Amazon collapse in the next century: exploring the sensitivity to climate and model formulation uncertainties

NASA Astrophysics Data System (ADS)

Booth, B.; Collins, M.; Harris, G.; Chris, H.; Jones, C.

2007-12-01

A number of recent studies have highlighted the risk of abrupt dieback of the Amazon Rain Forest as the result of climate changes over the next century. The recent 2005 Amazon drought brought wider acceptance of the idea that that climate drivers will play a significant role in future rain forest stability, yet that stability is still subject to considerable degree of uncertainty. We present a study which seeks to explore some of the underlying uncertainties both in the climate drivers of dieback and in the terrestrial land surface formulation used in GCMs. We adopt a perturbed physics approach which forms part of a wider project which is covered in an accompanying abstract submitted to the multi-model ensembles session. We first couple the same interactive land surface model to a number of different versions of the Hadley Centre atmosphere-ocean model that exhibit a wide range of different physical climate responses in the future. The rainforest extent is shown to collapse in all model cases but the timing of the collapse is dependent on the magnitude of the climate drivers. In the second part, we explore uncertainties in the terrestrial land surface model using the perturbed physics ensemble approach, perturbing uncertain parameters which have an important role in the vegetation and soil response. Contrasting the two approaches enables a greater understanding of the relative importance of climatic and land surface model uncertainties in Amazon dieback.

Projected 21st century coastal flooding in the Southern California Bight. Part 1: Development of the third generation CoSMoS model

USGS Publications Warehouse

O'Neill, Andrea; Erikson, Li; Barnard, Patrick; Limber, Patrick; Vitousek, Sean; Warrick, Jonathan; Foxgrover, Amy C.; Lovering, Jessica

2018-01-01

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the sustainability of coastal communities, development, and ecosystems as we know them today. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies due to projected increased levels of coastal flooding and erosion, coastal managers need local-scale hazards projections using the best available climate and coastal science. In collaboration with leading scientists world-wide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea-level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections in a thorough and comprehensive numerical modeling framework. In Part 1 of a two-part submission on CoSMoS, methods and the latest improvements are discussed, and an example of hazard projections is presented.

Scale and modeling issues in water resources planning

USGS Publications Warehouse

Lins, H.F.; Wolock, D.M.; McCabe, G.J.

1997-01-01

Resource planners and managers interested in utilizing climate model output as part of their operational activities immediately confront the dilemma of scale discordance. Their functional responsibilities cover relatively small geographical areas and necessarily require data of relatively high spatial resolution. Climate models cover a large geographical, i.e. global, domain and produce data at comparatively low spatial resolution. Although the scale differences between model output and planning input are large, several techniques have been developed for disaggregating climate model output to a scale appropriate for use in water resource planning and management applications. With techniques in hand to reduce the limitations imposed by scale discordance, water resource professionals must now confront a more fundamental constraint on the use of climate models-the inability to produce accurate representations and forecasts of regional climate. Given the current capabilities of climate models, and the likelihood that the uncertainty associated with long-term climate model forecasts will remain high for some years to come, the water resources planning community may find it impractical to utilize such forecasts operationally.

The key role of dry days in changing regional climate and precipitation regimes

USGS Publications Warehouse

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

2014-01-01

Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability.

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

NASA Astrophysics Data System (ADS)

Wang, Guiling

2005-12-01

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June July August (JJA) season and the Asian monsoon region in the December January February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.

More than the sum of the parts: forest climate response from joint species distribution models

Treesearch

James S. Clark; Alan E. Gelfand; Christopher W. Woodall; Kai Zhu

2014-01-01

The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Species respond to the same underlying climatic variables, and the abundance of any one species can be constrained by...

Teacher Challenges, Perceptions, and Use of Science Models in Middle School Classrooms about Climate, Weather, and Energy Concepts

ERIC Educational Resources Information Center

Yarker, Morgan Brown

2013-01-01

Research suggests that scientific models and modeling should be topics covered in K-12 classrooms as part of a comprehensive science curriculum. It is especially important when talking about topics in weather and climate, where computer and forecast models are the center of attention. There are several approaches to model based inquiry, but it can…

Shallow Horizontal GCHP Effectiveness in Arid Climate Soils

NASA Astrophysics Data System (ADS)

North, Timothy James

Ground coupled heat pumps (GCHPs) have been used successfully in many environments to improve the heating and cooling efficiency of both small and large scale buildings. In arid climate regions, such as the Phoenix, Arizona metropolitan area, where the air condi-tioning load is dominated by cooling in the summer, GCHPs are difficult to install and operate. This is because the nature of soils in arid climate regions, in that they are both dry and hot, renders them particularly ineffective at dissipating heat. The first part of this thesis addresses applying the SVHeat finite element modeling soft-ware to create a model of a GCHP system. Using real-world data from a prototype solar-water heating system coupled with a ground-source heat exchanger installed in Menlo Park, California, a relatively accurate model was created to represent a novel GCHP panel system installed in a shallow vertical trench. A sensitivity analysis was performed to evaluate the accuracy of the calibrated model. The second part of the thesis involved adapting the calibrated model to represent an ap-proximation of soil conditions in arid climate regions, using a range of thermal properties for dry soils. The effectiveness of the GCHP in the arid climate region model was then evaluated by comparing the thermal flux from the panel into the subsurface profile to that of the prototype GCHP. It was shown that soils in arid climate regions are particularly inefficient at heat dissipation, but that it is highly dependent on the thermal conductivity inputted into the model. This demonstrates the importance of proper site characterization in arid climate regions. Finally, several soil improvement methods were researched to evaluate their potential for use in improving the effectiveness of shallow horizontal GCHP systems in arid climate regions.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

Climate Prediction Center - Seasonal Outlook

Science.gov Websites

SEASONAL CLIMATE VARIABILITY, INCLUDING ENSO, SOIL MOISTURE, AND VARIOUS STATE-OF-THE-ART DYNAMICAL MODEL ACROSS PARTS OF THE EAST-CENTRAL CONUS CENTERED ON THE MISSISSIPPI RIVER. THIS IS DUE TO VERY HIGH SOIL TRENDS, NEGATIVE SOIL MOISTURE ANOMALIES, LAGGED ENSO REGRESSIONS, AND DYNAMICAL MODEL GUIDANCE ARE ALL

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

NASA Technical Reports Server (NTRS)

Phillips, T. J.; Semtner, A. J., Jr.

1984-01-01

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Eliciting climate experts' knowledge to address model uncertainties in regional climate projections: a case study of Guanacaste, Northwest Costa Rica

NASA Astrophysics Data System (ADS)

Grossmann, I.; Steyn, D. G.

2014-12-01

Global general circulation models typically cannot provide the detailed and accurate regional climate information required by stakeholders for climate adaptation efforts, given their limited capacity to resolve the regional topography and changes in local sea surface temperature, wind and circulation patterns. The study region in Northwest Costa Rica has a tropical wet-dry climate with a double-peak wet season. During the dry season the central Costa Rican mountains prevent tropical Atlantic moisture from reaching the region. Most of the annual precipitation is received following the northward migration of the ITCZ in May that allows the region to benefit from moist southwesterly flow from the tropical Pacific. The wet season begins with a short period of "early rains" and is interrupted by the mid-summer drought associated with the intensification and westward expansion of the North Atlantic subtropical high in late June. Model projections for the 21st century indicate a lengthening and intensification of the mid-summer drought and a weakening of the early rains on which current crop cultivation practices rely. We developed an expert elicitation to systematically address uncertainties in the available model projections of changes in the seasonal precipitation pattern. Our approach extends an elicitation approach developed previously at Carnegie Mellon University. Experts in the climate of the study region or Central American climate were asked to assess the mechanisms driving precipitation during each part of the season, uncertainties regarding these mechanisms, expected changes in each mechanism in a warming climate, and the capacity of current models to reproduce these processes. To avoid overconfidence bias, a step-by-step procedure was followed to estimate changes in the timing and intensity of precipitation during each part of the season. The questions drew upon interviews conducted with the regions stakeholders to assess their climate information needs. This study is part of the FuturAgua project funded by the Belmont Freshwater Security call. The expert opinions on expected changes in the seasonal precipitation pattern are being used to inform regional efforts to build drought resilience and to create and compare alternative water management strategies with the region's stakeholders.

