainty in the concentration-response function and that associated with variability among models. Few previous studies have quantified the effects of future climate change on global human health via changes in air quality, and this is the first such study to use an ensemble of global models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018MS%26E..342a2004N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018MS%26E..342a2004N"><span>Assessing the implementation of bias correction in the climate prediction</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>Nadrah Aqilah Tukimat, Nurul</p> <p>2018-04-01</p> <p>An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1248960','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1248960"><span>Final Technical Report for DOE Award SC0006616</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>Robertson, Andrew</p> <p>2015-08-01</p> <p>This report summarizes research carried out by the project "Collaborative Research, Type 1: Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia. This collaborative project brought together climate dynamicists (UCLA, IRI), dendroclimatologists (LDEO Tree Ring Laboratory), computer scientists (UCI), and hydrologists (Columbia Water Center, CWC), together with applied scientists in climate risk management (IRI) to create new scientific approaches to quantify and exploit the role of climate variability and change in the growing water crisis across southern and eastern Asia. This project developed new tree-ring based streamflow reconstructions for rivers in monsoonal Asia; improved understanding of hydrologic spatio-temporal modesmore » of variability over monsoonal Asia on interannual-to-centennial time scales; assessed decadal predictability of hydrologic spatio-temporal modes; developed stochastic simulation tools for creating downscaled future climate scenarios based on historical/proxy data and GCM climate change; and developed stochastic reservoir simulation and optimization for scheduling hydropower, irrigation and navigation releases.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://www.ars.usda.gov/research/publications/publication/?seqNo115=237209','TEKTRAN'); return false;" href="http://www.ars.usda.gov/research/publications/publication/?seqNo115=237209"><span>Crop response to climate: ecophysical models</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>Ecophysiological models were the dominant tools used to estimate the potential impact of climate change in agroecosystems in the Third and Fourth Assessment Reports of the IPCC and are widely used elsewhere in climate change research. These models, also known as “crop models” or “simulation models”,...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRD..11911682S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRD..11911682S"><span>Improving the representation of clouds, radiation, and precipitation using spectral nudging in the Weather Research and Forecasting 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>Spero, Tanya L.; Otte, Martin J.; Bowden, Jared H.; Nolte, Christopher G.</p> <p>2014-10-01</p> <p>Spectral nudging—a scale-selective interior constraint technique—is commonly used in regional climate models to maintain consistency with large-scale forcing while permitting mesoscale features to develop in the downscaled simulations. Several studies have demonstrated that spectral nudging improves the representation of regional climate in reanalysis-forced simulations compared with not using nudging in the interior of the domain. However, in the Weather Research and Forecasting (WRF) model, spectral nudging tends to produce degraded precipitation simulations when compared to analysis nudging—an interior constraint technique that is scale indiscriminate but also operates on moisture fields which until now could not be altered directly by spectral nudging. Since analysis nudging is less desirable for regional climate modeling because it dampens fine-scale variability, changes are proposed to the spectral nudging methodology to capitalize on differences between the nudging techniques and aim to improve the representation of clouds, radiation, and precipitation without compromising other fields. These changes include adding spectral nudging toward moisture, limiting nudging to below the tropopause, and increasing the nudging time scale for potential temperature, all of which collectively improve the representation of mean and extreme precipitation, 2 m temperature, clouds, and radiation, as demonstrated using a model-simulated 20 year historical period. Such improvements to WRF may increase the fidelity of regional climate data used to assess the potential impacts of climate change on human health and the environment and aid in climate change mitigation and adaptation studies.</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/2007AGUFMGC33B..01B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AGUFMGC33B..01B"><span>Data gathering and simulation of climate change impacts in mountainous areas</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>Bachelet, D.; Baker, B.; Hicke, J.; Conklin, D.; McKelvey, K.</p> <p>2007-12-01</p> <p>High mountains include species most at risk in a warming environment and are a critical link in the water supply chain for both human and natural systems. Scientists are monitoring and simulating these systems as snowpack depth changes, snowmelt timing changes, frozen soils melt and destabilize, and low elevation populations migrate upslope. Natural climate cycles and human activities interact with climate change trends and complicate the interpretation of the signal we observe. For ex. over the past 4 years in Yunnan (China), we documented that herbaceous alpine meadows are contracting as forest tree line advances and alpine shrub biomass increases. This is a result of interactions between human land use alteration and observed shifts in climate. In North America as snowpack decreases, wolverines and lynx denning conditions are jeopardized as human pressure reduces their extent. Coarse scale vegetation shift models using downscaled future climate scenarios fail to capture complex terrain features and microclimatic conditions that can either ensure critical habitat for the in-situ survival of threatened species or make things worse (ex. rockfalls) for climate migrants. Recent simulation efforts focus on high resolution models that address aspect, slope, soil types, and microclimate variations that affect local and migrating plants, their associated pollinators and insect herbivores, modifying habitat availability for birds and mammals</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp...69Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp...69Z"><span>Assessment of climate change in Algeria from 1951 to 2098 using the Köppen-Geiger climate classification scheme</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>Zeroual, Ayoub; Assani, Ali A.; Meddi, Mohamed; Alkama, Ramdane</p> <p>2018-02-01</p> <p>Significant changes in regional climates have been observed at the end of the twentieth century, taking place at unprecedented rates. These changes, in turn, lead to changes in global climate zones with pace and amplitude varying from one region to another. Algeria, a country characterized by climate conditions ranging from relatively wet to very dry (desert-like), has also experienced changes in its climate regions, notably in the country's wet region, which represents about 7% of its total surface area, but is home to 75% of its population. In this study, the pace of climate zone changes as it is defined by Koppen-Geiger was analyzed for the period from 1951 to 2098 using climate data from observation and regional climate simulations over Algeria. The ability of the CORDEX-Africa regional climate models simulations to reproduce the current observed climate zones and their shifts was first assessed. Future changes over the whole of the twenty-first century were then estimated based on two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Analysis of the shift rate of climate zones from 1951 to 2005 found a gradual but significant expansion of the surface area of the desert zone at an approximate rate of 650 ± 160 km2/year along with the abrupt shrinking, by approximately 30%, at a rate of 1086 ± 270 km2/year, of the warm temperate climate zone surface area. According to projections for the RCP8.5 scenario, the rate of expansion of desert climate will increase in the future (twenty-first century), particularly during the period from 2045 to 2098.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.epa.gov/research-grants/webinar-presentation-particle-resolved-simulations-quantifying-black-carbon-climate','PESTICIDES'); return false;" href="https://www.epa.gov/research-grants/webinar-presentation-particle-resolved-simulations-quantifying-black-carbon-climate"><span>Webinar Presentation: Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty</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>This presentation, Particle-Resolved Simulations for Quantifying Black Carbon Climate Impact and Model Uncertainty, was given at the STAR Black Carbon 2016 Webinar Series: Changing Chemistry over Time held on Oct. 31, 2016.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014ERL.....9f4005C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014ERL.....9f4005C"><span>Sensitivity of ocean acidification and oxygen to the uncertainty 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>Cao, Long; Wang, Shuangjing; Zheng, Meidi; Zhang, Han</p> <p>2014-05-01</p> <p>Due to increasing atmospheric CO2 concentrations and associated climate change, the global ocean is undergoing substantial physical and biogeochemical changes. Among these, changes in ocean oxygen and carbonate chemistry have great implication for marine biota. There is considerable uncertainty in the projections of future climate change, and it is unclear how the uncertainty in climate change would also affect the projection of oxygen and carbonate chemistry. To investigate this issue, we use an Earth system model of intermediate complexity to perform a set of simulations, including that which involves no radiative effect of atmospheric CO2 and those which involve CO2-induced climate change with climate sensitivity varying from 0.5 °C to 4.5 °C. Atmospheric CO2 concentration is prescribed to follow RCP 8.5 pathway and its extensions. Climate change affects carbonate chemistry and oxygen mainly through its impact on ocean temperature, ocean ventilation, and concentration of dissolved inorganic carbon and alkalinity. It is found that climate change mitigates the decrease of carbonate ions at the ocean surface but has negligible effect on surface ocean pH. Averaged over the whole ocean, climate change acts to decrease oxygen concentration but mitigates the CO2-induced reduction of carbonate ion and pH. In our simulations, by year 2500, every degree increase of climate sensitivity warms the ocean by 0.8 °C and reduces ocean-mean dissolved oxygen concentration by 5.0%. Meanwhile, every degree increase of climate sensitivity buffers CO2-induced reduction in ocean-mean carbonate ion concentration and pH by 3.4% and 0.02 units, respectively. Our study demonstrates different sensitivities of ocean temperature, carbonate chemistry, and oxygen, in terms of both the sign and magnitude to the amount of climate change, which have great implications for understanding the response of ocean biota to climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/984152','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/984152"><span>Estimates of the long-term U.S. economic impacts of global climate change-induced drought.</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>Ehlen, Mark Andrew; Loose, Verne W.; Warren, Drake E.</p> <p>2010-01-01</p> <p>While climate-change models have done a reasonable job of forecasting changes in global climate conditions over the past decades, recent data indicate that actual climate change may be much more severe. To better understand some of the potential economic impacts of these severe climate changes, Sandia economists estimated the impacts to the U.S. economy of climate change-induced impacts to U.S. precipitation over the 2010 to 2050 time period. The economists developed an impact methodology that converts changes in precipitation and water availability to changes in economic activity, and conducted simulations of economic impacts using a large-scale macroeconomic model of themore » U.S. economy.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27837471','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27837471"><span>Warmer and drier conditions and nitrogen fertilizer application altered methanotroph abundance and methane emissions in a vegetable soil.</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>Ran, Yu; Xie, Jianli; Xu, Xiaoya; Li, Yong; Liu, Yapeng; Zhang, Qichun; Li, Zheng; Xu, Jianming; Di, Hongjie</p> <p>2017-01-01</p> <p>Methane (CH 4 ) is a potent greenhouse gas, and soil can both be a source and sink for atmospheric CH 4 . It is not clear how future climate change may affect soil CH 4 emissions and related microbial communities. The aim of this study was to determine the interactive effects of a simulated warmer and drier climate scenarios and the application of different nitrogen (N) sources (urea and manure) on CH 4 emissions and related microbial community abundance in a vegetable soil. Greenhouses were used to control simulated climate conditions which gave 2.99 °C warmer and 6.2% lower water content conditions. The field experiment was divided into two phases. At the beginning of phase II, half of the greenhouses were removed to study possible legacy effects of the simulated warmer and drier conditions. The responses in methanogen and methanotroph abundance to a simulated climate change scenario were determined using real-time PCR. The results showed that the simulated warmer and drier conditions in the greenhouses significantly decreased CH 4 emissions largely due to the lower soil moisture content. For the same reason, CH 4 emissions of treatments in phase I were much lower than the same treatments in phase II. The abundance of methanotrophs showed a more significant response than methanogens to the simulated climate change scenario, increasing under simulated drier conditions. Methanogenic community abundance remained low, except where manure was applied which provided a source of organic C that stimulated methanogen growth. Soil moisture content was a major driver for methanotroph abundance and strongly affected CH 4 emissions. The application of N source decreased CH 4 emissions probably because of increased methanotrophic activity. CH 4 emissions were positively correlated to methanogenic abundance and negatively correlated to methanotrophic abundance. These results demonstrate that projected future climate change conditions can have a feedback impact on CH 4 emissions from the soil by altering soil conditions (particularly soil moisture) and related microbial communities.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.131..581P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.131..581P"><span>Projected changes in rainfall and temperature over homogeneous regions of 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>Patwardhan, Savita; Kulkarni, Ashwini; Rao, K. Koteswara</p> <p>2018-01-01</p> <p>The impact of climate change on the characteristics of seasonal maximum and minimum temperature and seasonal summer monsoon rainfall is assessed over five homogeneous regions of India using a high-resolution regional climate model. Providing REgional Climate for Climate Studies (PRECIS) is developed at Hadley Centre for Climate Prediction and Research, UK. The model simulations are carried out over South Asian domain for the continuous period of 1961-2098 at 50-km horizontal resolution. Here, three simulations from a 17-member perturbed physics ensemble (PPE) produced using HadCM3 under the Quantifying Model Uncertainties in Model Predictions (QUMP) project of Hadley Centre, Met. Office, UK, have been used as lateral boundary conditions (LBCs) for the 138-year simulations of the regional climate model under Intergovernmental Panel on Climate Change (IPCC) A1B scenario. The projections indicate the increase in the summer monsoon (June through September) rainfall over all the homogeneous regions (15 to 19%) except peninsular India (around 5%). There may be marginal change in the frequency of medium and heavy rainfall events (>20 mm) towards the end of the present century. The analysis over five homogeneous regions indicates that the mean maximum surface air temperatures for the pre-monsoon season (March-April-May) as well as the mean minimum surface air temperature for winter season (January-February) may be warmer by around 4 °C towards the end of the twenty-first century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.B54B..04L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.B54B..04L"><span>How disturbance, competition and dispersal interact to prevent tree range boundaries from keeping pace with 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>Liang, Y.; Duveneck, M.; Gustafson, E. J.; Serra-Diaz, J. M.; Thompson, J. R.</p> <p>2017-12-01</p> <p>Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change, disturbance and competitive interactions to produce range shifts are poorly understood. We used a physiologically-based mechanistic landscape model to study these interactions in the northeastern United States. We designed a series of disturbance scenarios to represent varied disturbance regimes in terms of both disturbance extent and intensity. We simulated forest succession by incorporating climate change under a high emissions future, disturbances, seed dispersal, and competition using the landscape model parameterized with forest inventory data. Tree species range boundary shifts in the next century were quantified as the change in the location of the 5th (the trailing edge) and 95th (the leading edge) percentiles of the spatial distribution of simulated species. Simulated tree species range boundary shifts in New England over the next century were far below (usually < 20 km) that required to track the velocity of temperature change (usually more than 110 km over 100 years) under a high emissions scenario. Simulated species` ranges shifted northward at both the leading edge (northern boundary) and trailing edge (southern boundary). Disturbances may expedite species` recruitment into new sites, but they had little effect on the velocity of simulated range boundary shifts. Range shifts at the trailing edge tended to be associated with photosynthetic capacity, competitive ability for light and seed dispersal ability, whereas shifts at the leading edge were associated only with photosynthetic capacity and competition for light. This study underscores the importance of understanding the role of interspecific competition and disturbance when studying tree range shifts.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29034990','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29034990"><span>How disturbance, competition, and dispersal interact to prevent tree range boundaries from keeping pace with 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>Liang, Yu; Duveneck, Matthew J; Gustafson, Eric J; Serra-Diaz, Josep M; Thompson, Jonathan R</p> <p>2018-01-01</p> <p>Climate change is expected to cause geographic shifts in tree species' ranges, but such shifts may not keep pace with climate changes because seed dispersal distances are often limited and competition-induced changes in community composition can be relatively slow. Disturbances may speed changes in community composition, but the interactions among climate change, disturbance and competitive interactions to produce range shifts are poorly understood. We used a physiologically based mechanistic landscape model to study these interactions in the northeastern United States. We designed a series of disturbance scenarios to represent varied disturbance regimes in terms of both disturbance extent and intensity. We simulated forest succession by incorporating climate change under a high-emissions future, disturbances, seed dispersal, and competition using the landscape model parameterized with forest inventory data. Tree species range boundary shifts in the next century were quantified as the change in the location of the 5th (the trailing edge) and 95th (the leading edge) percentiles of the spatial distribution of simulated species. Simulated tree species range boundary shifts in New England over the next century were far below (usually <20 km) that required to track the velocity of temperature change (usually more than 110 km over 100 years) under a high-emissions scenario. Simulated species` ranges shifted northward at both the leading edge (northern boundary) and trailing edge (southern boundary). Disturbances may expedite species' recruitment into new sites, but they had little effect on the velocity of simulated range boundary shifts. Range shifts at the trailing edge tended to be associated with photosynthetic capacity, competitive ability for light and seed dispersal ability, whereas shifts at the leading edge were associated only with photosynthetic capacity and competition for light. This study underscores the importance of understanding the role of interspecific competition and disturbance when studying tree range shifts. © 2017 John Wiley & Sons Ltd.