Climate change and heat-related mortality in six cities Part 1: model construction and validation

NASA Astrophysics Data System (ADS)

Gosling, Simon N.; McGregor, Glenn R.; Páldy, Anna

2007-08-01

Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature ( T max) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. ‘Threshold temperatures’ above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in ‘cooler’ cities exhibiting lower mean summer temperatures than in ‘warmer’ cities exhibiting higher mean summer temperatures. Analysis of individual ‘heat waves’ illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature-mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature-mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).

Photoperiod cues and patterns of genetic variation limit phenological responses to climate change in warm parts of species’ range: Modeling diameter-growth cessation in coast Douglas-fir

Treesearch

Kevin R. Ford; Constance A. Harrington; J. Bradley St. Clair

2017-01-01

The phenology of diameter-growth cessation in trees will likely play a key role in mediating species and ecosystem responses to climate change. A common expectation is that warming will delay cessation, but the environmental and genetic influences on this process are poorly understood. We modeled the effects of temperature, photoperiod, and seed-source climate on...

Climate-based species distribution models for Armillaria solidipes in Wyoming: A preliminary assessment

Treesearch

John W. Hanna; James T. Blodgett; Eric W. I. Pitman; Sarah M. Ashiglar; John E. Lundquist; Mee-Sook Kim; Amy L. Ross-Davis; Ned B. Klopfenstein

2014-01-01

As part of an ongoing project to predict Armillaria root disease in the Rocky Mountain zone, this project predicts suitable climate space (potential distribution) for A. solidipes in Wyoming and associated forest areas at risk to disease caused by this pathogen. Two bioclimatic models are being developed. One model is based solely on verified locations of A. solidipes...

Reliable low precision simulations in land surface models

NASA Astrophysics Data System (ADS)

Dawson, Andrew; Düben, Peter D.; MacLeod, David A.; Palmer, Tim N.

2017-12-01

Weather and climate models must continue to increase in both resolution and complexity in order that forecasts become more accurate and reliable. Moving to lower numerical precision may be an essential tool for coping with the demand for ever increasing model complexity in addition to increasing computing resources. However, there have been some concerns in the weather and climate modelling community over the suitability of lower precision for climate models, particularly for representing processes that change very slowly over long time-scales. These processes are difficult to represent using low precision due to time increments being systematically rounded to zero. Idealised simulations are used to demonstrate that a model of deep soil heat diffusion that fails when run in single precision can be modified to work correctly using low precision, by splitting up the model into a small higher precision part and a low precision part. This strategy retains the computational benefits of reduced precision whilst preserving accuracy. This same technique is also applied to a full complexity land surface model, resulting in rounding errors that are significantly smaller than initial condition and parameter uncertainties. Although lower precision will present some problems for the weather and climate modelling community, many of the problems can likely be overcome using a straightforward and physically motivated application of reduced precision.

Effect of climate change on marine ecosystems

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Earth System Modeling and Field Experiments in the Arctic-Boreal Zone - Report from a NASA Workshop

NASA Technical Reports Server (NTRS)

Sellers, Piers; Rienecker Michele; Randall, David; Frolking, Steve

2012-01-01

Early climate modeling studies predicted that the Arctic Ocean and surrounding circumpolar land masses would heat up earlier and faster than other parts of the planet as a result of greenhouse gas-induced climate change, augmented by the sea-ice albedo feedback effect. These predictions have been largely borne out by observations over the last thirty years. However, despite constant improvement, global climate models have greater difficulty in reproducing the current climate in the Arctic than elsewhere and the scatter between projections from different climate models is much larger in the Arctic than for other regions. Biogeochemical cycle (BGC) models indicate that the warming in the Arctic-Boreal Zone (ABZ) could lead to widespread thawing of the permafrost, along with massive releases of CO2 and CH4, and large-scale changes in the vegetation cover in the ABZ. However, the uncertainties associated with these BGC model predictions are even larger than those associated with the physical climate system models used to describe climate change. These deficiencies in climate and BGC models reflect, at least in part, an incomplete understanding of the Arctic climate system and can be related to inadequate observational data or analyses of existing data. A workshop was held at NASA/GSFC, May 22-24 2012, to assess the predictive capability of the models, prioritize the critical science questions; and make recommendations regarding new field experiments needed to improve model subcomponents. This presentation will summarize the findings and recommendations of the workshop, including the need for aircraft and flux tower measurements and extension of existing in-situ measurements to improve process modeling of both the physical climate and biogeochemical cycle systems. Studies should be directly linked to remote sensing investigations with a view to scaling up the improved process models to the Earth System Model scale. Data assimilation and observing system simulation studies should be used to guide the deployment pattern and schedule for inversion studies as well. Synthesis and integration of previously funded Arctic-Boreal projects (e.g., ABLE, BOREAS, ICESCAPE, ICEBRIDGE, ARCTAS) should also be undertaken. Such an effort would include the integration of multiple remotely sensed products from the EOS satellites and other resources.

Workshop: Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis: Modeling Climate Change Impacts and Associated Economic Damages (2011 - part 2)

EPA Pesticide Factsheets

The purpose of this workshop Improving the Assessment and Valuation of Climate Change Impacts for Policy and Regulatory Analysis. focused on conceptual and methodological issues - estimating impacts and valuing damages on a sectoral basis.

European climate change at global mean temperature increases of 1.5 and 2 °C above pre-industrial conditions as simulated by the EURO-CORDEX regional climate models

NASA Astrophysics Data System (ADS)

Kjellström, Erik; Nikulin, Grigory; Strandberg, Gustav; Bøssing Christensen, Ole; Jacob, Daniela; Keuler, Klaus; Lenderink, Geert; van Meijgaard, Erik; Schär, Christoph; Somot, Samuel; Sørland, Silje Lund; Teichmann, Claas; Vautard, Robert

2018-05-01

We investigate European regional climate change for time periods when the global mean temperature has increased by 1.5 and 2 °C compared to pre-industrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth-phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under the RCP8.5 forcing scenario. The results indicate considerable near-surface warming already at the lower 1.5 °C of warming. Regional warming exceeds that of the global mean in most parts of Europe, being the strongest in the northernmost parts of Europe in winter and in the southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, which are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are already seen at 1.5 °C of warming but are larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread among individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent show decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure, indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results, leading either to attenuation or amplification of the climate change signal in the underlying GCMs. We find that the RCMs tend to produce less warming and more precipitation (or less drying) in many areas in both winter and summer.

The Influence of the Green River Lake System on the Local Climate During the Early Eocene Period

NASA Astrophysics Data System (ADS)

Elguindi, N.; Thrasher, B.; Sloan, L. C.

2006-12-01

Several modeling efforts have attempted to reproduce the climate of the early Eocene North America. However when compared to proxy data, General Circulation Models (GCMs) tend to produce a large-scale cold-bias. Although higher resolution Regional Climate Models (RCMs) that are able to resolve many of the sub-GCM scale forcings improve this cold bias, RCMs are still unable to reproduce the warm climate of the Eocene. From geologic data, we know that the greater Green River and the Uinta basins were intermontane basins with a large lake system during portions of the Eocene. We speculate that the lack of presence of these lakes in previous modeling studies may explain part of the persistent cold-bias of GCMs and RCMs. In this study, we utilize a regional climate model coupled with a 1D-lake model in an attempt to reduce the uncertainties and biases associated with climate simulations over Eocene western North American. Specifically, we include the Green River Lake system in our RCM simulation and compare climates with and without lakes to proxy data.

Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins.

PubMed

Gampe, David; Nikulin, Grigory; Ludwig, Ralf

2016-12-15

Climate change will likely increase pressure on the water balances of Mediterranean basins due to decreasing precipitation and rising temperatures. To overcome the issue of data scarcity the hydrological relevant variables total runoff, surface evaporation, precipitation and air temperature are taken from climate model simulations. The ensemble applied in this study consists of 22 simulations, derived from different combinations of four General Circulation Models (GCMs) forcing different Regional Climate Models (RCMs) and two Representative Concentration Pathways (RCPs) at ~12km horizontal resolution provided through the EURO-CORDEX initiative. Four river basins (Adige, Ebro, Evrotas and Sava) are selected and climate change signals for the future period 2035-2065 as compared to the reference period 1981-2010 are investigated. Decreased runoff and evaporation indicate increased water scarcity over the Ebro and the Evrotas, as well as the southern parts of the Adige and the Sava, resulting from a temperature increase of 1-3° and precipitation decrease of up to 30%. Most severe changes are projected for the summer months indicating further pressure on the river basins already at least partly characterized by flow intermittency. The widely used Falkenmark indicator is presented and confirms this tendency and shows the necessity for spatially distributed analysis and high resolution projections. Related uncertainties are addressed by the means of a variance decomposition and model agreement to determine the robustness of the projections. The study highlights the importance of high resolution climate projections and represents a feasible approach to assess climate impacts on water scarcity also in regions that suffer from data scarcity. Copyright © 2016. Published by Elsevier B.V.

Predicting ecological responses in a changing ocean: the effects of future climate uncertainty.

PubMed

Freer, Jennifer J; Partridge, Julian C; Tarling, Geraint A; Collins, Martin A; Genner, Martin J

2018-01-01

Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica . Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies.

Practice and philosophy of climate model tuning across six US modeling centers

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

Schmidt, Gavin A.; Bader, David; Donner, Leo J.

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

Practice and philosophy of climate model tuning across six US modeling centers

NASA Astrophysics Data System (ADS)

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; Elsaesser, Gregory S.; Golaz, Jean-Christophe; Hannay, Cecile; Molod, Andrea; Neale, Richard B.; Saha, Suranjana

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

Practice and philosophy of climate model tuning across six US modeling centers

DOE PAGES

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; ...

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

Decadal climate prediction with a refined anomaly initialisation approach

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco J.; Hawkins, Ed; Nichols, Nancy K.

2017-03-01

In decadal prediction, the objective is to exploit both the sources of predictability from the external radiative forcings and from the internal variability to provide the best possible climate information for the next decade. Predicting the climate system internal variability relies on initialising the climate model from observational estimates. We present a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following key innovations: (1) the use of a weight applied to the observed anomalies, in order to avoid the risk of introducing anomalies recorded in the observed climate, whose amplitude does not fit in the range of the internal variability generated by the model; (2) the AI of the ocean density, instead of calculating it from the anomaly initialised state of temperature and salinity. An experiment initialised with this refined AI method has been compared with a full field and standard AI experiment. Results show that the use of such refinements enhances the surface temperature skill over part of the North and South Atlantic, part of the South Pacific and the Mediterranean Sea for the first forecast year. However, part of such improvement is lost in the following forecast years. For the tropical Pacific surface temperature, the full field initialised experiment performs the best. The prediction of the Arctic sea-ice volume is improved by the refined AI method for the first three forecast years and the skill of the Atlantic multidecadal oscillation is significantly increased compared to a non-initialised forecast, along the whole forecast time.

The use of EuroCordex in marine climate projections

NASA Astrophysics Data System (ADS)

Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

2017-04-01

The Northwest European Shelf seas (NWS, including the North Sea, Irish Sea and Celtic Sea) are of economic, environmental and cultural importance to a number of European countries. However, their representation by global climate models (GCMs) is very crude, due to their inability to represent the complex geometry and the absence of tides. Therefore, there is a need to employ dynamical downscaling methods when considering the potential impacts of climate change on the European (and other) shelf seas. Using a shelf seas model to dynamically downscale of the ocean component of the GCM is a well established method. While taking open ocean lateral boundary conditions from the GCM ocean is acceptable, using surface flux forcings from the GCM atmosphere is often problematic. The CORDEX project provides an important dataset of high spatial and temporal resolution atmospheric forcings, derived from 'parent' CMIP5 GCM simulations. We drive the NEMO shelf seas model with data from CMIP5 models and EURO-CORDEX Regional Climate Model (RCM) data to produce a set of NWS climate projections. We require relatively high temporal resolution output, and run-off (for the river forcings), and so are limited to a subset of the available EURO-CORDEX RCMs. From these we select two CMIP5 GCMs with the same RCM with two emissions scenarios to give a minimum estimate of GCM model structural and emission scenario uncertainty. Other experiments allow an initial estimate of the uncertainty associated with the model structure of both the shelf seas and the RCM. Our analysis is focused on the uncertainty associated with the mean change in a number 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. Our work is part of the UK Climate Projections (UKCP18) and will inform the following UK Climate Change Risk Assessments, required as part of the Climate Change Act.

75 FR 27990 - Mid-Atlantic Fishery Management Council (MAFMC); Public Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-19

... presentation on Climate Change and Responses in a Coupled Marine System; the Mid-Atlantic surfclam (MASC) model is being developed as part of a multi-disciplinary study looking at adaptation to climate change in a...

Global water resources affected by human interventions and climate change.

PubMed

Haddeland, Ingjerd; Heinke, Jens; Biemans, Hester; Eisner, Stephanie; Flörke, Martina; Hanasaki, Naota; Konzmann, Markus; Ludwig, Fulco; Masaki, Yoshimitsu; Schewe, Jacob; Stacke, Tobias; Tessler, Zachary D; Wada, Yoshihide; Wisser, Dominik

2014-03-04

Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future.

Global water resources affected by human interventions and climate change

PubMed Central

Haddeland, Ingjerd; Heinke, Jens; Biemans, Hester; Eisner, Stephanie; Flörke, Martina; Hanasaki, Naota; Konzmann, Markus; Ludwig, Fulco; Masaki, Yoshimitsu; Schewe, Jacob; Stacke, Tobias; Tessler, Zachary D.; Wada, Yoshihide; Wisser, Dominik

2014-01-01

Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future. PMID:24344275

Climate Change Effects on Agriculture: Economic Responses to Biophysical Shocks

NASA Technical Reports Server (NTRS)

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlik, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(sup 2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Climate change effects on agriculture: Economic responses to biophysical shocks

PubMed Central

Nelson, Gerald C.; Valin, Hugo; Sands, Ronald D.; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d’Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-01-01

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. PMID:24344285

Climate change effects on agriculture: economic responses to biophysical shocks.

PubMed

Nelson, Gerald C; Valin, Hugo; Sands, Ronald D; Havlík, Petr; Ahammad, Helal; Deryng, Delphine; Elliott, Joshua; Fujimori, Shinichiro; Hasegawa, Tomoko; Heyhoe, Edwina; Kyle, Page; Von Lampe, Martin; Lotze-Campen, Hermann; Mason d'Croz, Daniel; van Meijl, Hans; van der Mensbrugghe, Dominique; Müller, Christoph; Popp, Alexander; Robertson, Richard; Robinson, Sherman; Schmid, Erwin; Schmitz, Christoph; Tabeau, Andrzej; Willenbockel, Dirk

2014-03-04

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5

NASA Astrophysics Data System (ADS)

Briley, L.; Rood, R. B.

2017-12-01

The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.