</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://hdl.handle.net/2060/20140010545','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010545"><span>Impacts of Atmosphere-Ocean Coupling on Southern Hemisphere Climate Change</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>Li, Feng; Newman, Paul; Pawson, Steven</p> <p>2013-01-01</p> <p>Climate in the Southern Hemisphere (SH) has undergone significant changes in recent decades. These changes are closely linked to the shift of the Southern Annular Mode (SAM) towards its positive polarity, which is driven primarily by Antarctic ozone depletion. There is growing evidence that Antarctic ozone depletion has significant impacts on Southern Ocean circulation change. However, it is poorly understood whether and how ocean feedback might impact the SAM and climate change in the SH atmosphere. This outstanding science question is investigated using the Goddard Earth Observing System Coupled Atmosphere-Ocean-Chemistry Climate Model(GEOS-AOCCM).We perform ensemble simulations of the recent past (1960-2010) with and without the interactive ocean. For simulations without the interactive ocean, we use sea surface temperatures and sea ice concentrations produced by the interactive ocean simulations. The differences between these two ensemble simulations quantify the effects of atmosphere-ocean coupling. We will investigate the impacts of atmosphere-ocean coupling on stratospheric processes such as Antarctic ozone depletion and Antarctic polar vortex breakup. We will address whether ocean feedback affects Rossby wave generation in the troposphere and wave propagation into the stratosphere. Another focuson this study is to assess how ocean feedback might affect the tropospheric SAM response to Antarctic ozone depletion</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9347P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9347P"><span>Future efficiency of run of the river hydropower schemes based on climate change scenarios: case study in UK catchments</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>Pasten Zapata, Ernesto; Moggridge, Helen; Jones, Julie; Widmann, Martin</p> <p>2017-04-01</p> <p>Run-of-the-River (ROR) hydropower schemes are expected to be importantly affected by climate change as they rely in the availability of river flow to generate energy. As temperature and precipitation are expected to vary in the future, the hydrological cycle will also undergo changes. Therefore, climate models based on complex physical atmospheric interactions have been developed to simulate future climate scenarios considering the atmosphere's greenhouse gas concentrations. These scenarios are classified according to the Representative Concentration Pathways (RCP) that are generated according to the concentration of greenhouse gases. This study evaluates possible scenarios for selected ROR hydropower schemes within the UK, considering three different RCPs: 2.6, 4.5 and 8.5 W/m2 for 2100 relative to pre-industrial values. The study sites cover different climate, land cover, topographic and hydropower scheme characteristics representative of the UK's heterogeneity. Precipitation and temperature outputs from state-of-the-art Regional Climate Models (RCMs) from the Euro-CORDEX project are used as input for a HEC-HMS hydrological model to simulate the future river flow available. Both uncorrected and bias-corrected RCM simulations are analyzed. The results of this project provide an insight of the possible effects of climate change towards the generation of power from the ROR hydropower schemes according to the different RCP scenarios and contrasts the results obtained from uncorrected and bias-corrected RCMs. This analysis can aid on the adaptation to climate change as well as the planning of future ROR schemes in the region.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013NatGe...6..337B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013NatGe...6..337B"><span>Climate change: Future rise in rain inequality</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>Biasutti, Michela</p> <p>2013-05-01</p> <p>Rainfall disparities are expected to intensify in response to anthropogenic climate change. Model simulations suggest that wet regions and seasons will get wetter, and that a warmer equator will get wetter too.</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> </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('https://www.osti.gov/pages/biblio/1104732-accuracy-climate-models-simulated-season-lengths-effectiveness-grid-scale-correction-factors','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1104732-accuracy-climate-models-simulated-season-lengths-effectiveness-grid-scale-correction-factors"><span>The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Winterhalter, Wade E.</p> <p>2011-09-01</p> <p>Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1407276','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1407276"><span>TECA: Petascale pattern recognition for climate science</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>Prabhat, .; Byna, Surendra; Vishwanath, Venkatram</p> <p></p> <p>Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC13D..08B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC13D..08B"><span>Exploring the implication of climate process uncertainties within the Earth System Framework</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>Booth, B.; Lambert, F. H.; McNeal, D.; Harris, G.; Sexton, D.; Boulton, C.; Murphy, J.</p> <p>2011-12-01</p> <p>Uncertainties in the magnitude of future climate change have been a focus of a great deal of research. Much of the work with General Circulation Models has focused on the atmospheric response to changes in atmospheric composition, while other processes remain outside these frameworks. Here we introduce an ensemble of new simulations, based on an Earth System configuration of HadCM3C, designed to explored uncertainties in both physical (atmospheric, oceanic and aerosol physics) and carbon cycle processes, using perturbed parameter approaches previously used to explore atmospheric uncertainty. Framed in the context of the climate response to future changes in emissions, the resultant future projections represent significantly broader uncertainty than existing concentration driven GCM assessments. The systematic nature of the ensemble design enables interactions between components to be explored. For example, we show how metrics of physical processes (such as climate sensitivity) are also influenced carbon cycle parameters. The suggestion from this work is that carbon cycle processes represent a comparable contribution to uncertainty in future climate projections as contributions from atmospheric feedbacks more conventionally explored. The broad range of climate responses explored within these ensembles, rather than representing a reason for inaction, provide information on lower likelihood but high impact changes. For example while the majority of these simulations suggest that future Amazon forest extent is resilient to the projected climate changes, a small number simulate dramatic forest dieback. This ensemble represents a framework to examine these risks, breaking them down into physical processes (such as ocean temperature drivers of rainfall change) and vegetation processes (where uncertainties point towards requirements for new observational constraints).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JHyd..534..178H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JHyd..534..178H"><span>Projecting impacts of climate change on hydrological conditions and biotic responses in a chalk valley riparian wetland</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>House, A. R.; Thompson, J. R.; Acreman, M. C.</p> <p>2016-03-01</p> <p>Projected changes in climate are likely to substantially impact wetland hydrological conditions that will in turn have implications for wetland ecology. Assessing ecohydrological impacts of climate change requires models that can accurately simulate water levels at the fine-scale resolution to which species and communities respond. Hydrological conditions within the Lambourn Observatory at Boxford, Berkshire, UK were simulated using the physically based, distributed model MIKE SHE, calibrated to contemporary surface and groundwater levels. The site is a 10 ha lowland riparian wetland where complex geological conditions and channel management exert strong influences on the hydrological regime. Projected changes in precipitation, potential evapotranspiration, channel discharge and groundwater level were derived from the UK Climate Projections 2009 ensemble of climate models for the 2080s under different scenarios. Hydrological impacts of climate change differ through the wetland over short distances depending on the degree of groundwater/surface-water interaction. Discrete areas of groundwater upwelling are associated with an exaggerated response of water levels to climate change compared to non-upwelling areas. These are coincident with regions where a weathered chalk layer, which otherwise separates two main aquifers, is absent. Simulated water levels were linked to requirements of the MG8 plant community and Desmoulin's whorl snail (Vertigo moulinsiana) for which the site is designated. Impacts on each are shown to differ spatially and in line with hydrological impacts. Differences in water level requirements for this vegetation community and single species highlight the need for separate management strategies in distinct areas of the wetland.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1415347','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1415347"><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>Hinzman, Larry D.; Bolton, William Robert; Young-Robertson, Jessica</p> <p></p> <p>This project improves meso-scale hydrologic modeling in the boreal forest by: (1) demonstrating the importance of capturing the heterogeneity of the landscape using small scale datasets for parameterization for both small and large basins; (2) demonstrating that in drier parts of the landscape and as the boreal forest dries with climate change, modeling approaches must consider the sensitivity of simulations to soil hydraulic parameters - such as residual water content - that are usually held constant. Thus, variability / flexibility in residual water content must be considered for accurate simulation of hydrologic processes in the boreal forest; (3) demonstrating thatmore » assessing climate change impacts on boreal forest hydrology through multiple model integration must account for direct effects of climate change (temperature and precipitation), and indirect effects from climate impacts on landscape characteristics (permafrost and vegetation distribution). Simulations demonstrated that climate change will increase runoff, but will increase ET to a greater extent and result in a drying of the landscape; and (4) vegetation plays a significant role in boreal hydrologic processes in permafrost free areas that have deciduous trees. This landscape type results in a decoupling of ET and precipitation, a tight coupling of ET and temperature, low runoff, and overall soil drying.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70159641','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70159641"><span>Early-Holocene warming in Beringia and its mediation by sea-level and vegetation 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>Bartlein, P.J.; Edwards, M.E.; Hostetler, Steven W.; Shafer, Sarah; Anderson, P.M.; Brubaker, L. B; Lozhkin, A. V</p> <p>2015-01-01</p> <p>Arctic land-cover changes induced by recent global climate change (e.g., expansion of woody vegetation into tundra and effects of permafrost degradation) are expected to generate further feedbacks to the climate system. Past changes can be used to assess our understanding of feedback mechanisms through a combination of process modeling and paleo-observations. The subcontinental region of Beringia (northeastern Siberia, Alaska, and northwestern Canada) was largely ice-free at the peak of deglacial warming and experienced both major vegetation change and loss of permafrost when many arctic regions were still ice covered. The evolution of Beringian climate at this time was largely driven by global features, such as the amplified seasonal cycle of Northern Hemisphere insolation and changes in global ice volume and atmospheric composition, but changes in regional land-surface controls, such as the widespread development of thaw lakes, the replacement of tundra by deciduous forest or woodland, and the flooding of the Bering–Chukchi land bridge, were probably also important. We examined the sensitivity of Beringia's early Holocene climate to these regional-scale controls using a regional climate model (RegCM). Lateral and oceanic boundary conditions were provided by global climate simulations conducted using the GENESIS V2.01 atmospheric general circulation model (AGCM) with a mixed-layer ocean. We carried out two present-day simulations of regional climate – one with modern and one with 11 ka geography – plus another simulation for 6 ka. In addition, we performed five ~ 11 ka climate simulations, each driven by the same global AGCM boundary conditions: (i) 11 ka Control, which represents conditions just prior to the major transitions (exposed land bridge, no thaw lakes or wetlands, widespread tundra vegetation), (ii) sea-level rise, which employed present-day continental outlines, (iii) vegetation change, with deciduous needleleaf and deciduous broadleaf boreal vegetation types distributed as suggested by the paleoecological record, (iv) thaw lakes, which used the present-day distribution of lakes and wetlands, and (v) post-11 ka All, incorporating all boundary conditions changed in experiments (ii)–(iv). We find that regional-scale controls strongly mediate the climate responses to changes in the large-scale controls, amplifying them in some cases, damping them in others, and, overall, generating considerable spatial heterogeneity in the simulated climate changes. The change from tundra to deciduous woodland produces additional widespread warming in spring and early summer over that induced by the 11 ka insolation regime alone, and lakes and wetlands produce modest and localized cooling in summer and warming in winter. The greatest effect is the flooding of the land bridge and shelves, which produces generally cooler conditions in summer but warmer conditions in winter and is most clearly manifest on the flooded shelves and in eastern Beringia. By 6 ka continued amplification of the seasonal cycle of insolation and loss of the Laurentide ice sheet produce temperatures similar to or higher than those at 11 ka, plus a longer growing season.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1814646F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1814646F"><span>Nation-wide assessment of climate change impacts on crops in the Philippines and Peru as part of multi-disciplinary modelling framework</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>Agriculture is vulnerable to environmental changes, and climate change has been recognized as one of the most devastating factors. In many developing countries, however, few studies have focused on nation-wide assessment of crop yield and crop suitability in the future, and hence there is a large pressure on science to provide policy makers with solid predictions for major crops in the countries in support of climate risk management policies and programmes. FAO has developed the tool MOSAICC (Modelling System for Agricultural Impacts of Climate Change) where statistical climate downscaling is combined with crop yield projections under climate change scenarios. Three steps are required to get the results: 1. The historical meteorological data such as temperature and precipitation for about 30 years were collected, and future climates were statistically downscaled to the local scale, 2. The historical crop yield data were collected and regression functions were made to estimate the yield by using observed climatic data and water balance during the growing period for each crop, and 3. The yield changes in the future were estimated by using the future climate data, produced by the first step, as an input to the yield regression functions. The yield was first simulated at sub-national scale and aggregated to national scale, which is intended to provide national policies with adaptation options. The methodology considers future changes in characteristics of extreme weather events as the climate projections are on daily scale while crop simulations are on 10-daily scale. Yields were simulated with two greenhouse gas concentration pathways (RCPs) for three GCMs per crop to account for uncertainties in projections. The crop assessment constitutes a larger multi-disciplinary assessment of climate change impacts on agriculture and vulnerability of livelihoods in terms of food security (e.g. water resources, agriculture market, household-level food security from socio-economic perspective). In our presentation we will show the cases of Peru and the Philippines, and discuss the implications for agriculture policies and risk management.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012CliPa...8..637D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012CliPa...8..637D"><span>A seesaw in Mediterranean precipitation during the Roman Period linked to millennial-scale changes in the North Atlantic</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>Dermody, B. J.; de Boer, H. J.; Bierkens, M. F. P.; Weber, S. L.; Wassen, M. J.; Dekker, S. C.</p> <p>2012-03-01</p> <p>We present a reconstruction of the change in climatic humidity around the Mediterranean between 3000-1000 yr BP. Using a range of proxy archives and model simulations we demonstrate that climate during this period was typified by a millennial-scale seesaw in climatic humidity between Spain and Israel on one side and the Central Mediterranean and Turkey on the other, similar to precipitation anomalies associated with the East Atlantic/West Russia pattern in current climate. We find that changes in the position and intensity of the jet stream indicated by our analysis correlate with millennial changes in North Atlantic sea surface temperature. A model simulation indicates the proxies of climatic humidity used in our analysis were unlikely to be influenced by climatic aridification caused by deforestation during the Roman Period. That finding is supported by an analysis of the distribution of archaeological sites in the Eastern Mediterranean which exhibits no evidence that human habitation distribution changed since ancient times as a result of climatic aridification. Therefore we conclude that changes in climatic humidity over the Mediterranean during the Roman Period were primarily caused by a modification of the jet stream linked to sea surface temperature change in the North Atlantic. Based on our findings, we propose that ocean-atmosphere coupling may have contributed to regulating Atlantic Meridional Overturning Circulation intensity during the period of analysis.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMPP31C1647E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMPP31C1647E"><span>The Astronomical Forcing of Climate Change: Forcings and 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>Erb, M. P.; Broccoli, A. J.; Clement, A. C.</p> <p>2010-12-01</p> <p>Understanding the role that orbital forcing played in driving climate change over the Pleistocene has been a matter of ongoing research. While it is undeniable that variations in Earth’s orbit result in changes in the seasonal and latitudinal distribution of insolation, the specifics of how this forcing leads to the climate changes seen in the paleo record are not fully understood. To research this further, climate simulations have been conducted with the GFDL CM2.1, a coupled atmosphere-ocean GCM. Two simulations represent the extremes of obliquity during the past 600 kyr and four others show key times in the precessional cycle. All non-orbital variables are set to preindustrial levels to isolate the effects of astronomical forcing alone. It is expected that feedbacks should play a large role in dictating climate change, so to investigate this, the so-called “kernel method” is used to calculate the lapse rate, water vapor, albedo, and cloud feedbacks. Preliminary results of these experiments confirm that feedbacks are important in explaining the nature and, in places, even the sign of climate response to orbital forcing. In the case of low obliquity, for instance, a combination of climate feedbacks lead to global cooling in spite of zero global-average top of atmosphere insolation change. Feedbacks will be analyzed in the obliquity and precession experiments so that the role of feedbacks in contributing to climate change may be better understood.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/16600331','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/16600331"><span>Simulation of future stream alkalinity under changing deposition and climate scenarios.</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>Welsch, Daniel L; Cosby, B Jack; Hornberger, George M</p> <p>2006-08-31</p> <p>Models of soil and stream water acidification have typically been applied under scenarios of changing acidic deposition, however, climate change is usually ignored. Soil air CO2 concentrations have potential to increase as climate warms and becomes wetter, thus affecting soil and stream water chemistry by initially increasing stream alkalinity at the expense of reducing base saturation levels on soil exchange sites. We simulate this change by applying a series of physically based coupled models capable of predicting soil air CO2 and stream water chemistry. We predict daily stream water alkalinity for a small catchment in the Virginia Blue Ridge for 60 years into the future given stochastically generated daily climate values. This is done for nine different combinations of climate and deposition. The scenarios for both climate and deposition include a static scenario, a scenario of gradual change, and a scenario of abrupt change. We find that stream water alkalinity continues to decline for all scenarios (average decrease of 14.4 microeq L-1) except where climate is gradually warming and becoming more moist (average increase of 13 microeq L-1). In all other scenarios, base cation removal from catchment soils is responsible for limited alkalinity increase resulting from climate change. This has implications given the extent that acidification models are used to establish policy and legislation concerning deposition and emissions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27418072','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27418072"><span>Impact of climate change on crop yield and role of model for achieving food security.</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>Kumar, Manoj</p> <p>2016-08-01</p> <p>In recent times, several studies around the globe indicate that climatic changes are likely to impact the food production and poses serious challenge to food security. In the face of climate change, agricultural systems need to adapt measures for not only increasing food supply catering to the growing population worldwide with changing dietary patterns but also to negate the negative environmental impacts on the earth. Crop simulation models are the primary tools available to assess the potential consequences of climate change on crop production and informative adaptive strategies in agriculture risk management. In consideration with the important issue, this is an attempt to provide a review on the relationship between climate change impacts and crop production. It also emphasizes the role of crop simulation models in achieving food security. Significant progress has been made in understanding the potential consequences of environment-related temperature and precipitation effect on agricultural production during the last half century. Increased CO2 fertilization has enhanced the potential impacts of climate change, but its feasibility is still in doubt and debates among researchers. To assess the potential consequences of climate change on agriculture, different crop simulation models have been developed, to provide informative strategies to avoid risks and understand the physical and biological processes. Furthermore, they can help in crop improvement programmes by identifying appropriate future crop management practises and recognizing the traits having the greatest impact on yield. Nonetheless, climate change assessment through model is subjected to a range of uncertainties. The prediction uncertainty can be reduced by using multimodel, incorporating crop modelling with plant physiology, biochemistry and gene-based modelling. For devloping new model, there is a need to generate and compile high-quality field data for model testing. Therefore, assessment of agricultural productivity to sustain food security for generations is essential to maintain a collective knowledge and resources for preventing negative impact as well as managing crop practises.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018GBioC..32..565B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018GBioC..32..565B"><span>Dynamic Biological Functioning Important for Simulating and Stabilizing Ocean Biogeochemistry</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>Buchanan, P. J.; Matear, R. J.; Chase, Z.; Phipps, S. J.; Bindoff, N. L.</p> <p>2018-04-01</p> <p>The biogeochemistry of the ocean exerts a strong influence on the climate by modulating atmospheric greenhouse gases. In turn, ocean biogeochemistry depends on numerous physical and biological processes that change over space and time. Accurately simulating these processes is fundamental for accurately simulating the ocean's role within the climate. However, our simulation of these processes is often simplistic, despite a growing understanding of underlying biological dynamics. Here we explore how new parameterizations of biological processes affect simulated biogeochemical properties in a global ocean model. We combine 6 different physical realizations with 6 different biogeochemical parameterizations (36 unique ocean states). The biogeochemical parameterizations, all previously published, aim to more accurately represent the response of ocean biology to changing physical conditions. We make three major findings. First, oxygen, carbon, alkalinity, and phosphate fields are more sensitive to changes in the ocean's physical state. Only nitrate is more sensitive to changes in biological processes, and we suggest that assessment protocols for ocean biogeochemical models formally include the marine nitrogen cycle to assess their performance. Second, we show that dynamic variations in the production, remineralization, and stoichiometry of organic matter in response to changing environmental conditions benefit the simulation of ocean biogeochemistry. Third, dynamic biological functioning reduces the sensitivity of biogeochemical properties to physical change. Carbon and nitrogen inventories were 50% and 20% less sensitive to physical changes, respectively, in simulations that incorporated dynamic biological functioning. These results highlight the importance of a dynamic biology for ocean properties and climate.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70036262','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70036262"><span>Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China</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>Zhu, Q.; Jiang, H.; Peng, C.; Liu, J.; Wei, X.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.</p> <p>2011-01-01</p> <p>Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO2concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO2concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=258205&keyword=export&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=258205&keyword=export&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>Climate change and watershed mercury export: a multiple projection and model analysis</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>Future shifts in climatic conditions may impact watershed mercury (Hg) dynamics and transport. We apply an ensemble of watershed models to simulate and assess the responses of hydrological and total Hg (HgT) fluxes and concentrations to two climate change projections in the US Co...</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('http://adsabs.harvard.edu/abs/1983rnac.rept......','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1983rnac.rept......"><span>Response of the North American corn belt to climate warming, CO2</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></p> <p>1983-08-01</p> <p>The climate of the North American corn belt was characterized to estimate the effects of climatic change on that agricultural region. Heat and moisture characteristics of the current corn belt were identified and mapped based on a simulated climate for a doubling of atmospheric CO2 concentrations. The result was a map of the projected corn belt corresponding to the simulated climatic change. Such projections were made with and without an allowance for earlier planting dates that could occur under a CO2-induced climatic warming. Because the direct effects of CO2 increases on plants, improvements in farm technology, and plant breeding are not considered, the resulting projections represent an extreme or worst case. The results indicate that even for such a worst case, climatic conditions favoring corn production would not extend very far into Canada. Climatic buffering effects of the Great Lakes would apparently retard northeastward shifts in corn-belt location.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016HESS...20.4129D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016HESS...20.4129D"><span>Relative impacts of land use and climate change on summer precipitation in the Netherlands</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>Daniels, Emma; Lenderink, Geert; Hutjes, Ronald; Holtslag, Albert</p> <p>2016-10-01</p> <p>The effects of historic and future land use on precipitation in the Netherlands are investigated on 18 summer days with similar meteorological conditions. The days are selected with a circulation type classification and a clustering procedure to obtain a homogenous set of days that is expected to favor land impacts. Changes in precipitation are investigated in relation to the present-day climate and land use, and from the perspective of future climate and land use. To that end, the weather research and forecasting (WRF) model is used with land use maps for 1900, 2000, and 2040. In addition, a temperature perturbation of +1 °C assuming constant relative humidity is imposed as a surrogate climate change scenario. Decreases in precipitation of, respectively, 3-5 and 2-5 % are simulated following conversion of historic to present, and present to future, land use. The temperature perturbation under present land use conditions increases precipitation amounts by on average 7-8 % and amplifies precipitation intensity. However, when also considering future land use, the increase is reduced to 2-6 % on average, and no intensification of extreme precipitation is simulated. In all, the simulated effects of land use changes on precipitation in summer are smaller than the effects of climate change, but are not negligible.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ESDD....6.2181S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ESDD....6.2181S"><span>Impacts of climate change on growth period and planting boundaries of winter wheat in China under RCP4.5 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>Sun, Z.; Jia, S. F.; Lv, A. F.; Yang, K. J.; Svensson, J.; Gao, Y. C.</p> <p>2015-10-01</p> <p>This paper advances understanding of the impacts of climate change on crops in China by moving from ex-post analysis to forecasting, and by demonstrating how the effects of climate change will affect the growth period and the planting boundaries of winter wheat. Using a multiple regression model based on agricultural meteorological observations and the IPCC AR5 GCMs simulations, we find that the sowing date of winter wheat in the base period, 2040s and 2070s, shows a gradually delayed trend from north to south and the growth period of winter wheat in China will be shortened under climate change. The simulation results also show that (i) the north planting boundaries of winter wheat in China will likely move northward and expand westward in the future, while the south planting boundary will rise and spread in south Hainan and Taiwan; and (ii) the Xinjiang Uygur Autonomous Region and the Inner Mongolia Autonomous Region will have the largest increases in planting areas in 2040s and 2070s. Our simulation implies that Xinjiang and Inner Mongolia are more sensitive to climate change than other regions in China and priority should be given to design adaptation strategies for winter wheat planting for these provinces.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H41Q..05L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H41Q..05L"><span>Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System 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>Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.</p> <p>2017-12-01</p> <p>Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A33G0328S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A33G0328S"><span>Windblown Dust and Air Quality Under a Changing Climate in the Pacific Northwest</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>Sharratt, B. S.; Tatarko, J.; Abatzoglou, J. T.; Fox, F.; Huggins, D. R.</p> <p>2016-12-01</p> <p>Wind erosion is a concern for sustainable agriculture and societal health in the US Pacific Northwest. Indeed, wind erosion continues to cause exceedances of the National Ambient Air Quality Standard for PM10 in the region. Can we expect air quality to deteriorate or improve as climate changes? Will wind erosion escalate in the future under a warmer and drier climate as forecast for Australia, southern prairies of Canada, northern China, and United States Corn Belt and Colorado Plateau? To answer these questions, we used 18 global climate models, cropping systems simulation model (CropSyst), and the Wind Erosion Prediction System (WEPS) to simulate the complex interactions among climate, crop production, and wind erosion. These simulations were carried out in eastern Washington where wind erosion of agricultural lands contribute to poor air quality in the region. Our results suggest that an increase in temperature and CO2 concentration, coupled with nominal increases in precipitation, will enhance biomass production and reduce soil and PM10 losses by the mid-21st century. This study reveals that climate change may reduce the risk of wind erosion and improve air quality in the Inland Pacific Northwest.</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('https://pubs.er.usgs.gov/publication/70191007','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70191007"><span>Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change</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>Miller, Brian W.; Frid, Leonardo; Chang, Tony; Piekielek, N. B.; Hansen, Andrew J.; Morisette, Jeffrey T.</p> <p>2015-01-01</p> <p>State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine (Pinus albicaulis). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27723460','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27723460"><span>Future climate change impact assessment of watershed scale hydrologic processes in Peninsular Malaysia by a regional climate model coupled with a physically-based hydrology modelo.</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>Amin, M Z M; Shaaban, A J; Ercan, A; Ishida, K; Kavvas, M L; Chen, Z Q; Jang, S</p> <p>2017-01-01</p> <p>Impacts of climate change on the hydrologic processes under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate and physically-based hydrology model utilizing an ensemble of future climate change projections. An ensemble of 15 different future climate realizations from coarse resolution global climate models' (GCMs) projections for the 21st century was dynamically downscaled to 6km resolution over Peninsular Malaysia by a regional climate model, which was then coupled with the watershed hydrology model WEHY through the atmospheric boundary layer over Muda and Dungun watersheds. Hydrologic simulations were carried out at hourly increments and at hillslope-scale in order to assess the impacts of climate change on the water balances and flooding conditions in the 21st century. The coupled regional climate and hydrology model was simulated for a duration of 90years for each of the 15 realizations. It is demonstrated that the increase in mean monthly flows due to the impact of expected climate change during 2040-2100 is statistically significant from April to May and from July to October at Muda watershed. Also, the increase in mean monthly flows is shown to be significant in November during 2030-2070 and from November to December during 2070-2100 at Dungun watershed. In other words, the impact of the expected climate change will be significant during the northeast and southwest monsoon seasons at Muda watershed and during the northeast monsoon season at Dungun watershed. Furthermore, the flood frequency analyses for both watersheds indicated an overall increasing trend in the second half of the 21st century. Copyright © 2016 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1410623-global-sensitivity-simulated-water-balance-indicators-under-future-climate-change-colorado-basin','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1410623-global-sensitivity-simulated-water-balance-indicators-under-future-climate-change-colorado-basin"><span>Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra; ...</p> <p>2017-11-20</p> <p>The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1410623-global-sensitivity-simulated-water-balance-indicators-under-future-climate-change-colorado-basin','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1410623-global-sensitivity-simulated-water-balance-indicators-under-future-climate-change-colorado-basin"><span>Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin</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>Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra</p> <p></p> <p>The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011790','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011790"><span>The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna</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>Molod, Andrea; Takacs, Lawrence; Suarez, Max; Bacmeister, Julio; Song, In-Sun; Eichmann, Andrew</p> <p>2012-01-01</p> <p>This report is a documentation of the Fortuna version of the GEOS-5 Atmospheric General Circulation Model (AGCM). The GEOS-5 AGCM is currently in use in the NASA Goddard Modeling and Assimilation Office (GMAO) for simulations at a wide range of resolutions, in atmosphere only, coupled ocean-atmosphere, and data assimilation modes. The focus here is on the development subsequent to the version that was used as part of NASA s Modern-Era Retrospective Analysis for Research and Applications (MERRA). We present here the results of a series of 30-year atmosphere-only simulations at different resolutions, with focus on the behavior of the 1-degree resolution simulation. The details of the changes in parameterizations subsequent to the MERRA model version are outlined, and results of a series of 30-year, atmosphere-only climate simulations at 2-degree resolution are shown to demonstrate changes in simulated climate associated with specific changes in parameterizations. The GEOS-5 AGCM presented here is the model used for the GMAO s atmosphere-only and coupled CMIP-5 simulations.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9.2027G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9.2027G"><span>Simulating climate and stable water isotopes during the Last Interglacial using a coupled climate-isotope 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>Gierz, Paul; Werner, Martin; Lohmann, Gerrit</p> <p>2017-09-01</p> <p>Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change, and while it is possible to simulate warm interglacial climates, these simulated results cannot be evaluated without the aid of geochemical proxies. One such proxy is δ18O, which allows for inference about both a climate state's hydrology and temperature. We utilize a stable water isotope equipped climate model to simulate three stages during the Last Interglacial (LIG), corresponding to 130, 125, and 120 kyr before present, using forcings for orbital configuration as well as greenhouse gases. We discover heterogeneous responses in the mean δ18O signal to the climate forcing, with large areas of depletion in the LIG δ18O signal over the tropical Atlantic, the Sahel, and the Indian subcontinent, and with enrichment over the Pacific and Arctic Oceans. While we find that the climatology mean relationship between δ18O and temperature remains stable during the LIG, we also discover that this relationship is not spatially consistent. Our results suggest that great care must be taken when comparing δ18O records of different paleoclimate archives with the results of climate models as both the qualitative and quantitative interpretation of δ18O variations as a proxy for past temperature changes may be problematic due to the complexity of the signals.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.5022A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.5022A"><span>The effect of changing wind forcing on Antarctic ice shelf melting in high-resolution, global sea ice-ocean simulations with the Accelerated Climate Model for Energy (ACME)</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>Asay-Davis, Xylar; Price, Stephen; Petersen, Mark; Wolfe, Jonathan</p> <p>2017-04-01</p> <p>The capability for simulating sub-ice shelf circulation and submarine melting and freezing has recently been added to the U.S. Department of Energy's Accelerated Climate Model for Energy (ACME). With this new capability, we use an eddy permitting ocean model to conduct two sets of simulations in the spirit of Spence et al. (GRL, 41, 2014), who demonstrate increased warm water upwelling along the Antarctic coast in response to poleward shifting and strengthening of Southern Ocean westerly winds. These characteristics, symptomatic of a positive Southern Annular Mode (SAM), are projected to continue into the 21st century under anthropogenic climate change (Fyfe et al., J. Clim., 20, 2007). In our first simulation, we force the climate model using the standard CORE interannual forcing dataset (Large and Yeager; Clim. Dyn., 33, 2009). In our second simulation, we force our climate model using an altered version of CORE interannual forcing, based on the latter half of the full time series, which we take as a proxy for a future climate state biased towards a positive SAM. We compare ocean model states and sub-ice shelf melt rates with observations, exploring sources of model biases as well as the effects of the two forcing scenarios.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1036845','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1036845"><span>Detection and Attribution of Regional Climate Change</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>Bala, G; Mirin, A</p> <p>2007-01-19</p> <p>We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1177296-impacts-climate-change-energy-consumption-peak-demand-buildings-detailed-regional-approach','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1177296-impacts-climate-change-energy-consumption-peak-demand-buildings-detailed-regional-approach"><span>Impacts of Climate Change on Energy Consumption and Peak Demand in Buildings: A Detailed Regional Approach</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>Dirks, James A.; Gorrissen, Willy J.; Hathaway, John E.