Understanding How Biomass Burning Impacts Climate Change

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

Aiken, Allison

2016-09-27

Biomass burning in Africa is creating a plume that spreads across the Atlantic Ocean all the way to Brazil. Allison Aiken, a research scientist at Los Alamos National Laboratory, collects data about the black carbon aerosols within this plume and their impact on the environment to help improve global climate modeling. A leader in energy science, Los Alamos develops climate models in support of the Laboratory’s mission to strengthen the nation’s energy security. Allison’s work is part of FIDO, a field operations team funded by the Energy Department’s Office of Science’s ARM Climate Research Facility.

Multi-model projections of Indian summer monsoon climate changes under A1B scenario

NASA Astrophysics Data System (ADS)

Niu, X.; Wang, S.; Tang, J.

2016-12-01

As part of the Regional Climate Model Intercomparison Project for Asia, the projections of Indian summer monsoon climate changes are constructed using three global climate models (GCMs) and seven regional climate models (RCMs) during 2041-2060 based on the Intergovernmental Panel on Climate Change A1B emission scenario. For the control climate of 1981-2000, most nested RCMs show advantage over the driving GCM of European Centre/Hamburg Fifth Generation (ECHAM5) in the temporal-spatial distributions of temperature and precipitation over Indian Peninsula. Following the driving GCM of ECHAM5, most nested RCMs produce advanced monsoon onset in the control climate. For future climate widespread summer warming is projected over Indian Peninsula by all climate models, with the Multi-RCMs ensemble mean (MME) temperature increasing of 1°C to 2.5°C and the maximum warming center located in northern Indian Peninsula. While for the precipitation, a large inter-model spread is projected by RCMs, with wetter condition in MME projections and significant increase over southern India. Driven by the same GCM, most RCMs project advanced monsoon onset while delayed onset is found in two Regional Climate Model (RegCM3) projections, indicating uncertainty can be expected in the Indian Summer Monsoon onset. All climate models except Conformal-Cubic Atmospheric Model with equal resolution (referred as CCAMP) and two RegCM3 models project stronger summer monsoon during 2041-2060. The disagreement in precipitation projections by RCMs indicates that the surface climate change on regional scale is not only dominated by the large-scale forcing which is provided by driving GCM but also sensitive to RCM' internal physics.

Latest research related to climate change analysis with applications in impact studies over the territory of Serbia

NASA Astrophysics Data System (ADS)

Vukovic, Ana; Vujadinovic, Mirjam; Djurdjevic, Vladimir; Cvetkovic, Bojan; Djordjevic, Marija; Ruml, Mirjana; Rankovic-Vasic, Zorica; Przic, Zoran; Stojicic, Djurdja; Krzic, Aleksandra; Rajkovic, Borivoj

2015-04-01

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.

Subseasonal-to-Seasonal Science and Prediction Initiatives of the NOAA MAPP Program

NASA Astrophysics Data System (ADS)

Archambault, H. M.; Barrie, D.; Mariotti, A.

2016-12-01

There is great practical interest in developing predictions beyond the 2-week weather timescale. Scientific communities have historically organized themselves around the weather and climate problems, but the subseasonal-to-seasonal (S2S) timescale range overall is recognized as new territory for which a concerted shared effort is needed. For instance, the climate community, as part of programs like CLIVAR, has historically tackled coupled phenomena and modeling, keys to harnessing predictability on longer timescales. In contrast, the weather community has focused on synoptic dynamics, higher-resolution modeling, and enhanced model initialization, of importance at the shorter timescales and especially for the prediction of extremes. The processes and phenomena specific to timescales between weather and climate require a unified approach to science, modeling, and predictions. Internationally, the WWRP/WCRP S2S Prediction Project is a promising catalyzer for these types of activities. Among the various contributing U.S. research programs, the Modeling, Analysis, Predictions and Projections (MAPP) program, as part of the NOAA Climate Program Office, has launched coordinated research and transition activities that help to meet the agency's goals to fill the weather-to-climate prediction gap and will contribute to advance international goals. This presentation will describe ongoing MAPP program S2S science and prediction initiatives, specifically the MAPP S2S Task Force and the SubX prediction experiment.

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

CMIP5-downscaled projections for the NW European Shelf Seas: initial results and insights into uncertainties

NASA Astrophysics Data System (ADS)

Tinker, Jonathan; Palmer, Matthew; Lowe, Jason; Howard, Tom

2017-04-01

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.

[Projection of potential geographic distribution of Apocynum venetum under climate change in northern China].

PubMed

Yang, Hui-Feng; Zheng, Jiang-Hua; Jia, Xiao-Guang; Li, Xiao-Jin

2017-03-01

Apocynum venetum belongs to apocynaceae and is a perennial medicinal plant, its stem is an important textile raw materials. The projection of potential geographic distribution of A. venetum has an important significance for the protection and sustainable utilization of the plant. This study was conducted to determine the potential geographic distribution of A. venetum and to project how climate change would affect its geographic distribution. The projection geographic distribution of A. venetum under current bioclimatic conditions in northern China was simulated using MaxEnt software based on species presence data at 44 locations and 19 bioclimatic parameters. The future distributions of A. venetum were also projected in 2050 and 2070 under the climate change scenarios of RCP2.6 and RCP8.5 described in 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). The result showed that min air temperature of the coldest month, annual mean air temperature, precipitation of the coldest quarter and mean air temperature of the wettest quarter dominated the geographic distribution of A. venetum. Under current climate, the suitable habitats of A. venetum is 11.94% in China, the suitable habitats are mainly located in the middle of Xinjiang, in the northern part of Gansu, in the southern part of Neimeng, in the northern part of Ningxia, in the middle and northern part of Shaanxi, in the southern part of Shanxi, in the middle and northern part of Henan, in the middle and southern part of Hebei, Shandong, Tianjin, in the southern part of Liaoning and part of Beijing. From 2050 to 2070, the model outputs indicated that the suitable habitats of A. venetum would decrease under the climate change scenarios of RCP2.6 and RCP8.5. Copyright© by the Chinese Pharmaceutical Association.

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.

Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

PubMed Central

Yuan, Naiming; Fu, Zuntao; Liu, Shida

2014-01-01

Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

NASA Technical Reports Server (NTRS)

Gasson, E.; Lunt, D. J.; DeConto, R.; Goldner, A.; Heinemann, M.; Huber, M.; LeGrande, A. N.; Pollard, D.; Sagoo, N.; Siddall, M.;

Climate Sensitivity, Sea Level, and Atmospheric Carbon Dioxide

NASA Technical Reports Server (NTRS)

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3+/-1deg C for a 4 W/sq m CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4deg C for a 4 W/sq m CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Climate model response from the Geoengineering Model Intercomparison Project (GeoMIP)

NASA Astrophysics Data System (ADS)

Kravitz, Ben; Caldeira, Ken; Boucher, Olivier; Robock, Alan; Rasch, Philip J.; Alterskjær, Kari; Karam, Diana Bou; Cole, Jason N. S.; Curry, Charles L.; Haywood, James M.; Irvine, Peter J.; Ji, Duoying; Jones, Andy; Kristjánsson, Jón Egill; Lunt, Daniel J.; Moore, John C.; Niemeier, Ulrike; Schmidt, Hauke; Schulz, Michael; Singh, Balwinder; Tilmes, Simone; Watanabe, Shingo; Yang, Shuting; Yoon, Jin-Ho

2013-08-01

geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwise occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2 mm day-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.