</p> <p>2015-01-01</p> <p>This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the Eastern Interconnection (EIC) located in the United States. The climate change scenario considered (IPCC A2 scenario as downscaled from the CASCaDE data set) has changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. This investigation examines building energy demand for three annual periods representative of climate trends in the CASCaDE data set at the beginning, middle, andmore » end of the century--2004, 2052, and 2089. Simulations were performed using the Building ENergy Demand (BEND) model which is a detailed simulation platform built around EnergyPlus. BEND was developed in collaboration with the Platform for Regional Integrated Modeling and Analysis (PRIMA), a modeling framework designed to simulate the complex interactions among climate, energy, water, and land at decision-relevant spatial scales. Over 26,000 building configurations of different types, sizes, vintages, and, characteristics which represent the population of buildings within the EIC, are modeled across the 3 EIC time zones using the future climate from 100 locations within the target region, resulting in nearly 180,000 spatially relevant simulated demand profiles for each of the 3 years. In this study, the building stock characteristics are held constant based on the 2005 building stock in order to isolate and present results that highlight the impact of the climate signal on commercial and residential energy demand. Results of this analysis compare well with other analyses at their finest level of specificity. This approach, however, provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability to perform detailed hourly impact studies of building adaptation and mitigation strategies on energy use and electricity peak demand within the context of the entire grid and economy.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC21B1087B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC21B1087B"><span>Modeling the potential persistence of various ecological systems under CMIP5 future climate and land use scenarios throughout California, USA</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>Baker, B.; Ferschweiler, K.; Bachelet, D. M.; Sleeter, B. M.</p> <p>2016-12-01</p> <p>California's geographic location, topographic complexity and latitudinal climatic gradient give rise to great biological and ecological diversity. However, increased land use pressure, altered seasonal weather patterns, and changes in temperature and precipitation regimes are having pronounced effects on ecosystems and the multitude of services they provide for an increasing population. As a result, natural resource managers are faced with formidable challenges to maintain these critical services. The goals of this project were to better understand how projected 21st century climate and land-use change scenarios may alter ecosystem dynamics, the spatial distribution of various vegetation types and land-use patterns, and to provide a coarse scale "triage map" of where land managers may want to concentrate efforts to reduce ecological stress in order to mitigate the potential impacts of a changing climate. We used the MC2 dynamic global vegetation model and the LUCAS state-and-transition simulation model to simulate the potential effects of future climate and land-use change on ecological processes for the state of California. Historical climate data were obtained from the PRISM dataset and nine CMIP5 climate models were run for the RCP 8.5 scenario. Climate projections were combined with a business-as-usual land-use scenario based on local-scale land use histories. For ease of discussion, results from five simulation runs (historic, hot-dry, hot-wet, warm-dry, and warm-wet) are presented. Results showed large changes in the extent of urban and agricultural lands. In addition, several simulated potential vegetation types persisted in situ under all four future scenarios, although alterations in total area, total ecosystem carbon, and forest vigor (NPP/LAI) were noted. As might be expected, the majority of the forested types that persisted occurred on public lands. However, more than 78% of the simulated subtropical mixed forest and 26% of temperate evergreen needleleaf forest types persisted on private lands under all four future scenarios. Result suggest that building collaborations across management borders could be valuable tool to guide natural resource management actions into the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28520770','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28520770"><span>Life history trade-off moderates model predictions of diversity loss from 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>Moor, Helen</p> <p>2017-01-01</p> <p>Climate change can trigger species range shifts, local extinctions and changes in diversity. Species interactions and dispersal capacity are important mediators of community responses to climate change. The interaction between multispecies competition and variation in dispersal capacity has recently been shown to exacerbate the effects of climate change on diversity and to increase predictions of extinction risk dramatically. Dispersal capacity, however, is part of a species' overall ecological strategy and are likely to trade off with other aspects of its life history that influence population growth and persistence. In plants, a well-known example is the trade-off between seed mass and seed number. The presence of such a trade-off might buffer the diversity loss predicted by models with random but neutral (i.e. not impacting fitness otherwise) differences in dispersal capacity. Using a trait-based metacommunity model along a warming climatic gradient the effect of three different dispersal scenarios on model predictions of diversity change were compared. Adding random variation in species dispersal capacity caused extinctions by the introduction of strong fitness differences due an inherent property of the dispersal kernel. Simulations including a fitness-equalising trade-off based on empirical relationships between seed mass (here affecting dispersal distance, establishment probability, and seedling biomass) and seed number (fecundity) maintained higher initial species diversity and predicted lower extinction risk and diversity loss during climate change than simulations with variable dispersal capacity. Large seeded species persisted during climate change, but developed lags behind their climate niche that may cause extinction debts. Small seeded species were more extinction-prone during climate change but tracked their niches through dispersal and colonisation, despite competitive resistance from residents. Life history trade-offs involved in coexistence mechanisms may increase community resilience to future climate change and are useful guides for model development.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29694355','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29694355"><span>Future climate change scenarios in Central America at high spatial resolution.</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>Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena</p> <p>2018-01-01</p> <p>The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961-1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021-2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021-2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5919078','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5919078"><span>Future climate change scenarios in Central America at high spatial resolution</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>Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena</p> <p>2018-01-01</p> <p>The objective of this work is to assess the downscaling projections of climate change over Central America at 8-km resolution using the Eta Regional Climate Model, driven by the HadGEM2-ES simulations of RCP4.5 emission scenario. The narrow characteristic of continent supports the use of numerical simulations at very high-horizontal resolution. Prior to assessing climate change, the 30-year baseline period 1961–1990 is evaluated against different sources of observations of precipitation and temperature. The mean seasonal precipitation and temperature distribution show reasonable agreement with observations. Spatial correlation of the Eta, 8-km resolution, simulations against observations show clear advantage over the driver coarse global model simulations. Seasonal cycle of precipitation confirms the added value of the Eta at 8-km over coarser resolution simulations. The Eta simulations show a systematic cold bias in the region. Climate features of the Mid-Summer Drought and the Caribbean Low-Level Jet are well simulated by the Eta model at 8-km resolution. The assessment of the future climate change is based on the 30-year period 2021–2050, under RCP4.5 scenario. Precipitation is generally reduced, in particular during the JJA and SON, the rainy season. Warming is expected over the region, but stronger in the northern portion of the continent. The Mid-Summer Drought may develop in regions that do not occur during the baseline period, and where it occurs the strength may increase in the future scenario. The Caribbean Low-Level Jet shows little change in the future. Extreme temperatures have positive trend within the period 2021–2050, whereas extreme precipitation, measured by R50mm and R90p, shows positive trend in the eastern coast, around Costa Rica, and negative trends in the northern part of the continent. Negative trend in the duration of dry spell, which is an estimate based on evapotranspiration, is projected in most part of the continent. Annual mean water excess has negative trends in most part of the continent, which suggests decreasing water availability in the future scenario. PMID:29694355</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('http://adsabs.harvard.edu/abs/2017HESS...21.2143Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017HESS...21.2143Y"><span>Impact of climate change on hydrological conditions in a tropical West African catchment using an ensemble of 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>Yira, Yacouba; Diekkrüger, Bernd; Steup, Gero; Yaovi Bossa, Aymar</p> <p>2017-04-01</p> <p>This study evaluates climate change impacts on water resources using an ensemble of six regional climate models (RCMs)-global climate models (GCMs) in the Dano catchment (Burkina Faso). The applied climate datasets were performed in the framework of the <span style="text-decoration:underline; " class="text">COordinated <span style="text-decoration:underline; " class="text">Regional climate <span style="text-decoration:underline; " class="text">Downscaling <span style="text-decoration:underline; " class="text">Experiment (CORDEX-Africa) project.<p class="p">After evaluation of the historical runs of the climate models' ensemble, a statistical bias correction (empirical quantile mapping) was applied to daily precipitation. Temperature and bias corrected precipitation data from the ensemble of RCMs-GCMs was then used as input for the <span style="text-decoration:underline; " class="text">Water flow and balance <span style="text-decoration:underline; " class="text">Simulation <span style="text-decoration:underline; " class="text">Model (WaSiM) to simulate water balance components.<p class="p">The mean hydrological and climate variables for two periods (1971-2000 and 2021-2050) were compared to assess the potential impact of climate change on water resources up to the middle of the 21st century under two greenhouse gas concentration scenarios, the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicate (i) a clear signal of temperature increase of about 0.1 to 2.6 °C for all members of the RCM-GCM ensemble; (ii) high uncertainty about how the catchment precipitation will evolve over the period 2021-2050; (iii) the applied bias correction method only affected the magnitude of the climate change signal; (iv) individual climate models results lead to opposite discharge change signals; and (v) the results for the RCM-GCM ensemble are too uncertain to give any clear direction for future hydrological development. Therefore, potential increase and decrease in future discharge have to be considered in climate change adaptation strategies in the catchment. The results further underline on the one hand the need for a larger ensemble of projections to properly estimate the impacts of climate change on water resources in the catchment and on the other hand the high uncertainty associated with climate projections for the West African region. A water-energy budget analysis provides further insight into the behavior of the catchment.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917494S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917494S"><span>Quantifying the consequences of changing hydroclimatic extremes on protection levels for the Rhine</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>Sperna Weiland, Frederiek; Hegnauer, Mark; Buiteveld, Hendrik; Lammersen, Rita; van den Boogaard, Henk; Beersma, Jules</p> <p>2017-04-01</p> <p>The Dutch method for quantifying the magnitude and frequency of occurrence of discharge extremes in the Rhine basin and the potential influence of climate change hereon are presented. In the Netherlands flood protection design requires estimates of discharge extremes for return periods of 1000 up to 100,000 years. Observed discharge records are too short to derive such extreme return discharges, therefore extreme value assessment is based on very long synthetic discharge time-series generated with the Generator of Rainfall And Discharge Extremes (GRADE). The GRADE instrument consists of (1) a stochastic weather generator based on time series resampling of historical f rainfall and temperature and (2) a hydrological model optimized following the GLUE methodology and (3) a hydrodynamic model to simulate the propagation of flood waves based on the generated hydrological time-series. To assess the potential influence of climate change, the four KNMI'14 climate scenarios are applied. These four scenarios represent a large part of the uncertainty provided by the GCMs used for the IPCC 5th assessment report (the CMIP5 GCM simulations under different climate forcings) and are for this purpose tailored to the Rhine and Meuse river basins. To derive the probability distributions of extreme discharges under climate change the historical synthetic rainfall and temperature series simulated with the weather generator are transformed to the future following the KNMI'14 scenarios. For this transformation the Advanced Delta Change method, which allows that the changes in the extremes differ from those in the means, is used. Subsequently the hydrological model is forced with the historical and future (i.e. transformed) synthetic time-series after which the propagation of the flood waves is simulated with the hydrodynamic model to obtain the extreme discharge statistics both for current and future climate conditions. The study shows that both for 2050 and 2085 increases in discharge extremes for the river Rhine at Lobith are projected by all four KNMI'14 climate scenarios. This poses increased requirements for flood protection design in order to prepare for changing climate conditions.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC14A..07H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC14A..07H"><span>Nonlinear Interactions between Climate and Atmospheric Carbon Dioxide Drivers of Terrestrial and Marine Carbon Cycle Changes</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>Hoffman, F. M.; Randerson, J. T.; Moore, J. K.; Goulden, M.; Fu, W.; Koven, C.; Swann, A. L. S.; Mahowald, N. M.; Lindsay, K. T.; Munoz, E.</p> <p>2017-12-01</p> <p>Quantifying interactions between global biogeochemical cycles and the Earth system is important for predicting future atmospheric composition and informing energy policy. We applied a feedback analysis framework to three sets of Historical (1850-2005), Representative Concentration Pathway 8.5 (2006-2100), and its extension (2101-2300) simulations from the Community Earth System Model version 1.0 (CESM1(BGC)) to quantify drivers of terrestrial and ocean responses of carbon uptake. In the biogeochemically coupled simulation (BGC), the effects of CO2 fertilization and nitrogen deposition influenced marine and terrestrial carbon cycling. In the radiatively coupled simulation (RAD), the effects of rising temperature and circulation changes due to radiative forcing from CO2, other greenhouse gases, and aerosols were the sole drivers of carbon cycle changes. In the third, fully coupled simulation (FC), both the biogeochemical and radiative coupling effects acted simultaneously. We found that climate-carbon sensitivities derived from RAD simulations produced a net ocean carbon storage climate sensitivity that was weaker and a net land carbon storage climate sensitivity that was stronger than those diagnosed from the FC and BGC simulations. For the ocean, this nonlinearity was associated with warming-induced weakening of ocean circulation and mixing that limited exchange of dissolved inorganic carbon between surface and deeper water masses. For the land, this nonlinearity was associated with strong gains in gross primary production in the FC simulation, driven by enhancements in the hydrological cycle and increased nutrient availability. We developed and applied a nonlinearity metric to rank model responses and driver variables. The climate-carbon cycle feedback gain at 2300 was 42% higher when estimated from climate-carbon sensitivities derived from the difference between FC and BGC than when derived from RAD. We re-analyzed other CMIP5 model results to quantify the effects of such nonlinearities on their projected climate-carbon cycle feedback gains.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmEn.158...76Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmEn.158...76Y"><span>Impact of plastic mulching on nitrous oxide emissions in China's arid agricultural region under climate change conditions</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>Yu, Yongxiang; Tao, Hui; Jia, Hongtao; Zhao, Chengyi</p> <p>2017-06-01</p> <p>The denitrification-decomposition (DNDC) model is a useful tool for integrating the effects of agricultural practices and climate change on soil nitrous oxide (N2O) emissions from agricultural ecosystems. In this study, the DNDC model was evaluated against observations and used to simulate the effect of plastic mulching on soil N2O emissions and crop growth. The DNDC model performed well in simulating temporal variations in N2O emissions and plant growth during the observation period, although it slightly underestimated the cumulative N2O emissions, and was able to simulate the effects of plastic mulching on N2O emissions and crop yield. Both the observations and simulations demonstrated that the application of plastic film increased cumulative N2O emissions and cotton lint yield compared with the non-mulched treatment. The sensitivity test showed that the N2O emissions and lint yield were sensitive to changes in climate and management practices, and the application of plastic film made the N2O emissions and lint yield less sensitive to changes in temperature and irrigation. Although the simulations showed that the beneficial impacts of plastic mulching on N2O emissions were not gained under high fertilizer and irrigation scenarios, our simulations suggest that the application of plastic film effectively reduced soil N2O emissions while promoting yields under suitable fertilizer rates and irrigation. Compared with the baseline scenario, future climate change significantly increased N2O emissions by 15-17% without significantly influencing the lint yields in the non-mulched treatment; in the mulched treatment, climate change significantly promoted the lint yield by 5-6% and significantly reduced N2O emissions by 14% in the RCP4.5 and RCP8.5 scenarios. Overall, our results demonstrate that the application of plastic film is an efficient way to address increased N2O emissions and simultaneously enhance crop yield in the future.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN31F..01K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN31F..01K"><span>The CESM Large Ensemble Project: Inspiring New Ideas and Understanding</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>Kay, J. E.; Deser, C.</p> <p>2016-12-01</p> <p>While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26259438','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26259438"><span>[Impact of changes in land use and climate on the runoff in Liuxihe Watershed based on SWAT 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>Yuan, Yu-zhi; Zhang, Zheng-dong; Meng, Jin-hua</p> <p>2015-04-01</p> <p>SWAT model, an extensively used distributed hydrological model, was used to quantitatively analyze the influences of changes in land use and climate on the runoff at watershed scale. Liuxihe Watershed' s SWAT model was established and three scenarios were set. The calibration and validation at three hydrological stations of Wenquan, Taipingchang and Nangang showed that the three factors of Wenquan station just only reached the standard in validated period, and the other two stations had relative error (RE) < 15%, correlation coefficient (R2) > 0.8 and Nash-Sutcliffe efficiency valve (Ens) > 0.75, suggesting that SWAT model was appropriate for simulating runoff response to land use change and climate variability in Liuxihe watershed. According to the integrated scenario simulation, the annual runoff increased by 11.23 m3 x s(-1) from 2001 to 2010 compared with the baseline period from 1991 to 2000, among which, the land use change caused an annual runoff reduction of 0.62 m3 x s(-1), whereas climate variability caused an annual runoff increase of 11.85 m3 x s(-1). Apparently, the impact of climate variability was stronger than that of land use change. On the other hand, the scenario simulation of extreme land use showed that compared with the land use in 2000, the annual runoff of the farmland scenario and the grassland scenario increased by 2.7% and 0.5% respectively, while that of the forest land scenario were reduced by 0.7%, which suggested that forest land had an ability of diversion closure. Furthermore, the scenario simulation of climatic variability indicated that the change of river runoff correlated positively with precipitation change (increase of 11.6% in annual runoff with increase of 10% in annual precipitation) , but negatively with air temperature change (reduction of 0.8% in annual runoff with increase of 1 degrees C in annual mean air temperature), which showed that the impact of precipitation variability was stronger than that of air temperature change. Therefore, in face of climate variability, we need to pay attention to strong rainfall forecasts, optimization of land use structure and spatial distribution, which could reduce the negative hydrological effects (such as floods) induced by 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_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('https://www.osti.gov/pages/biblio/1395318-cloud-feedback-model-intercomparison-project-cfmip-contribution-cmip6','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1395318-cloud-feedback-model-intercomparison-project-cfmip-contribution-cmip6"><span>The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...</p> <p>2017-01-01</p> <p>Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170001441&hterms=robin&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Drobin','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170001441&hterms=robin&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Drobin"><span>The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to 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>Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170001441'); toggleEditAbsImage('author_20170001441_show'); toggleEditAbsImage('author_20170001441_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170001441_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170001441_hide"></p> <p>2017-01-01</p> <p>The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions 'How does the Earth system respond to forcing?' and 'What are the origins and consequences of systematic model biases?' and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity. A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming? CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. 1. How well do clouds and other relevant variables simulated by models agree with observations? 2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models? 3. Which models have the most credible representations of processes relevant to the simulation of clouds? 4. How do clouds and their changes interact with other elements of the climate system?</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1395318','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1395318"><span>The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6</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>Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro</p> <p></p> <p>Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less</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('http://adsabs.harvard.edu/abs/2011CliPD...7.1973H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011CliPD...7.1973H"><span>Tropical climate and vegetation changes during Heinrich Event 1: comparing climate model output to pollen-based vegetation reconstructions with emphasis on the region around the tropical Atlantic Ocean</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>Handiani, D.; Paul, A.; Dupont, L.</p> <p>2011-06-01</p> <p>Abrupt climate changes associated with Heinrich Event 1 (HE1) about 18 to 15 thousand years before present (ka BP) strongly affected climate and vegetation patterns not only in the Northern Hemisphere, but also in tropical regions in the South Atlantic Ocean. We used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era (PI), the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). The HE1-like simulation with a glacial climate background produced sea surface temperature patterns and enhanced interhemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. It allowed us to investigate the vegetation changes that result from a transition to a drier climate as predicted for northern tropical Africa due to a southward shift of the Intertropical Convergence Zone (ITCZ). We found that a cooling of the Northern Hemisphere caused a southward shift of those plant-functional types (PFTs) in Northern Tropical Africa that are indicative of an increased desertification, and a retreat of broadleaf forests in Western Africa and Northern South America. We used the PFTs generated by the model to calculate mega-biomes to allow for a direct comparison between paleodata and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well to the modern and LGM sites of the BIOME6000 (v.4.2) reconstruction, except that our present-day simulation predicted the dominance of grassland in Southern Europe and our LGM simulation simulated more forest cover in tropical and sub-tropical South America. The mega-biomes from the HE1 simulation with glacial background climate were in agreement with paleovegetation data from land and ocean proxies in West, Central, and Northern Tropical Africa as well as Northeast South America. However, our model did not agree well with predicted biome distributions in Eastern South America.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFMGC51A0730L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMGC51A0730L"><span>Validation of the RegCM4-Subgrid module for the high resolution climate simulation over Korea</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>Lee, C.; Im, E.; Chang, K.; Choi, Y.</p> <p>2010-12-01</p> <p>Given the discernable evidences of climate changes due to human activity, there is a growing demand for the reliable climate change scenario in response to future emission forcing. One of the most significant impacts of climate changes can be that on the hydrological process. Changes in the seasonality and the low and high rainfall extremes can influence the water balance of river basin, with several consequences for societies and ecosystems. In fact, recent studies have reported that East Asia including the Korean peninsula is regarded to be a highly vulnerability region under global warming, especially for water resources. As an attempt to accurately assess the impact of climate change over Korea, we developed the dynamical downscaling system using the RegCM4 with a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS). The Sub-BATS system is composed of 20 km coarse-grid cell and 4 km sub-grid cell. Before a full climate change simulation is carried out, we performed the simulation spanning the 19-year periods (1989-2007) with the lateral boundary fields obtained from the ERA-Interim reanalysis. The Korean peninsula is characterized by narrow mountain systems surrounded by ocean, and covered by a relatively dense observational network (approximate 400 stations), which provides an excellent dataset to validate a finescale downscaled results over the region. The evaluation of simulated surface variables (e.g. temperature, precipitation, snow, runoff) shows the usefulness of the RegCM4-Subgrid module as a tool to produce fine scale climate information of surface processes for coupling with hydrological model over the Korean peninsula Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. 2009-0085533), and by the "Advanced research on industrial meteorology" and " Development of meteorological resources for green growth." of National Institute of Meteorological Research (NIMR), funded by the Korea Meteorological Administration(KMA).</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..12.9263C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..12.9263C"><span>Impact of climate change upon vector born diseases in Europe and Africa using ENSEMBLES Regional 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>Caminade, Cyril; Morse, Andy</p> <p>2010-05-01</p> <p>Climate variability is an important component in determining the incidence of a number of diseases with significant human/animal health and socioeconomic impacts. The most important diseases affecting health are vector-borne, such as malaria, Rift Valley Fever and including those that are tick borne, with over 3 billion of the world population at risk. Malaria alone is responsible for at least one million deaths annually, with 80% of malaria deaths occurring in sub-Saharan Africa. The climate has a large impact upon the incidence of vector-borne diseases; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the environmental conditions. A large ensemble of regional climate model simulations has been produced within the ENSEMBLES project framework for both the European and African continent. This work will present recent progress in human and animal disease modelling, based on high resolution climate observations and regional climate simulations. Preliminary results will be given as an illustration, including the impact of climate change upon bluetongue (disease affecting the cattle) over Europe and upon malaria and Rift Valley Fever over Africa. Malaria scenarios based on RCM ensemble simulations have been produced for West Africa. These simulations have been carried out using the Liverpool Malaria Model. Future projections highlight that the malaria incidence decreases at the northern edge of the Sahel and that the epidemic belt is shifted southward in autumn. This could lead to significant public health problems in the future as the demography is expected to dramatically rise over Africa for the 21st century.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC31F1175D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC31F1175D"><span>Can climate models be tuned to simulate the global mean absolute temperature correctly?</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>Duan, Q.; Shi, Y.; Gong, W.</p> <p>2016-12-01</p> <p>The Inter-government Panel on Climate Change (IPCC) has already issued five assessment reports (ARs), which include the simulation of the past climate and the projection of the future climate under various scenarios. The participating models can simulate reasonably well the trend in global mean temperature change, especially of the last 150 years. However, there is a large, constant discrepancy in terms of global mean absolute temperature simulations over this period. This discrepancy remained in the same range between IPCC-AR4 and IPCC-AR5, which amounts to about 3oC between the coldest model and the warmest model. This discrepancy has great implications to the land processes, particularly the processes related to the cryosphere, and casts doubts over if land-atmosphere-ocean interactions are correctly considered in those models. This presentation aims to explore if this discrepancy can be reduced through model tuning. We present an automatic model calibration strategy to tune the parameters of a climate model so the simulated global mean absolute temperature would match the observed data over the last 150 years. An intermediate complexity model known as LOVECLIM is used in the study. This presentation will show the preliminary results.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMGC32B..01P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMGC32B..01P"><span>Inability of CMIP5 Climate Models to Simulate Recent Multi-decadal Climate Change in the Tropical Pacific.</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>Power, S.; Delage, F.; Kociuba, G.; Wang, G.; Smith, I.</p> <p>2017-12-01</p> <p>Observed 15-year surface temperature trends beginning 1998 or later have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short trends, whether they indicate a possible bias in models and the implications for global warming generally. Here we analyse historical and projected changes in 38 CMIP5 climate models. All of the models simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This stark difference cannot be fully explained by observed, internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. We also show that CMIP5 models are not able to simulate the magnitude of the strengthening of the Walker Circulation over the past thirty years. Some of the reasons for these major shortcomings in the ability of models to simulate multi-decadal variability in the Pacific, and the impact these findings have on our confidence in global 21st century projections, will be discussed.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003HyPr...17.3703B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003HyPr...17.3703B"><span>An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)</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>Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain</p> <p>2003-12-01</p> <p>Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.6686M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.6686M"><span>Possible future changes in extreme events over Northern Eurasia</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>Monier, Erwan; Sokolov, Andrei; Scott, Jeffery</p> <p>2013-04-01</p> <p>In this study, we investigate possible future climate change over Northern Eurasia and its impact on extreme events. Northern Eurasia is a major player in the global carbon budget because of boreal forests and peatlands. Circumpolar boreal forests alone contain more than five times the amount of carbon of temperate forests and almost double the amount of carbon of the world's tropical forests. Furthermore, severe permafrost degradation associated with climate change could result in peatlands releasing large amounts of carbon dioxide and methane. Meanwhile, changes in the frequency and magnitude of extreme events, such as extreme precipitation, heat waves or frost days are likely to have substantial impacts on Northern Eurasia ecosystems. For this reason, it is very important to quantify the possible climate change over Northern Eurasia under different emissions scenarios, while accounting for the uncertainty in the climate response and changes in extreme events. For several decades, the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change has been investigating uncertainty in climate change using the MIT Integrated Global System Model (IGSM) framework, an integrated assessment model that couples an earth system model of intermediate complexity (with a 2D zonal-mean atmosphere) to a human activity model. In this study, regional change is investigated using the MIT IGSM-CAM framework that links the IGSM to the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). New modules were developed and implemented in CAM to allow climate parameters to be changed to match those of the IGSM. The simulations presented in this paper were carried out for two emission scenarios, a "business as usual" scenario and a 660 ppm of CO2-equivalent stabilization, which are similar to, respectively, the Representative Concentration Pathways RCP8.5 and RCP4.5 scenarios. Values of climate sensitivity and net aerosol forcing used in the simulations within the IGSM-CAM framework provide a good approximation for the median, and the lower and upper bound of 90% probability distribution of 21st century climate change. Five member ensembles were carried out for each choice of parameters using different initial conditions. With these simulations, we investigate the role of emissions scenarios (climate policies), the global climate response (climate sensitivity) and natural variability (initial conditions) on the uncertainty in future climate changes over Northern Eurasia. A particular emphasis is made on future changes in extreme events, including frost days, extreme summer temperature and extreme summer and winter precipitation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.H13L1759J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.H13L1759J"><span>Future integrated aquifer vulnerability assessment considering land use / land cover and climate change using DRASTIC and SWAT</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>Jang, W.; Engel, B.; Chaubey, I.</p> <p>2015-12-01</p> <p>Climate change causes significant changes to temperature regimes and precipitation patterns across the world. Such alterations in climate pose serious risks for not only inland freshwater ecosystems but also groundwater systems, and may adversely affect numerous critical services they provide to humans. All groundwater results from precipitation, and precipitation is affected by climate change. Climate change is also influenced by land use / land cover (LULC) change and vice versa. According to Intergovernmental Panel on Climate Change (IPCC) reports, climate change is caused by global warming which is generated by the increase of greenhouse gas (GHG) emissions in the atmosphere. LULC change is a major driving factor causing an increase in GHG emissions. LULC change data (years 2006-2100) will be produced by the Land Transformation Model (LTM) which simulates spatial patterns of LULC change over time. MIROC5 (years 2006-2100) will be obtained considering GCMs and ensemble characteristics such as resolution and trend of temperature and precipitation which is a consistency check with observed data from local weather stations and historical data from GCMs output data. Thus, MIROC5 will be used to account for future climate change scenarios and relationship between future climate change and alteration of groundwater quality in this study. For efficient groundwater resources management, integrated aquifer vulnerability assessments (= intrinsic vulnerability + hazard potential assessment) are required. DRASTIC will be used to evaluate intrinsic vulnerability, and aquifer hazard potential will be evaluated by Soil and Water Assessment Tool (SWAT) which can simulate pollution potential from surface and transport properties of contaminants. Thus, for effective integrated aquifer vulnerability assessment for LULC and climate change in the Midwestern United States, future projected LULC and climate data from the LTM and GCMs will be incorporated with DRASTIC and SWAT. It is hypothesized that: 1) long-term future hydrology and water quality in surface and subsurface drainage areas will be influenced by LULC and climate change, and 2) this approach will be useful to identify specific areas contributing the most pollutants to aquifers due to LULC and climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/biblio/1455294-climate-extremes-landclimate-feedbacks-land-use-forcing','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1455294-climate-extremes-landclimate-feedbacks-land-use-forcing"><span>Climate extremes, land–climate feedbacks and land-use forcing at 1.5°C</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>Seneviratne, Sonia I.; Wartenburger, Richard; Guillod, Benoit P.</p> <p></p> <p>This article investigates projected changes in temperature and water cycle extremes at 1.5°C global warming, and highlights the role of land processes and land-use changes (LUC) for these projections. We provide new comparisons of changes in climate at 1.5°C vs 2°C based on empirical sampling analyses of transient simulations vs simulations from the 'Half a degree Additional warming, Prognosis and Projected Impacts' (HAPPI) multi-model experiment. The two approaches yield overall similar results regarding changes in climate extremes on land, and reveal a substantial difference in regional extremes occurrence at 1.5°C vs 2°C. Land processes mediated through soil moisture feedbacks andmore » land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from Integrated Assessment Models (IAMs), which include major LUC in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUC are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1437030-climate-extremes-landclimate-feedbacks-land-use-forcing','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1437030-climate-extremes-landclimate-feedbacks-land-use-forcing"><span>Climate extremes, land–climate feedbacks and land-use forcing at 1.5°C</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Seneviratne, Sonia I.; Wartenburger, Richard; Guillod, Benoit P.; ...</p> <p>2018-04-02</p> <p>Here, this article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated throughmore » soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1437030','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1437030"><span>Climate extremes, land–climate feedbacks and land-use forcing at 1.5°C</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>Seneviratne, Sonia I.; Wartenburger, Richard; Guillod, Benoit P.</p> <p></p> <p>Here, this article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated throughmore » soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways.« less</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5884431','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5884431"><span>The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance 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>Thom, Dominik; Rammer, Werner; Seidl, Rupert</p> <p>2018-01-01</p> <p>Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NHESS..16..757B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NHESS..16..757B"><span>River flood risk in Jakarta under scenarios of future 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>Budiyono, Yus; Aerts, Jeroen C. J. H.; Tollenaar, Daniel; Ward, Philip J.</p> <p>2016-03-01</p> <p>Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the Damagescanner-Jakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability. We estimate baseline flood risk at USD 186 million p.a. Combining all future scenarios, we simulate a median increase in risk of +180 % by 2030. The single driver with the largest contribution to that increase is land subsidence (+126 %). We simulated the impacts of climate change by combining two scenarios of sea level rise with simulations of changes in 1-day extreme precipitation totals from five global climate models (GCMs) forced by the four Representative Concentration Pathways (RCPs). The results are highly uncertain; the median change in risk due to climate change alone by 2030 is a decrease by -46 %, but we simulate an increase in risk under 12 of the 40 GCM-RCP-sea level rise combinations. Hence, we developed probabilistic risk scenarios to account for this uncertainty. If land use change by 2030 takes places according to the official Jakarta Spatial Plan 2030, risk could be reduced by 12 %. However, if land use change in the future continues at the same rate as the last 30 years, large increases in flood risk will take place. Finally, we discuss the relevance of the results for flood risk management in Jakarta.