Climate Model Response from the Geoengineering Model Intercomparison Project (GeoMIP)

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

Kravitz, Benjamin S.; Caldeira, Ken; Boucher, Olivier

2013-08-09

Solar geoengineering—deliberate reduction in the amount of solar radiation retained by the Earth—has been proposed as a means of counteracting some of the climatic effects of anthropogenic greenhouse gas emissions. We present results from Experiment G1 of the Geoengineering Model Intercomparison Project, in which 12 climate models have simulated the climate response to an abrupt quadrupling of CO2 from preindustrial concentrations brought into radiative balance via a globally uniform reduction in insolation. Models show this reduction largely offsets global mean surface temperature increases due to quadrupled CO2 concentrations and prevents 97% of the Arctic sea ice loss that would otherwisemore » occur under high CO2 levels but, compared to the preindustrial climate, leaves the tropics cooler (-0.3 K) and the poles warmer (+0.8 K). Annual mean precipitation minus evaporation anomalies for G1 are less than 0.2mmday-1 in magnitude over 92% of the globe, but some tropical regions receive less precipitation, in part due to increased moist static stability and suppression of convection. Global average net primary productivity increases by 120% in G1 over simulated preindustrial levels, primarily from CO2 fertilization, but also in part due to reduced plant heat stress compared to a high CO2 world with no geoengineering. All models show that uniform solar geoengineering in G1 cannot simultaneously return regional and global temperature and hydrologic cycle intensity to preindustrial levels.« less

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

Sea Surface Temperature of the mid-Piacenzian Ocean: A Data-Model Comparison

PubMed Central

Dowsett, Harry J.; Foley, Kevin M.; Stoll, Danielle K.; Chandler, Mark A.; Sohl, Linda E.; Bentsen, Mats; Otto-Bliesner, Bette L.; Bragg, Fran J.; Chan, Wing-Le; Contoux, Camille; Dolan, Aisling M.; Haywood, Alan M.; Jonas, Jeff A.; Jost, Anne; Kamae, Youichi; Lohmann, Gerrit; Lunt, Daniel J.; Nisancioglu, Kerim H.; Abe-Ouchi, Ayako; Ramstein, Gilles; Riesselman, Christina R.; Robinson, Marci M.; Rosenbloom, Nan A.; Salzmann, Ulrich; Stepanek, Christian; Strother, Stephanie L.; Ueda, Hiroaki; Yan, Qing; Zhang, Zhongshi

2013-01-01

The mid-Piacenzian climate represents the most geologically recent interval of long-term average warmth relative to the last million years, and shares similarities with the climate projected for the end of the 21st century. As such, it represents a natural experiment from which we can gain insight into potential climate change impacts, enabling more informed policy decisions for mitigation and adaptation. Here, we present the first systematic comparison of Pliocene sea surface temperature (SST) between an ensemble of eight climate model simulations produced as part of PlioMIP (Pliocene Model Intercomparison Project) with the PRISM (Pliocene Research, Interpretation and Synoptic Mapping) Project mean annual SST field. Our results highlight key regional and dynamic situations where there is discord between the palaeoenvironmental reconstruction and the climate model simulations. These differences have led to improved strategies for both experimental design and temporal refinement of the palaeoenvironmental reconstruction. PMID:23774736

Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

NASA Astrophysics Data System (ADS)

Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

2013-04-01

Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

An introduction of a new stochastic tropical cyclone model for Japan area

NASA Astrophysics Data System (ADS)

Suzuki, K.; Nakano, S.; Ueno, G.; Mori, N.; Nakajo, S.

2015-12-01

The extreme events such as tropical cyclones (TC), downpours, floods, and so on, have huge influences on the human life in the past, present, and future. In particular, the change in their risks on the human life under the future climate has been concerned by the governments and researchers. Our aim is to estimate the probabilities for frequencies of TC which could attack to Japan under the future climate that calculated by GCMs. For carrying out this subject, it is needed a suitable rare event sampling method to find TCs that land on big cities in Japan. Moreover, it requires sufficient reproductions of TCs for calculation of their probabilities, too. The model for TC reproductions is designed with three parts following the lifecycle of TC; formation, maturity and decay. However, we don't treat the part of maturity with physical equations because the maturity process is complicated to express as a stochastic model. The TC intensity model will take the place of this physical part. Several stochastic TC models have been developed for different purposes and problems. Our model is developed for the establishment of a rare event sampling method. Here, the comparisons of behaviors of TC tracks among several stochastic TC models will be discussed using Best Track data provided by Japan Meteorological Agency and MRI-AGCM data for the present climate.

Teachers' Views of Their School Climate and Its Relationship with Teacher Self-Efficacy and Job Satisfaction

ERIC Educational Resources Information Center

Aldridge, Jill M.; Fraser, Barry J.

2016-01-01

The purpose of this study, in part, was to confirm the factor structure of the School-Level Environment Questionnaire, which assesses six school climate factors that can be considered important for improving schools. The study also tested a research model of the relationships between the school climate, teachers' self-efficacy and job…

Climate and dengue transmission: evidence and implications.

PubMed

Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

2013-01-01

Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

Future projections of temperature and precipitation climatology for CORDEX-MENA domain using RegCM4.4

NASA Astrophysics Data System (ADS)

Ozturk, Tugba; Turp, M. Tufan; Türkeş, Murat; Kurnaz, M. Levent

2018-07-01

In this study, we investigate changes in seasonal temperature and precipitation climatology of CORDEX Middle East and North Africa (MENA) region for three periods of 2010-2040, 2040-2070 and 2070-2100 with respect to the control period of 1970-2000 by using regional climate model simulations. Projections of future climate conditions are modeled by forcing Regional Climate Model, RegCM4.4 of the International Centre for Theoretical Physics (ICTP) with two different CMIP5 global climate models. HadGEM2-ES global climate model of the Met Office Hadley Centre and MPI-ESM-MR global climate model of the Max Planck Institute for Meteorology were used to generate 50 km resolution data for the Coordinated Regional Climate Downscaling Experiment (CORDEX) Region 13. We test the seasonal time-scale performance of RegCM4.4 in simulating the observed climatology over domain of the MENA by using the output of two different global climate models. The projection results show relatively high increase of average temperatures from 3 °C up to 9 °C over the domain for far future (2070-2100). A strong decrease in precipitation is projected in almost all parts of the domain according to the output of the regional model forced by scenario outputs of two global models. Therefore, warmer and drier than present climate conditions are projected to occur more intensely over the CORDEX-MENA domain.

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

USGS Publications Warehouse

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

Effects of fire suppression under a changing climate in Pacific Northwest mixed-pine forests

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Bart, R. R.; Kennedy, M. C.; Abatzoglou, J. T.; Kolden, C.; Adam, J. C.

2017-12-01

The frequency of large and severe wildfires has increased over recent decades in many regions across the Western U.S., including the Pacific and Inland Northwest. This increase is likely driven in large part by wildfire suppression, which has promoted fuel accumulation in western landscapes. Recent studies also suggest that anthropogenic climate change intensifies wildfire activity by increasing fuel aridity. However, the contribution of these drivers to observed changes in fire regime is not well quantified at regional scales. Understanding the relative influence of climate and fire suppression is crucial for both projecting the effects of climate change on future fire spread, and for developing site-specific fuel management strategies under a new climate paradigm. To quantify the extent to which fire suppression and climate change have contributed to increases in wildfire activity in the Pacific Northwest, we conduct a modeling experiment using the ecohydrologic model RHESSys and the coupled stochastic fire spread model WMFire. Specifically, we use historical climate inputs from GCMs, combined with fire suppression scenarios to gauge the extent to which these drivers promote the spread of severe wildfires in Johnson Creek, a large (565-km2) mixed-pine dominated subcatchment of the Southfork Salmon River; part of the larger Columbia River Basin. We run 500 model iterations for suppressed, intermediate, and unsuppressed fire management scenarios, both with and without climate change in a factorial design, focusing on fire spread surrounding two extreme fire years in Johnson Creek (1998 and 2007). After deriving fire spread "fingerprints" for each combination of possible drivers, we evaluate the extent to which these fingerprints match observations in the fire record. We expect that climate change plays a role in the spread of large and severe wildfires in Johnson Creek, but the magnitude of this effect is mediated by prior suppression. Preliminary results suggest that management strategies aimed at reducing the extent of contiguous even-aged fuels may help curtail climate-driven increases in wildfire severity in Pacific Northwest watersheds.