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ESDD....3.1055B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ESDD....3.1055B"><span>Scenario and modelling uncertainty in global mean temperature change derived from emission driven Global 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>Booth, B. B. B.; Bernie, D.; McNeall, D.; Hawkins, E.; Caesar, J.; Boulton, C.; Friedlingstein, P.; Sexton, D.</p> <p>2012-09-01</p> <p>We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission driven rather than concentration driven perturbed parameter ensemble of a Global Climate Model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration driven simulations (with 10-90 percentile ranges of 1.7 K for the aggressive mitigation scenario up to 3.9 K for the high end business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 degrees (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission driven experiments, they do not change existing expectations (based on previous concentration driven experiments) on the timescale that different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration pathways used to drive GCM ensembles lies towards the lower end of our simulated distribution. This design decision (a legecy of previous assessments) is likely to lead concentration driven experiments to under-sample strong feedback responses in concentration driven projections. Our ensemble of emission driven simulations span the global temperature response of other multi-model frameworks except at the low end, where combinations of low climate sensitivity and low carbon cycle feedbacks lead to responses outside our ensemble range. The ensemble simulates a number of high end responses which lie above the CMIP5 carbon cycle range. These high end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real world climate sensitivity constraints which, if achieved, would lead to reductions on the uppper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present day observables and future changes while the large spread of future projected changes, highlights the ongoing need for such work.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26250864','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26250864"><span>Potential impacts of climate change on flow regime and fish habitat in mountain rivers of the south-western Balkans.</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>Papadaki, Christina; Soulis, Konstantinos; Muñoz-Mas, Rafael; Martinez-Capel, Francisco; Zogaris, Stamatis; Ntoanidis, Lazaros; Dimitriou, Elias</p> <p>2016-01-01</p> <p>The climate change in the Mediterranean area is expected to have significant impacts on the aquatic ecosystems and particular in the mountain rivers and streams that often host important species such as the Salmo farioides, Karaman 1938. These impacts will most possibly affect the habitat availability for various aquatic species resulting to an essential alteration of the water requirements, either for dams or other water abstractions, in order to maintain the essential levels of ecological flow for the rivers. The main scope of this study was to assess potential climate change impacts on the hydrological patterns and typical biota for a south-western Balkan mountain river, the Acheloos. The altered flow regimes under different emission scenarios of the Intergovernmental Panel on Climate Change (IPCC) were estimated using a hydrological model and based on regional climate simulations over the study area. The Indicators of Hydrologic Alteration (IHA) methodology was then used to assess the potential streamflow alterations in the studied river due to predicted climate change conditions. A fish habitat simulation method integrating univariate habitat suitability curves and hydraulic modeling techniques were used to assess the impacts on the relationships between the aquatic biota and hydrological status utilizing a sentinel species, the West Balkan trout. The most prominent effects of the climate change scenarios depict severe flow reductions that are likely to occur especially during the summer flows, changing the duration and depressing the magnitude of the natural low flow conditions. Weighted Usable Area-flow curves indicated the limitation of suitable habitat for the native trout. Finally, this preliminary application highlighted the potential of science-based hydrological and habitat simulation approaches that are relevant to both biological quality elements (fish) and current EU Water policy to serve as efficient tools for the estimation of possible climate change impacts on the south-western Balkan river ecosystems. Copyright © 2015 Elsevier B.V. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24299081','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24299081"><span>Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.</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>Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet</p> <p>2013-12-01</p> <p>Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.</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://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://ntrs.nasa.gov/search.jsp?R=20000004374&hterms=climate+change+anthropogenic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dclimate%2Bchange%2Banthropogenic','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000004374&hterms=climate+change+anthropogenic&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dclimate%2Bchange%2Banthropogenic"><span>Climate Simulations of Past, Present and Future</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 forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BGeo...15.1947G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BGeo...15.1947G"><span>Plant functional diversity affects climate-vegetation interaction</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>Groner, Vivienne P.; Raddatz, Thomas; Reick, Christian H.; Claussen, Martin</p> <p>2018-04-01</p> <p>We present how variations in plant functional diversity affect climate-vegetation interaction towards the end of the African Humid Period (AHP) in coupled land-atmosphere simulations using the Max Planck Institute Earth system model (MPI-ESM). In experiments with AHP boundary conditions, the extent of the <q>green</q> Sahara varies considerably with changes in plant functional diversity. Differences in vegetation cover extent and plant functional type (PFT) composition translate into significantly different land surface parameters, water cycling, and surface energy budgets. These changes have not only regional consequences but considerably alter large-scale atmospheric circulation patterns and the position of the tropical rain belt. Towards the end of the AHP, simulations with the standard PFT set in MPI-ESM depict a gradual decrease of precipitation and vegetation cover over time, while simulations with modified PFT composition show either a sharp decline of both variables or an even slower retreat. Thus, not the quantitative but the qualitative PFT composition determines climate-vegetation interaction and the climate-vegetation system response to external forcing. The sensitivity of simulated system states to changes in PFT composition raises the question how realistically Earth system models can actually represent climate-vegetation interaction, considering the poor representation of plant diversity in the current generation of land surface models.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMNH23B1860W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMNH23B1860W"><span>Impact assessment of climate change on tourism in the Pacific small islands based on the database of long-term high-resolution climate ensemble experiments</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>Watanabe, S.; Utsumi, N.; Take, M.; Iida, A.</p> <p>2016-12-01</p> <p>This study aims to develop a new approach to assess the impact of climate change on the small oceanic islands in the Pacific. In the new approach, the change of the probabilities of various situations was projected with considering the spread of projection derived from ensemble simulations, instead of projecting the most probable situation. The database for Policy Decision making for Future climate change (d4PDF) is a database of long-term high-resolution climate ensemble experiments, which has the results of 100 ensemble simulations. We utilized the database for Policy Decision making for Future climate change (d4PDF), which was (a long-term and high-resolution database) composed of results of 100 ensemble experiments. A new methodology, Multi Threshold Ensemble Assessment (MTEA), was developed using the d4PDF in order to assess the impact of climate change. We focused on the impact of climate change on tourism because it has played an important role in the economy of the Pacific Islands. The Yaeyama Region, one of the tourist destinations in Okinawa, Japan, was selected as the case study site. Two kinds of impact were assessed: change in probability of extreme climate phenomena and tourist satisfaction associated with weather. The database of long-term high-resolution climate ensemble experiments and the questionnaire survey conducted by a local government were used for the assessment. The result indicated that the strength of extreme events would be increased, whereas the probability of occurrence would be decreased. This change should result in increase of the number of clear days and it could contribute to improve the tourist satisfaction.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.B31G..05K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.B31G..05K"><span>Assessing Potential Future Carbon Dynamics with Climate Change and Fire Management in a Mountainous Landscape on the Olympic Peninsula, Washington, USA</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>Kennedy, R. S.</p> <p>2010-12-01</p> <p>Forests of the mountainous landscapes of the maritime Pacific Northwestern USA may have high carbon sequestration potential via their high productivity and moderate to infrequent fire regimes. With climate change, there may be shifts in incidence and severity of fire, especially in the drier areas of the region, via changes to forest productivity and hydrology, and consequent effects to C sequestration and forest structure. To explore this issue, I assessed potential effects of fire management (little fire suppression/wildland fire management/highly effective fire suppression) under two climate change scenarios on future C sequestration dynamics (amounts and spatial pattern) in Olympic National Park, WA, over a 500-year simulation period. I used the simulation platform FireBGCv2, which contains a mechanistic, individual tree succession model, a spatially explicit climate-based biophysical model that uses daily weather data, and a spatially explicit fire model incorporating ignition, spread, and effects on ecosystem components. C sequestration patterns varied over time and spatial and temporal patterns differed somewhat depending on the climate change scenario applied and the fire management methods employed. Under the more extreme climate change scenario with little fire suppression, fires were most frequent and severe and C sequestration decreased. General trends were similar under the more moderate climate change scenario, as compared to current climate, but spatial patterns differed. Both climate change scenarios under highly effective fire suppression showed about 50% of starting total C after the initial transition phase, whereas with 10% fire suppression both scenarios exhibited about 10% of starting amounts. Areas of the landscape that served as refugia for older forest under increasing frequency of high severity fire were also hotspots for C sequestration in a landscape experiencing increasing frequency of disturbance with climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27398619','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27398619"><span>Evidence for climate change in the satellite cloud record.</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>Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A</p> <p>2016-08-04</p> <p>Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016Natur.536...72N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016Natur.536...72N"><span>Evidence for climate change in the satellite cloud 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>Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.</p> <p>2016-08-01</p> <p>Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900048091&hterms=pollution+climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpollution%2Bclimate%2Bchange','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900048091&hterms=pollution+climate+change&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpollution%2Bclimate%2Bchange"><span>Global climate change and US agriculture</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>Adams, Richard M.; Rosenzweig, Cynthia; Peart, Robert M.; Ritchie, Joe T.; Mccarl, Bruce A.</p> <p>1990-01-01</p> <p>Agricultural productivity is expected to be sensitive to global climate change. Models from atmospheric science, plant science, and agricultural economics are linked to explore this sensitivity. Although the results depend on the severity of climate change and the compensating effects of carbon dioxide on crop yields, the simulation suggests that irrigated acreage will expand and regional patterns of U.S. agriculture will shift. The impact of the U.S. economy strongly depends on which climate model is used.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H32E..07M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H32E..07M"><span>Simulation of future land use change and climate change impacts on hydrological processes in a tropical catchment</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>Marhaento, H.; Booij, M. J.; Hoekstra, A. Y.</p> <p>2017-12-01</p> <p>Future hydrological processes in the Samin catchment (278 km2) in Java, Indonesia have been simulated using the Soil and Water Assessment Tool (SWAT) model using inputs from predicted land use distributions in the period 2030 - 2050, bias corrected Regional Climate Model (RCM) output and output of six Global Climate Models (GCMs) to include climate model uncertainty. Two land use change scenarios namely a business-as-usual (BAU) scenario, where no measures are taken to control land use change, and a controlled (CON) scenario, where the future land use follows the land use planning, were used in the simulations together with two climate change scenarios namely Representative Concentration Pathway (RCP) 4.5 and 8.5. It was predicted that in 2050 settlement and agriculture area of the study catchment will increase by 33.9% and 3.5%, respectively under the BAU scenario, whereas agriculture area and evergreen forest will increase by 15.2% and 10.2%, respectively under the CON scenario. In comparison to the baseline conditions (1983 - 2005), the predicted mean annual maximum and minimum temperature in 2030 - 2050 will increase by an average of +10C, while changes in the mean annual rainfall range from -20% to +19% under RCP 4.5 and from -25% to +15% under RCP 8.5. The results show that land use change and climate change individually will cause changes in the water balance components, but that more pronounced changes are expected if the drivers are combined, in particular for changes in annual stream flow and surface runoff. It was observed that combination of the RCP 4.5 climate scenario and BAU land use scenario resulted in an increase of the mean annual stream flow from -7% to +64% and surface runoff from +21% to +102%, which is 40% and 60% more than when land use change is acting alone. Furthermore, under the CON scenario the annual stream flow and surface runoff could be potentially reduced by up to 10% and 30%, respectively indicating the effectiveness of applied land use planning. The findings of this study will be useful for the water resource managers to mitigate future risks associated with land use and climate changes in the study catchment. Keywords: land use change, climate change, hydrological impact assessment, Samin catchment</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917427B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917427B"><span>Water resources sensitivity to the isolated effects of land use, water demand and climate change under 2 degree 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>Bisselink, Berny; Bernhard, Jeroen; de Roo, Ad</p> <p>2017-04-01</p> <p>One of the key impacts of global change are the future water resources. These water resources are influenced by changes in land use (LU), water demand (WD) and climate change. Recent developments in scenario modelling opened new opportunities for an integrated assessment. However, for identifying water resource management strategies it is helpful to focus on the isolated effects of possible changes in LU, WD and climate that may occur in the near future. In this work, we quantify the isolated contribution of LU, WD and climate to the integrated total water resources assuming a linear model behavior. An ensemble of five EURO-CORDEX RCP8.5 climate projections for the 31-year periods centered on the year of exceeding the global-mean temperature of 2 degree is used to drive the fully distributed hydrological model LISFLOOD for multiple river catchments in Europe. The JRC's Land Use Modelling Platform LUISA was used to obtain a detailed pan-European reference land use scenario until 2050. Water demand is estimated based on socio-economic (GDP, population estimates etc.), land use and climate projections as well. For each climate projection, four model runs have been performed including an integrated (LU, WD and climate) simulation and other three simulations to isolate the effect of LU, WD and climate. Changes relative to the baseline in terms of water resources indicators of the ensemble means of the 2 degree warming period and their associated uncertainties will reveal the integrated and isolated effect of LU, WD and climate change on water resources.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..1611080B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..1611080B"><span>New insights for the hydrology of the Rhine based on the new generation 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>Bouaziz, Laurène; Sperna Weiland, Frederiek; Beersma, Jules; Buiteveld, Hendrik</p> <p>2014-05-01</p> <p>Decision makers base their choices of adaptation strategies on climate change projections and their associated hydrological consequences. New insights of climate change gained under the new generation of climate models belonging to the IPCC 5th assessment report may influence (the planning of) adaption measures and/or future expectations. In this study, hydrological impacts of climate change as projected under the new generation of climate models for the Rhine were assessed. Hereto we downscaled 31 General Circulation Models (GCMs), which were developed as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5), using an advanced Delta Change Method for the Rhine basin. Changes in mean monthly, maximum and minimum flows at Lobith were derived with the semi-distributed hydrological model HBV of the Rhine. The projected changes were compared to changes that were previously obtained in the trans-boundary project Rheinblick using eight CMIP3 GCMs and Regional Climate Models (RCMs) for emission scenario A1B. All eight selected CMIP3 models (scenario A1B) predicted for 2071-2100 a decrease in mean monthly flows between June and October. Similar decreases were found for some of the 31 CMIP5 models for Representative Concentration Pathways (RCPs) 4.5, 6.0 and 8.5. However, under each RCP, there were also models that projected an increase in mean flows between June and October and on average the decrease was smaller than for the eight CMIP3 models. For 2071-2100, also the mean annual minimum 7-days discharge decreased less in the CMIP5 model simulations than was projected in CMIP3. When assessing the response of mean monthly flows of the CMIP5 simulation with the CSIRO-Mk3-6-0 and HadGEM2-ES models with respect to initial conditions and RCPs, it was found that natural variability plays a dominant role in the near future (2021-2050), while changes in mean monthly flows are dominated by the radiative forcing in the far future (2071-2100). According to RCP 8.5 model simulations, the change in mean monthly flow from May to November may be half the change in mean monthly flow projected by RCP 4.5. From January to March, RCP 8.5 simulations projected higher changes in mean monthly flows than RCP 4.5 simulations. These new insights based on the CMIP5 simulations imply that for the Rhine, the mean and low flow extremes might not decrease as much in summer as was expected under CMIP3. Stresses on water availability during summer are therefore also less than expected from CMIP3.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCC...7..823W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCC...7..823W"><span>Habitat-based conservation strategies cannot compensate for climate-change-induced range loss</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>Wessely, Johannes; Hülber, Karl; Gattringer, Andreas; Kuttner, Michael; Moser, Dietmar; Rabitsch, Wolfgang; Schindler, Stefan; Dullinger, Stefan; Essl, Franz</p> <p>2017-11-01</p> <p>Anthropogenic habitat fragmentation represents a major obstacle to species shifting their range in response to climate change. Conservation measures to increase the (meta-)population capacity and permeability of landscapes may help but the effectiveness of such measures in a warming climate has rarely been evaluated. Here, we simulate range dynamics of 51 species from three taxonomic groups (vascular plants, butterflies and grasshoppers) in Central Europe as driven by twenty-first-century climate scenarios and analyse how three habitat-based conservation strategies (establishing corridors, improving the landscape matrix, and protected area management) modify species' projected range size changes. These simulations suggest that the conservation strategies considered are unable to save species from regional extinction. For those persisting, they reduce the magnitude of range loss in lowland but not in alpine species. Protected area management and corridor establishment are more effective than matrix improvement. However, none of the conservation strategies evaluated could fully compensate the negative impact of climate change for vascular plants, butterflies or grasshoppers in central Europe.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012BGD.....9.7601F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012BGD.....9.7601F"><span>Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C earth system 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>Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.</p> <p>2012-06-01</p> <p>The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in scrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during winter and spring); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during summer), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during winter and spring) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012BGeo....9.4739F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012BGeo....9.4739F"><span>Role of vegetation change in future climate under the A1B scenario and a climate stabilisation scenario, using the HadCM3C Earth system 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>Falloon, P. D.; Dankers, R.; Betts, R. A.; Jones, C. D.; Booth, B. B. B.; Lambert, F. H.</p> <p>2012-11-01</p> <p>The aim of our study was to use the coupled climate-carbon cycle model HadCM3C to quantify climate impact of ecosystem changes over recent decades and under future scenarios, due to changes in both atmospheric CO2 and surface albedo. We use two future scenarios - the IPCC SRES A1B scenario, and a climate stabilisation scenario (2C20), allowing us to assess the impact of climate mitigation on results. We performed a pair of simulations under each scenario - one in which vegetation was fixed at the initial state and one in which vegetation changes dynamically in response to climate change, as determined by the interactive vegetation model within HadCM3C. In our simulations with interactive vegetation, relatively small changes in global vegetation coverage were found, mainly dominated by increases in shrub and needleleaf trees at high latitudes and losses of broadleaf trees and grasses across the Amazon. Globally this led to a loss of terrestrial carbon, mainly from the soil. Global changes in carbon storage were related to the regional losses from the Amazon and gains at high latitude. Regional differences in carbon storage between the two scenarios were largely driven by the balance between warming-enhanced decomposition and altered vegetation growth. Globally, interactive vegetation reduced albedo acting to enhance albedo changes due to climate change. This was mainly related to the darker land surface over high latitudes (due to vegetation expansion, particularly during December-January and March-May); small increases in albedo occurred over the Amazon. As a result, there was a relatively small impact of vegetation change on most global annual mean climate variables, which was generally greater under A1B than 2C20, with markedly stronger local-to-regional and seasonal impacts. Globally, vegetation change amplified future annual temperature increases by 0.24 and 0.15 K (under A1B and 2C20, respectively) and increased global precipitation, with reductions in precipitation over the Amazon and increases over high latitudes. In general, changes were stronger over land - for example, global temperature changes due to interactive vegetation of 0.43 and 0.28 K under A1B and 2C20, respectively. Regionally, the warming influence of future vegetation change in our simulations was driven by the balance between driving factors. For instance, reduced tree cover over the Amazon reduced evaporation (particularly during June-August), outweighing the cooling influence of any small albedo changes. In contrast, at high latitudes the warming impact of reduced albedo (particularly during December-February and March-May) due to increased vegetation cover appears to have offset any cooling due to small evaporation increases. Climate mitigation generally reduced the impact of vegetation change on future global and regional climate in our simulations. Our study therefore suggests that there is a need to consider both biogeochemical and biophysical effects in climate adaptation and mitigation decision making.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy..tmp.2286C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy..tmp.2286C"><span>Projected changes in extreme precipitation over Scotland and Northern England using a high-resolution regional climate 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>Chan, Steven C.; Kahana, Ron; Kendon, Elizabeth J.; Fowler, Hayley J.</p> <p>2018-03-01</p> <p>The UK Met Office has previously conducted convection-permitting climate simulations over the southern UK (Kendon et al. in Nat Clim Change 4:570-576, 2014). The southern UK simulations have been followed up by a new set of northern UK simulations using the same model configuration. Here we present the mean and extreme precipitation projections from these new simulations. Relative to the southern UK, the northern UK projections show a greater summertime increase of return levels and extreme precipitation intensity in both 1.5 km convection-permitting and 12 km convection-parameterised simulations, but this increase is against a backdrop of large decreases in summertime mean precipitation and precipitation frequency. Similar to the southern UK, projected change is model resolution dependent and the convection-permitting simulation projects a larger intensification. For winter, return level increases are somewhat lower than for the southern UK. Analysis of model biases highlight challenges in simulating the diurnal cycle over high terrain, sensitivity to domain size and driving-GCM biases, and quality issues of radar precipitation observations, which are relevant to the wider regional climate modelling community.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://dx.doi.org/10.1111/j.1523-1739.2011.01684.x','USGSPUBS'); return false;" href="http://dx.doi.org/10.1111/j.1523-1739.2011.01684.x"><span>Understanding interaction effects of climate change and fire management on bird distributions through combined process and habitat models</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>White, Joseph D.; Gutzwiller, Kevin J.; Barrow, Wylie C.; Johnson-Randall, Lori; Zygo, Lisa; Swint, Pamela</p> <p>2011-01-01</p> <p>Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process-based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf-area index values were lower in shrubland. This high probability of occurrence likely is related to the species' use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70033997','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70033997"><span>Understanding interaction effects of climate change and fire management on bird distributions through combined process and habitat models</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>White, Joseph D.; Gutzwiller, Kevin J.; Barrow, Wylie C.; Johnson-Randall, Lori; Zygo, Lisa; Swint, Pamela</p> <p>2011-01-01</p> <p>Avian conservation efforts must account for changes in vegetation composition and structure associated with climate change. We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process-based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf-area index values were lower in shrubland. This high probability of occurrence likely is related to the species' use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes. ??2011 Society for Conservation Biology.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://eric.ed.gov/?q=business+AND+management+AND+topics&pg=5&id=EJ976565','ERIC'); return false;" href="https://eric.ed.gov/?q=business+AND+management+AND+topics&pg=5&id=EJ976565"><span>More than a Game: Learning about Climate Change through Role-Play</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>Paschall, Melissa; Wustenhagen, Rolf</p> <p>2012-01-01</p> <p>Educating management students on the connections between business and climate change is essential both to their careers and to society's ability to solve the climate challenge. To impart deep and lasting learning on this topic, the authors developed a multischool negotiation simulation that is unique in its intensiveness, cross-sector design, and…</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=307542&keyword=national+AND+parks&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=307542&keyword=national+AND+parks&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>Simulating future climate and land-use impacts on at-risk species in parks and protected areas</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>Alpine and sagebrush ecosystems in the mountain west are under threat from climate change and development. The wolverine, fisher, greater sage-grouse,and pygmy rabbit are iconic at-risk species in the region. We explore the impacts of future climate and land-use change on these s...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=242011&keyword=Lamb&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=242011&keyword=Lamb&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>Evaluating the effects of climate change on summertime ozone using a relative reduction factor approach for policymakers</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>The impact of climate change on surface-level ozone is examined through a multiscale modeling effort that linked global and regional climate models to drive air quality model simulations. Results are quantified in terms of the relative response factor (RRFE), which estimates the ...</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('https://www.ncbi.nlm.nih.gov/pubmed/26374998','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26374998"><span>Novel competitors shape species' 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>Alexander, Jake M; Diez, Jeffrey M; Levine, Jonathan M</p> <p>2015-09-24</p> <p>Understanding how species respond to climate change is critical for forecasting the future dynamics and distribution of pests, diseases and biological diversity. Although ecologists have long acknowledged species' direct physiological and demographic responses to climate, more recent work suggests that these direct responses can be overwhelmed by indirect effects mediated via other interacting community members. Theory suggests that some of the most dramatic impacts of community change will probably arise through the assembly of novel species combinations after asynchronous migrations with climate. Empirical tests of this prediction are rare, as existing work focuses on the effects of changing interactions between competitors that co-occur today. To explore how species' responses to climate warming depend on how their competitors migrate to track climate, we transplanted alpine plant species and intact plant communities along a climate gradient in the Swiss Alps. Here we show that when alpine plants were transplanted to warmer climates to simulate a migration failure, their performance was strongly reduced by novel competitors that could migrate upwards from lower elevation; these effects generally exceeded the impact of warming on competition with current competitors. In contrast, when we grew the focal plants under their current climate to simulate climate tracking, a shift in the competitive environment to novel high-elevation competitors had little to no effect. This asymmetry in the importance of changing competitor identity at the leading versus trailing range edges is best explained by the degree of functional similarity between current and novel competitors. We conclude that accounting for novel competitive interactions may be essential to predict species' responses to climate change accurately.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70194838','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70194838"><span>Co-producing simulation models to inform resource management: a case study from southwest South Dakota</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>Miller, Brian W.; Symstad, Amy J.; Frid, Leonardo; Fisichelli, Nicholas A.; Schuurman, Gregor W.</p> <p>2017-01-01</p> <p>Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://edcintl.cr.usgs.gov/ip/lca_fact_sheet/lca_factsheet.pdf','USGSPUBS'); return false;" href="http://edcintl.cr.usgs.gov/ip/lca_fact_sheet/lca_factsheet.pdf"><span>Land Cover Applications, Landscape Dynamics, and Global Change</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>Tieszen, Larry L.</p> <p>2007-01-01</p> <p>The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMGC13C1209E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMGC13C1209E"><span>Future Climate Change Impact Assessment of River Flows at Two Watersheds of Peninsular Malaysia</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>Ercan, A.; Ishida, K.; Kavvas, M. L.; Chen, Z. R.; Jang, S.; Amin, M. Z. M.; Shaaban, A. J.</p> <p>2016-12-01</p> <p>Impacts of climate change on the river flows under future climate change conditions were assessed over Muda and Dungun watersheds of Peninsular Malaysia by means of a coupled regional climate model and a physically-based hydrology model utilizing an ensemble of 15 different future climate realizations. Coarse resolution GCMs' future projections covering a wide range of emission scenarios were dynamically downscaled to 6 km resolution over the study area. Hydrologic simulations of the two selected watersheds were carried out at hillslope-scale and at hourly increments.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ThApC.tmp..145A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ThApC.tmp..145A"><span>Performance of the general circulation models in simulating temperature and precipitation over Iran</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>Abbasian, Mohammadsadegh; Moghim, Sanaz; Abrishamchi, Ahmad</p> <p>2018-03-01</p> <p>General Circulation Models (GCMs) are advanced tools for impact assessment and climate change studies. Previous studies show that the performance of the GCMs in simulating climate variables varies significantly over different regions. This study intends to evaluate the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs in simulating temperature and precipitation over Iran. Simulations from 37 GCMs and observations from the Climatic Research Unit (CRU) were obtained for the period of 1901-2005. Six measures of performance including mean bias, root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), linear correlation coefficient (r), Kolmogorov-Smirnov statistic (KS), Sen's slope estimator, and the Taylor diagram are used for the evaluation. GCMs are ranked based on each statistic at seasonal and annual time scales. Results show that most GCMs perform reasonably well in simulating the annual and seasonal temperature over Iran. The majority of the GCMs have a poor skill to simulate precipitation, particularly at seasonal scale. Based on the results, the best GCMs to represent temperature and precipitation simulations over Iran are the CMCC-CMS (Euro-Mediterranean Center on Climate Change) and the MRI-CGCM3 (Meteorological Research Institute), respectively. The results are valuable for climate and hydrometeorological studies and can help water resources planners and managers to choose the proper GCM based on their criteria.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/43705','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/43705"><span>Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change</span></a></p> <p><a target="_blank" rel="noopener noreferrer" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Anantha M. Prasad; Judith D. Gardiner; Louis R. Iverson; Stephen N. Matthews; Matthew Peters</p> <p>2013-01-01</p> <p>Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new...</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A43G0387S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A43G0387S"><span>Impacts of Ozone-vegetation Interactions and Biogeochemical Feedbacks on Atmospheric Composition and Air Quality 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>Sadeke, M.; Tai, A. P. K.; Lombardozzi, D.; Val Martin, M.</p> <p>2015-12-01</p> <p>Surface ozone pollution is one of the major environmental concerns due to its damaging effects on human and vegetation. One of the largest uncertainties of future surface ozone prediction comes from its interaction with vegetation under a changing climate. Ozone can be modulated by vegetation through, e.g., biogenic emissions, dry deposition and transpiration. These processes are in turn affected by chronic exposure to ozone via lowered photosynthesis rate and stomatal conductance. Both ozone and vegetation growth are expected to be altered by climate change. To better understand these climate-ozone-vegetation interactions and possible feedbacks on ozone itself via vegetation, we implement an online ozone-vegetation scheme [Lombardozzi et al., 2015] into the Community Earth System Model (CESM) with active atmospheric chemistry, climate and land surface components. Previous overestimation of surface ozone in eastern US, Canada and Europe is shown to be reduced by >8 ppb, reflecting improved model-observation comparison. Simulated surface ozone is lower by 3.7 ppb on average globally. Such reductions (and improvements) in simulated ozone are caused mainly by lower isoprene emission arising from reduced leaf area index in response to chronic ozone exposure. Effects via transpiration are also potentially significant but require better characterization. Such findings suggest that ozone-vegetation interaction may substantially alter future ozone simulations, especially under changing climate and ambient CO2 levels, which would further modulate ozone-vegetation interactions. Inclusion of such interactions in Earth system models is thus necessary to give more realistic estimation and prediction of surface ozone. This is crucial for better policy formulation regarding air quality, land use and climate change mitigation. Reference list: Lombardozzi, D., et al. "The Influence of Chronic Ozone Exposure on Global Carbon and Water Cycles." Journal of Climate 28.1 (2015): 292-305.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMGC21A0802O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMGC21A0802O"><span>Attribution of changes in precipitation patterns in African rainforests</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, F. E.; Jones, R. G.; Halladay, K.; Allen, M. R.</p> <p>2013-12-01</p> <p>The effects of projected future global and regional climate change on the water cycle and thus on global water security are amongst the most economically and politically important challenges that society faces in the 21st century. The provision of secure access to water resources and the protection of communities from water-related risks have emerged as top priorities amongst policymakers within the public and private sectors alike. Investment decisions on water infrastructure rely heavily on quantitative assessments of risks and uncertainties associated with future changes in water-related threats. Especially with the introduction of loss and damages on the agenda of the UNFCCC additionally the attribution of such changes to anthropogenic climate change and other external climate drivers is crucial. Probabilistic event attribution (PEA) provides a method of evaluating the extent to which human-induced climate change is affecting localised weather events and impacts of such events that relies on good observations as well as climate modelling. The overall approach is to simulate both, the statistics of observed weather, and the statistics of the weather that would have occurred had specific external drivers of climate change been absent. The majority of studies applying PEA have focused on quantifying attributable risk, with changes in risk depending on an assumption of 'all other things being equal', including natural drivers of climate change and vulnerability. Most previous attribution studies have focused on European extreme weather events, but the most vulnerable regions to climate change are in Asia and Africa. One of the most complex hydrological systems is the tropical rainforest, with the rainforests in tropical Africa being some of the most under-researched regions in the world. Research in the Amazonian rainforest suggests potential vulnerability to climate change. We will present results from using the large ensemble of atmosphere-only general circulation model (AGCM) simulations within the weather@home project, and analysing statistics of precipitation in the dry season of the Congo Basin rainforests. Because observed data sets in that region are of very poor quality we show how validation methods not only relying on such data have been used to investigate the applicability of PEA analysis from large model ensembles to this tropical region. Additionally we will present results for the same region but generated with a very large ensemble of regional climate simulations which allows analysing the importance of a realistic simulation of small scale precipitation processes for attribution studies in a tropical climate. We highlight that PEA analysis has the potential to provide valuable scientific evidence of recent or anticipated climatological changes in the water cycle, especially in regions with sparse observational data and unclear projections of future changes. However, the strong influence of SST tele-connection patterns on tropical precipitation provides more challenges in the set-up of attribution studies than studies on mid-latitude rainfall.