Climate-induced changes in forest disturbance and vegetation

NASA Technical Reports Server (NTRS)

Overpeck, Jonathan T.; Rind, David; Goldberg, Richard

1990-01-01

New and published climate-model results are discussed which indicate that global warming favors increased rates of forest disturbance as a result of weather more likely to cause forest fires, convective wind storms, coastal flooding, and hurricanes. New sensitivity tests carried out with a vegetation model indicate that climate-induced increases in disturbance could, in turn, significantly alter the total biomass and compositional response of forests to future warming. An increase in disturbance frequency is also likely to increase the rate at which natural vegetation responses to future climate change. The results reinforce the hypothesis that forests could be significantly altered by the first part of the next century. The modeling also confirms the potential utility of selected time series of fossil pollen data for investigating the poorly understood natural patterns of century-scale climate variability.

Regionalisation of statistical model outputs creating gridded data sets for Germany

NASA Astrophysics Data System (ADS)

Höpp, Simona Andrea; Rauthe, Monika; Deutschländer, Thomas

2016-04-01

The goal of the German research program ReKliEs-De (regional climate projection ensembles for Germany, http://.reklies.hlug.de) is to distribute robust information about the range and the extremes of future climate for Germany and its neighbouring river catchment areas. This joint research project is supported by the German Federal Ministry of Education and Research (BMBF) and was initiated by the German Federal States. The Project results are meant to support the development of adaptation strategies to mitigate the impacts of future climate change. The aim of our part of the project is to adapt and transfer the regionalisation methods of the gridded hydrological data set (HYRAS) from daily station data to the station based statistical regional climate model output of WETTREG (regionalisation method based on weather patterns). The WETTREG model output covers the period of 1951 to 2100 with a daily temporal resolution. For this, we generate a gridded data set of the WETTREG output for precipitation, air temperature and relative humidity with a spatial resolution of 12.5 km x 12.5 km, which is common for regional climate models. Thus, this regionalisation allows comparing statistical to dynamical climate model outputs. The HYRAS data set was developed by the German Meteorological Service within the German research program KLIWAS (www.kliwas.de) and consists of daily gridded data for Germany and its neighbouring river catchment areas. It has a spatial resolution of 5 km x 5 km for the entire domain for the hydro-meteorological elements precipitation, air temperature and relative humidity and covers the period of 1951 to 2006. After conservative remapping the HYRAS data set is also convenient for the validation of climate models. The presentation will consist of two parts to present the actual state of the adaptation of the HYRAS regionalisation methods to the statistical regional climate model WETTREG: First, an overview of the HYRAS data set and the regionalisation methods for precipitation (REGNIE method based on a combination of multiple linear regression with 5 predictors and inverse distance weighting), air temperature and relative humidity (optimal interpolation) will be given. Finally, results of the regionalisation of WETTREG model output will be shown.

A simple object-oriented and open-source model for scientific and policy analyses of the global climate system – Hector v1.0

DOE PAGES

Hartin, Corinne A.; Patel, Pralit L.; Schwarber, Adria; ...

2015-04-01

Simple climate models play an integral role in the policy and scientific communities. They are used for climate mitigation scenarios within integrated assessment models, complex climate model emulation, and uncertainty analyses. Here we describe Hector v1.0, an open source, object-oriented, simple global climate carbon-cycle model. This model runs essentially instantaneously while still representing the most critical global-scale earth system processes. Hector has a three-part main carbon cycle: a one-pool atmosphere, land, and ocean. The model's terrestrial carbon cycle includes primary production and respiration fluxes, accommodating arbitrary geographic divisions into, e.g., ecological biomes or political units. Hector actively solves the inorganicmore » carbon system in the surface ocean, directly calculating air–sea fluxes of carbon and ocean pH. Hector reproduces the global historical trends of atmospheric [CO 2], radiative forcing, and surface temperatures. The model simulates all four Representative Concentration Pathways (RCPs) with equivalent rates of change of key variables over time compared to current observations, MAGICC (a well-known simple climate model), and models from the 5th Coupled Model Intercomparison Project. Hector's flexibility, open-source nature, and modular design will facilitate a broad range of research in various areas.« less

New Observationally-Based Metrics for the Analysis of Coupled Climate Model and Earth System Model Simulations of the Southern Ocean

NASA Astrophysics Data System (ADS)

Russell, J. L.

2014-12-01

The exchange of heat and carbon dioxide between the atmosphere and ocean are major controls on Earth's climate under conditions of anthropogenic forcing. The Southern Ocean south of 30°S, occupying just over ¼ of the surface ocean area, accounts for a disproportionate share of the vertical exchange of properties between the deep and surface waters of the ocean and between the surface ocean and the atmosphere; thus this region can be disproportionately influential on the climate system. Despite the crucial role of the Southern Ocean in the climate system, understanding of the particular mechanisms involved remains inadequate, and the model studies underlying many of these results are highly controversial. As part of the overall goal of working toward reducing uncertainties in climate projections, we present an analysis using new data/model metrics based on a unified framework of theory, quantitative datasets, and numerical modeling. These new metrics quantify the mechanisms, processes, and tendencies relevant to the role of the Southern Ocean in climate.

Uncertainty in Climate Change Research: An Integrated Approach

NASA Astrophysics Data System (ADS)

Mearns, L.

2017-12-01

Uncertainty has been a major theme in research regarding climate change from virtually the very beginning. And appropriately characterizing and quantifying uncertainty has been an important aspect of this work. Initially, uncertainties were explored regarding the climate system and how it would react to future forcing. A concomitant area of concern was viewed in the future emissions and concentrations of important forcing agents such as greenhouse gases and aerosols. But, of course we know there are important uncertainties in all aspects of climate change research, not just that of the climate system and emissions. And as climate change research has become more important and of pragmatic concern as possible solutions to the climate change problem are addressed, exploring all the relevant uncertainties has become more relevant and urgent. More recently, over the past five years or so, uncertainties in impacts models, such as agricultural and hydrological models, have received much more attention, through programs such as AgMIP, and some research in this arena has indicated that the uncertainty in the impacts models can be as great or greater than that in the climate system. Still there remains other areas of uncertainty that remain underexplored and/or undervalued. This includes uncertainty in vulnerability and governance. Without more thoroughly exploring these last uncertainties, we likely will underestimate important uncertainties particularly regarding how different systems can successfully adapt to climate change . In this talk I will discuss these different uncertainties and how to combine them to give a complete picture of the total uncertainty individual systems are facing. And as part of this, I will discuss how the uncertainty can be successfully managed even if it is fairly large and deep. Part of my argument will be that large uncertainty is not the enemy, but rather false certainty is the true danger.

The relief formed by the descent phenomenon in the north-east part of Kosova.

PubMed

Bulliqi, Shpejtim; Isufi, Florim; Ramadani, Ibrahim; Gashi, Gani

2012-04-01

In the diverse relief of north-east part of Kosova a relatively wide range occupies the relief modelled by the descent phenomenon, which is conditioned by morph-structural and climatic factors quite suitable for their development. The morphogenesis activity of descent phenomenon is conditioned by the types of rocks, tectonic process of this region and climatic conditions. These factors condition horizontal and vertical relief fragmentation, slope, especially in Gollaku mountains and in SE part of Kopaonik mountain. Along the tectonic descents, the steepness is detaching and the detaching lines consisting of magmatic rocks show overthrows, demolitions and stony torrents, but the Teri gene composition formations are modelled by sliding and muddy torrents, depending upon the presence of clayey and alevrolite belts on these Teri gene ones. The impact of factors and conditions on the relief of this part, the phenomena like demolitions, overthrows, sliding, muddy torrents, stony torrents, etc, operate here, which play an important morphological role in the modelling of relief.

C4MIP - The Coupled Climate-Carbon Cycle Model Intercomparison Project: experimental protocol for CMIP6

NASA Astrophysics Data System (ADS)

Jones, Chris D.; Arora, Vivek; Friedlingstein, Pierre; Bopp, Laurent; Brovkin, Victor; Dunne, John; Graven, Heather; Hoffman, Forrest; Ilyina, Tatiana; John, Jasmin G.; Jung, Martin; Kawamiya, Michio; Koven, Charlie; Pongratz, Julia; Raddatz, Thomas; Randerson, James T.; Zaehle, Sönke

2016-08-01

Coordinated experimental design and implementation has become a cornerstone of global climate modelling. Model Intercomparison Projects (MIPs) enable systematic and robust analysis of results across many models, by reducing the influence of ad hoc differences in model set-up or experimental boundary conditions. As it enters its 6th phase, the Coupled Model Intercomparison Project (CMIP6) has grown significantly in scope with the design and documentation of individual simulations delegated to individual climate science communities. The Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP) takes responsibility for design, documentation, and analysis of carbon cycle feedbacks and interactions in climate simulations. These feedbacks are potentially large and play a leading-order contribution in determining the atmospheric composition in response to human emissions of CO2 and in the setting of emissions targets to stabilize climate or avoid dangerous climate change. For over a decade, C4MIP has coordinated coupled climate-carbon cycle simulations, and in this paper we describe the C4MIP simulations that will be formally part of CMIP6. While the climate-carbon cycle community has created this experimental design, the simulations also fit within the wider CMIP activity, conform to some common standards including documentation and diagnostic requests, and are designed to complement the CMIP core experiments known as the Diagnostic, Evaluation and Characterization of Klima (DECK). C4MIP has three key strands of scientific motivation and the requested simulations are designed to satisfy their needs: (1) pre-industrial and historical simulations (formally part of the common set of CMIP6 experiments) to enable model evaluation, (2) idealized coupled and partially coupled simulations with 1 % per year increases in CO2 to enable diagnosis of feedback strength and its components, (3) future scenario simulations to project how the Earth system will respond to anthropogenic activity over the 21st century and beyond. This paper documents in detail these simulations, explains their rationale and planned analysis, and describes how to set up and run the simulations. Particular attention is paid to boundary conditions, input data, and requested output diagnostics. It is important that modelling groups participating in C4MIP adhere as closely as possible to this experimental design.

Climate sensitivity, sea level and atmospheric carbon dioxide

PubMed Central

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-01-01

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1°C for a 4 W m−2 CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3–4°C for a 4 W m−2 CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change. PMID:24043864

Climate sensitivity, sea level and atmospheric carbon dioxide.

PubMed

Hansen, James; Sato, Makiko; Russell, Gary; Kharecha, Pushker

2013-10-28

Cenozoic temperature, sea level and CO2 covariations provide insights into climate sensitivity to external forcings and sea-level sensitivity to climate change. Climate sensitivity depends on the initial climate state, but potentially can be accurately inferred from precise palaeoclimate data. Pleistocene climate oscillations yield a fast-feedback climate sensitivity of 3±1(°)C for a 4 W m(-2) CO2 forcing if Holocene warming relative to the Last Glacial Maximum (LGM) is used as calibration, but the error (uncertainty) is substantial and partly subjective because of poorly defined LGM global temperature and possible human influences in the Holocene. Glacial-to-interglacial climate change leading to the prior (Eemian) interglacial is less ambiguous and implies a sensitivity in the upper part of the above range, i.e. 3-4(°)C for a 4 W m(-2) CO2 forcing. Slow feedbacks, especially change of ice sheet size and atmospheric CO2, amplify the total Earth system sensitivity by an amount that depends on the time scale considered. Ice sheet response time is poorly defined, but we show that the slow response and hysteresis in prevailing ice sheet models are exaggerated. We use a global model, simplified to essential processes, to investigate state dependence of climate sensitivity, finding an increased sensitivity towards warmer climates, as low cloud cover is diminished and increased water vapour elevates the tropopause. Burning all fossil fuels, we conclude, would make most of the planet uninhabitable by humans, thus calling into question strategies that emphasize adaptation to climate change.

Planetary boundary layer as an essential component of the earth's climate system

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

Following the traditional engineering approach proposed by Prandtl, the turbulent planetary boundary layers (PBLs) are considered in the climate science as complex, non-linear, essential but nevertheless subordinated components of the earth's climate system. Correspondingly, the temperature variations, dT - a popular and practically important measure of the climate variability, are seen as the system's response to the external heat forcing, Q, e.g. in the energy balance model of the type dT=Q/C (1). The moderation of this response by non-linear feedbacks embedded in the effective heat capacity, C, are to a large degree overlooked. The effective heat capacity is globally determined by the depth of the ocean mixed layer (on multi-decadal and longer time scales) but regionally, over the continents, C is much smaller and determined (on decadal time scales) by the depth, h, of the PBL. The present understanding of the climatological features of turbulent boundary layers is set by the works of Frankignoul & Hasselmann (1976) and Manabe & Stauffer (1980). The former explained how large-scale climate anomalies could be generated in the case of a large C (in the sea surface temperature) by the delta-correlated stochastic forcing (white noise). The latter demonstrated that the climate response to a given forcing is moderated by the depth, h, so that in the shallow PBL the signal should be significantly amplified. At present there are more than 3000 publications (ISI Web of Knowledge) which detail this understanding but the physical mechanisms, which control the boundary layer depth, and statistical relationships between the turbulent and climatological measures remain either unexplored or incorrectly attributed. In order to identify the climatic role of the PBL, the relationships between the PBL depth, h, - as the integral measure of the turbulent processes and micro-circulations due to the surface heterogeneity - and the climatic variability (variations and trends) of temperature have to be established. These relationships are necessary to complete the model (1) where the relationships between temperature variability, dT, and heat forcing, Q, are intensively studied. We demonstrate that the statistical dependences between dT and h becomes the primary factor in controlling the climate features of the earth's climate system when h is shallow (less than about 500 m). Such conditions are found in the cold (with negative surface heat balance on average) and dry (with large-scale air subsidence) climates. To get those climates and their variations correct, the climate models must be able to reproduce the shallow stably-stratified PBL. We show that the present-day CMIP-5 models are systematically and strongly biased towards producing deeper PBLs (between 20-50% deeper than observed) in this part of the parameter space which leads to large errors (around 15 K) and a damped variability of the surface temperatures under these conditions. More generally, this bias indicates that the models represent the earth's cooling processes incorrectly, which may be a part of the puzzle of the observed "hiatus" (or pause) in global warming. Frankignoul, C. & K. Hasselmann, 1977: Stochastic climate models. Part 2, Application to sea-surface temperature anomalies and thermocline variability, Tellus, 29, 289-305. Manabe, S. & R. Stouffer, 1980: Sensitivity of a Global Climate Model to an increase of CO2 concentration in the atmosphere, Journal of Geophysical Research, 85(C10): 5529-5554.

Assessment of climate change impact on yield of major crops in the Banas River Basin, India.