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFMGC24A..07S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC24A..07S"><span>Past and Future Climate Change Impacts on Mountain Forests on the Olympic Peninsula (Washington, USA)</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>Schwörer, C.; Fisher, D. M.; Gavin, D. G.; Temperli, C.; Bartlein, P. J.</p> <p>2015-12-01</p> <p>Mountain forest composition and distribution is strongly affected by temperature and is expected to shift to higher elevations with climate change. However, warmer winters will also lead to an upward shift of the snowline and a decrease in snowpack at lower and intermediate elevations. In the mountain ranges of Western North America, snowpack plays an important role in providing additional moisture during the dry summer months. It is therefore unclear if the projected climate change will lead to a rise of subalpine forest due to a longer growing season or a contraction due to drought stress. Since forest succession processes take place over decades and centuries we use LandClim, a dynamic vegetation model, to assess the impact of climate change on mountain forests on the Olympic Peninsula (Washington, USA). As a reality check we first simulate vegetation dynamics since the last Ice Age and compare model output with paleobotanical data from five natural archives that span the topographic and climatic gradients on the Peninsula. LandClim produces realistic present-day species compositions with respect to elevation and precipitation gradients. Moreover, the simulations of forest dynamics for the last 16,000 years generally agree with the pollen and macrofossil data. We then simulated mountain forests under future climate projections. As a result, our model indicates drastic changes in species composition with a replacement of mountain hemlock (Tsuga mertensiana) by more drought-resistant species such as subalpine fir (Abies lasiocarpa). On the drier, eastern side of the Peninsula, the model even suggests a lowering of timberline due to insufficient moisture availability in shallow alpine soils. Our results have important implications for ecosystem managers and stress the urgency of climate change mitigation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC24A..04S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC24A..04S"><span>Uncertainties in Past and Future Global Water Availability</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>Sheffield, J.; Kam, J.</p> <p>2014-12-01</p> <p>Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23925864','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23925864"><span>The potential effects of climate change on the distribution and productivity of Cunninghamia lanceolata in China.</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>Liu, Yupeng; Yu, Deyong; Xun, Bin; Sun, Yun; Hao, Ruifang</p> <p>2014-01-01</p> <p>Climate changes may have immediate implications for forest productivity and may produce dramatic shifts in tree species distributions in the future. Quantifying these implications is significant for both scientists and managers. Cunninghamia lanceolata is an important coniferous timber species due to its fast growth and wide distribution in China. This paper proposes a methodology aiming at enhancing the distribution and productivity of C. lanceolata against a background of climate change. First, we simulated the potential distributions and establishment probabilities of C. lanceolata based on a species distribution model. Second, a process-based model, the PnET-II model, was calibrated and its parameterization of water balance improved. Finally, the improved PnET-II model was used to simulate the net primary productivity (NPP) of C. lanceolata. The simulated NPP and potential distribution were combined to produce an integrated indicator, the estimated total NPP, which serves to comprehensively characterize the productivity of the forest under climate change. The results of the analysis showed that (1) the distribution of C. lanceolata will increase in central China, but the mean probability of establishment will decrease in the 2050s; (2) the PnET-II model was improved, calibrated, and successfully validated for the simulation of the NPP of C. lanceolata in China; and (3) all scenarios predicted a reduction in total NPP in the 2050s, with a markedly lower reduction under the a2 scenario than under the b2 scenario. The changes in NPP suggested that forest productivity will show a large decrease in southern China and a mild increase in central China. All of these findings could improve our understanding of the impact of climate change on forest ecosystem structure and function and could provide a basis for policy-makers to apply adaptive measures and overcome the unfavorable influences of climate change.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.9768A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.9768A"><span>The variability of runoff and soil erosion in the Brazilian Cerrado biome due to the potential land use and climate changes</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>Alexandre Ayach Anache, Jamil; Wendland, Edson; Malacarne Pinheiro Rosalem, Lívia; Srivastava, Anurag; Flanagan, Dennis</p> <p>2017-04-01</p> <p>Changes in land use and climate can influence runoff and soil loss, threatening soil and water conservation in the Cerrado biome in Brazil. Due to the lack of long term observed data for runoff and soil erosion in Brazil, the adoption of a process-based model was necessary, representing the variability of both variables in a continuous simulation approach. Thus, we aimed to calibrate WEPP (Water Erosion Prediction Project) model for different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane) under subtropical conditions inside the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change scenarios. We performed the model calibration using a 4-year dataset of observed runoff and soil loss in four different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane). The WEPP model components (climate, topography, soil, and management) were calibrated according to field data. However, soil and management were optimized according to each land use using a parameter estimation tool. The observations were conducted between 2012 and 2015 in experimental plots (5 m width, 20 m length, 9% slope gradient, 3 replicates per treatment). The simulations were done using the calibrated WEPP model components, but changing the 4-year observed climate file by a 100-year dataset created with CLIGEN (weather generator) based on regional climate statistics. Afterwards, using MarkSim DSSAT Weather File Generator, runoff and soil loss were simulated using future climate scenarios for 2030, 2060, and 2090. To analyze the data, we used non-parametric statistics as data do not follow normal distribution. The results show that WEPP model had an acceptable performance for the considered conditions. In addition, both land use and climate can influence on runoff and soil loss rates. Potential climate changes which consider the increase of rainfall intensities and depths in the studied region may increase the variability and rates for runoff and soil erosion. However, the climate did not change the differences and similarities between the rates of the four analyzed land uses. The runoff behavior is distinct for all land uses, but for soil loss we found similarities between pasture and undisturbed Cerrado, suggesting that soil sustainability could be reached when the management follows conservation principles.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21145634','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21145634"><span>A dynamic modelling approach for estimating critical loads of nitrogen based on plant community changes under 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>Belyazid, Salim; Kurz, Dani; Braun, Sabine; Sverdrup, Harald; Rihm, Beat; Hettelingh, Jean-Paul</p> <p>2011-03-01</p> <p>A dynamic model of forest ecosystems was used to investigate the effects of climate change, atmospheric deposition and harvest intensity on 48 forest sites in Sweden (n = 16) and Switzerland (n = 32). The model was used to investigate the feasibility of deriving critical loads for nitrogen (N) deposition based on changes in plant community composition. The simulations show that climate and atmospheric deposition have comparably important effects on N mobilization in the soil, as climate triggers the release of organically bound nitrogen stored in the soil during the elevated deposition period. Climate has the most important effect on plant community composition, underlining the fact that this cannot be ignored in future simulations of vegetation dynamics. Harvest intensity has comparatively little effect on the plant community in the long term, while it may be detrimental in the short term following cutting. This study shows: that critical loads of N deposition can be estimated using the plant community as an indicator; that future climatic changes must be taken into account; and that the definition of the reference deposition is critical for the outcome of this estimate. Copyright © 2010 Elsevier Ltd. All rights reserved.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4186761','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4186761"><span>Investigation of Climate Change Impact on Water Resources for an Alpine Basin in Northern Italy: Implications for Evapotranspiration Modeling Complexity</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>Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco</p> <p>2014-01-01</p> <p>Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required beacause of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied. PMID:25285917</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25285917','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25285917"><span>Investigation of climate change impact on water resources for an Alpine basin in northern Italy: implications for evapotranspiration modeling complexity.</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>Ravazzani, Giovanni; Ghilardi, Matteo; Mendlik, Thomas; Gobiet, Andreas; Corbari, Chiara; Mancini, Marco</p> <p>2014-01-01</p> <p>Assessing the future effects of climate change on water availability requires an understanding of how precipitation and evapotranspiration rates will respond to changes in atmospheric forcing. Use of simplified hydrological models is required because of lack of meteorological forcings with the high space and time resolutions required to model hydrological processes in mountains river basins, and the necessity of reducing the computational costs. The main objective of this study was to quantify the differences between a simplified hydrological model, which uses only precipitation and temperature to compute the hydrological balance when simulating the impact of climate change, and an enhanced version of the model, which solves the energy balance to compute the actual evapotranspiration. For the meteorological forcing of future scenario, at-site bias-corrected time series based on two regional climate models were used. A quantile-based error-correction approach was used to downscale the regional climate model simulations to a point scale and to reduce its error characteristics. The study shows that a simple temperature-based approach for computing the evapotranspiration is sufficiently accurate for performing hydrological impact investigations of climate change for the Alpine river basin which was studied.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.1464P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.1464P"><span>Hydrological Assessment of Model Performance and Scenario Analyses of Land Use Change and Climate Change in lowlands of Veneto Region (Italy)</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>Pijl, Anton; Brauer, Claudia; Sofia, Giulia; Teuling, Ryan; Tarolli, Paolo</p> <p>2017-04-01</p> <p>Growing water-related challenges in lowland areas of the world call for good assessment of our past and present actions, in order to guide our future decisions. The novel Wageningen Lowland Runoff Simulator (WALRUS; Brauer et al., 2014) was developed to simulate hydrological processes and has showed promising performance in recent studies in the Netherlands. Here the model was applied to a coastal basin of 2800 ha in the Veneto Region (northern Italy) to test model performance and evaluate scenario analyses of land use change and climate change. Located partially below sea-level, the reclaimed area is facing persistent land transformation and climate change trends, which alter not only the processes in the catchment but also the demands from it (Tarolli and Sofia, 2016). Firstly results of the calibration (NSE = 0.77; year simulation, daily resolution) and validation (NSE = 0.53; idem) showed that the model is able to reproduce the dominant hydrological processes of this lowland area (e.g. discharge and groundwater fluxes). Land use scenarios between 1951 and 2060 were constructed using demographic models, supported by orthographic interpretation techniques. Climate scenarios were constructed by historical records and future projections by COSMO-CLM regional climate model (Rockel et al., 2008) under the RCP4.5 pathway. WALRUS simulations showed that the land use changes result in a wetter catchment with more discharge, and the climatic changes cause more extremes with longer droughts and stronger rain events. These changes combined show drier summers (-33{%} rainfall, +27{%} soil moisture deficit) and wetter (+13{%} rainfall) and intenser (+30{%} rain intensity) autumn and winters in the future. The simulated discharge regime -particularly peak flow- follows these polarising trends, in good agreement with similar studies in the geographical zone (e.g. Vezzoli et al., 2015). This will increase the pressure on the fully-artificial drainage and agricultural systems, that will need to adapt to prevent largescale floods or crop-failure. Additionally, simulations under 'business-as-usual' pathway RCP8.5 would likely amplify the polarising effects on the hydrological regime as presented here, further stressing the need for adequate adaptation. The proposed presentation at EGU 2017 will contain clear visual results of the model and quantitative scenario simulations. These results are particularly interesting, firstly because they prove how a simple conceptual model can become a powerful tool in scenario analysis of future pathways. Furthermore, they clearly indicate major challenges that lowland areas are facing in modern times - not only the 46.000 km2 Po valley, but all around the world where lowlands often host the centres of our societies and economies. REFERENCES Brauer, C., Teuling, A., Torfs, P., Uijlenhoet, R., 2014. The Wageningen Lowland Runoff Simulator (WALRUS): a lumped rainfall-runoff model for catchments with shallow groundwater. Geoscientific Model Development 7 (5), 2313-2332. Rockel, B., Will, A., Hense, A., 2008. The regional climate model COSMO-CLM (CCLM). Meteorologische Zeitschrift 17 (4), 347-348. Tarolli, P., Sofia, G., 2016. Human topographic signatures and derived geomorphic processes across landscapes. Geomorphology 255, 140-161. Vezzoli, R., Mercogliano, P., Pecora, S., Zollo, A., Cacciamani, C., 2015. Hydrological simulation of Po River (North Italy) discharge under climate change scenarios using the RCM COSMO-CLM. Science of The Total Environment 521, 346-358.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3923064','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3923064"><span>A Risk-Based Framework for Assessing the Effectiveness of Stratospheric Aerosol Geoengineering</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>Ferraro, Angus J.; Charlton-Perez, Andrew J.; Highwood, Eleanor J.</p> <p>2014-01-01</p> <p>Geoengineering by stratospheric aerosol injection has been proposed as a policy response to warming from human emissions of greenhouse gases, but it may produce unequal regional impacts. We present a simple, intuitive risk-based framework for classifying these impacts according to whether geoengineering increases or decreases the risk of substantial climate change, with further classification by the level of existing risk from climate change from increasing carbon dioxide concentrations. This framework is applied to two climate model simulations of geoengineering counterbalancing the surface warming produced by a quadrupling of carbon dioxide concentrations, with one using a layer of sulphate aerosol in the lower stratosphere, and the other a reduction in total solar irradiance. The solar dimming model simulation shows less regional inequality of impacts compared with the aerosol geoengineering simulation. In the solar dimming simulation, 10% of the Earth's surface area, containing 10% of its population and 11% of its gross domestic product, experiences greater risk of substantial precipitation changes under geoengineering than under enhanced carbon dioxide concentrations. In the aerosol geoengineering simulation the increased risk of substantial precipitation change is experienced by 42% of Earth's surface area, containing 36% of its population and 60% of its gross domestic product. PMID:24533155</p> </li> <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('http://adsabs.harvard.edu/abs/2015AGUFMGC41A1055K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFMGC41A1055K"><span>Projected changes in climate extremes over Qatar and the Arabian Gulf 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>Kundeti, K.; Kanikicharla, K. K.; Al sulaiti, M.; Khulaifi, M.; Alboinin, N.; Kito, A.</p> <p>2015-12-01</p> <p>The climate of the State of Qatar and the adjacent region is dominated by subtropical dry, hot desert climate with low annual rainfall, very high temperatures in summer and a big difference between maximum and minimum temperatures, especially in the inland areas. The coastal areas are influenced by the Arabian Gulf, and have lower maximum, but higher minimum temperatures and a higher moisture percentage in the air. The global warming can have profound impact on the mean climate as well as extreme weather events over the Arabian Peninsula that may affect both natural and human systems significantly. Therefore, it is important to assess the future changes in the seasonal/annual mean of temperature and precipitation and also the extremes in temperature and wind events for a country like Qatar. This study assesses the performance of the Coupled Model Inter comparison Project Phase 5 (CMIP5) simulations in present and develops future climate scenarios. The changes in climate extremes are assessed for three future periods 2016-2035, 2046-2065 and 2080-2099 with respect to 1986-2005 (base line) under two RCPs (Representative Concentrate Pathways) - RCP4.5 and RCP8.5. We analyzed the projected changes in temperature and precipitation extremes using several indices including those that capture heat stress. The observations show an increase in warm extremes over many parts in this region that are generally well captured by the models. The results indicate a significant change in frequency and intensity of both temperature and precipitation extremes over many parts of this region which may have serious implications on human health, water resources and the onshore/offshore infrastructure in this region. Data from a high-resolution (20km) AGCM simulation from Meteorological Research Institute of Japan Meteorological Agency for the present (1979-2003) and a future time slice (2075-2099) corresponding to RCP8.5 have also been utilized to assess the impact of climate change on regional climate extremes as well. The scenarios generated with the high-resolution model simulation were compared with the coarse resolution CMIP5 model scenarios to identify region specific features that might be better resolved in the former simulation.</p> </li> <li> <p><a target="_blank" rel="noopener noreferrer" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PApGe.175..465S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PApGe.175..465S"><span>Impact of Desiccation of Aral Sea on the Regional Climate of Central Asia Using WRF 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>Sharma, Ashish; Huang, Huei-Ping; Zavialov, Peter; Khan, Valentina</p> <p>2018-01-01</p> <p>This study explores the impacts of the desiccation of the Aral Sea and large-scale climate change on the regional climate of Central Asia in the post-1960 era. A series of climate downscaling experiments for the 1960's and 2000's decades were performed using the Weather Research and Forecast model at 12-km horizontal resolution. To quantify the impacts of the changing surface boundary condition, a set of simulations with an identical lateral boundary condition but different extents of the Aral Sea were performed. It was found that the desiccation of the Aral Sea leads to more snow (and less rain) as desiccated winter surface is relatively much colder than water surface. In summer, desiccation led to substantial warming over the Aral Sea. These impacts were largely confined to within the area covered by the former Aral Sea and its immediate vicinity, although desiccation of the Sea also led to minor cooling over the greater Central Asia in winter. A contrasting set of simulations with an identical surface boundary condition but different lateral boundary conditions produced more identifiable changes in regional climate over the greater Central Asia which was characterized by a warming trend in both winter and summer. Simulations also showed that while the desiccation of the Aral Sea has significant impacts on the local climate over the Sea, the climate over the greater Central Asia on inter-decadal time scale was more strongly influenced by the continental or global-scale climate change on that time scale.</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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