PubMed

Dubey, Swatantra Kumar; Sharma, Devesh

2018-09-01

Crop growth models like AquaCrop are useful in understanding the impact of climate change on crop production considering the various projections from global circulation models and regional climate models. The present study aims to assess the climate change impact on yield of major crops in the Banas River Basin i.e., wheat, barley and maize. Banas basin is part of the semi-arid region of Rajasthan state in India. AquaCrop model is used to calculate the yield of all the three crops for a historical period of 30years (1981-2010) and then compared with observed yield data. Root Mean Square Error (RMSE) values are calculated to assess the model accuracy in prediction of yield. Further, the calibrated model is used to predict the possible impacts of climate change and CO 2 concentration on crop yield using CORDEX-SA climate projections of three driving climate models (CNRM-CM5, CCSM4 and MPI-ESM-LR) for two different scenarios (RCP4.5 and RCP8.5) for the future period 2021-2050. RMSE values of simulated yield with respect to observed yield of wheat, barley and maize are 11.99, 16.15 and 19.13, respectively. It is predicted that crop yield of all three crops will increase under the climate change conditions for future period (2021-2050). Copyright © 2018 Elsevier B.V. All rights reserved.

Climate change effects on agriculture: Economic responses to biophysical shocks

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

Nelson, Gerald; Valin, Hugo; Sands, Ronald

Agricultural production is sensitive to weather and will thus be directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments inmore » yields, area, consumption, and international trade. We apply biophysical shocks derived from the IPCC’s Representative Concentration Pathway that result in end-of-century radiative forcing of 8.5 watts per square meter. The mean biophysical impact on crop yield with no incremental CO2 fertilization is a 17 percent reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11 percent, increase area of major crops by 12 percent, and reduce consumption by 2 percent. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences includes model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.« less

Regional climate model data used within the SWURVE project - 1: projected changes in seasonal patterns and estimation of PET

NASA Astrophysics Data System (ADS)

Ekström, M.; Jones, P. D.; Fowler, H. J.; Lenderink, G.; Buishand, T. A.; Conway, D.

2007-04-01

Climate data for studies within the SWURVE (Sustainable Water: Uncertainty, Risk and Vulnerability in Europe) project, assessing the risk posed by future climatic change to various hydrological and hydraulic systems were obtained from the regional climate model HadRM3H, developed at the Hadley Centre of the UK Met Office. This paper gives some background to HadRM3H; it also presents anomaly maps of the projected future changes in European temperature, rainfall and potential evapotranspiration (PET, estimated using a variant of the Penman formula). The future simulations of temperature and rainfall, following the SRES A2 emissions scenario, suggest that most of Europe will experience warming in all seasons, with heavier precipitation in winter in much of western Europe (except for central and northern parts of the Scandinavian mountains) and drier summers in most parts of western and central Europe (except for the north-west and the eastern part of the Baltic Sea). Particularly large temperature anomalies (>6°C) are projected for north-east Europe in winter and for southern Europe, Asia Minor and parts of Russia in summer. The projected PET displayed very large increases in summer for a region extending from southern France to Russia. The unrealistically large values could be the result of an enhanced hydrological cycle in HadRM3H, affecting several of the input parameters to the PET calculation. To avoid problems with hydrological modelling schemes, PET was re-calculated, using empirical relationships derived from observational values of temperature and PET.

Modeling long-term changes in forested landscapes and their relation to the Earth's energy balance

NASA Technical Reports Server (NTRS)

Shugart, H. H.; Emanuel, W. R.; Solomon, A. M.

1984-01-01

The dynamics of the forested parts of the Earth's surface on time scales from decades to centuries are discussed. A set of computer models developed at Oak Ridge National Laboratory and elsewhere are applied as tools. These models simulate a landscape by duplicating the dynamics of growth, death and birth of each tree living on a 0.10 ha element of the landscape. This spatial unit is generally referred to as a gap in the case of the forest models. The models were tested against and applied to a diverse array of forests and appear to provide a reasonable representation for investigating forest-cover dynamics. Because of the climate linkage, one important test is the reconstruction of paleo-landscapes. Detailed reconstructions of changes in vegetation in response to changes in climate are crucial to understanding the association of the Earth's vegetation and climate and the response of the vegetation to climate change.

Devon Ice cap's future: results from climate and ice dynamics modelling via surface mass balance modelling

NASA Astrophysics Data System (ADS)

Rodehacke, C. B.; Mottram, R.; Boberg, F.

2017-12-01

The Devon Ice Cap is an example of a relatively well monitored small ice cap in the Canadian Arctic. Close to Greenland, it shows a similar surface mass balance signal to glaciers in western Greenland. Here we various boundary conditions, ranging from ERA-Interim reanalysis data via global climate model high resolution (5km) output from the regional climate model HIRHAM5, to determine the surface mass balance of the Devon ice cap. These SMB estimates are used to drive the PISM glacier model in order to model the present day and future prospects of this small Arctic ice cap. Observational data from the Devon Ice Cap in Arctic Canada is used to evaluate the surface mass balance (SMB) data output from the HIRHAM5 model for simulations forced with the ERA-Interim climate reanalysis data and the historical emissions scenario run by the EC-Earth global climate model. The RCP8.5 scenario simulated by EC-Earth is also downscaled by HIRHAM5 and this output is used to force the PISM model to simulate the likely future evolution of the Devon Ice Cap under a warming climate. We find that the Devon Ice Cap is likely to continue its present day retreat, though in the future increased precipitation partly offsets the enhanced melt rates caused by climate change.

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

European scale climate information services for water use sectors

NASA Astrophysics Data System (ADS)

van Vliet, Michelle T. H.; Donnelly, Chantal; Strömbäck, Lena; Capell, René; Ludwig, Fulco

2015-09-01

This study demonstrates a climate information service for pan-European water use sectors that are vulnerable to climate change induced hydrological changes, including risk and safety (disaster preparedness), agriculture, energy (hydropower and cooling water use for thermoelectric power) and environment (water quality). To study the climate change impacts we used two different hydrological models forced with an ensemble of bias-corrected general circulation model (GCM) output for both the lowest (2.6) and highest (8.5) representative concentration pathways (RCP). Selected indicators of water related vulnerability for each sector were then calculated from the hydrological model results. Our results show a distinct north-south divide in terms of climate change impacts; in the south the water availability will reduce while in the north water availability will increase. Across different climate models precipitation and streamflow increase in northern Europe and decrease in southern Europe, but the latitude at which this change occurs varies depending on the GCM. Hydrological extremes are increasing over large parts of Europe. The agricultural sector will be affected by reduced water availability (in the south) and increased drought. Both streamflow and soil moistures droughts are projected to increase in most parts of Europe except in northern Scandinavia and the Alps. The energy sector will be affected by lower hydropower potential in most European countries and reduced cooling water availability due to higher water temperatures and reduced summer river flows. Our results show that in particular in the Mediterranean the pressures are high because of increasing drought which will have large impacts on both the agriculture and energy sectors. In France and Italy this is combined with increased flood hazards. Our results show important impacts of climate change on European water use sectors indicating a clear need for adaptation.

Multimodel ensemble projection of precipitation in eastern China under A1B emission scenario

NASA Astrophysics Data System (ADS)

Niu, Xiaorui; Wang, Shuyu; Tang, Jianping; Lee, Dong-Kyou; Gao, Xuejie; Wu, Jia; Hong, Songyou; Gutowski, William J.; McGregor, John

2015-10-01

As part of the Regional Climate Model Intercomparison Project for Asia, future precipitation projection in China is constructed using five regional climate models (RCMs) driven by the same global climate model (GCM) of European Centre/Hamburg version 5. The simulations cover both the control climate (1978-2000) and future projection (2041-2070) under the Intergovernmental Panel on Climate Change emission scenario A1B. For the control climate, the RCMs have an advantage over the driving GCM in reproducing the summer mean precipitation distribution and the annual cycle. The biases in simulating summer precipitation mainly are caused by the deficiencies in reproducing the low-level circulation, such as the western Pacific subtropical high. In addition, large inter-RCM differences exist in the summer precipitation simulations. For the future climate, consistent and inconsistent changes in precipitation between the driving GCM and the nested RCMs are observed. Similar changes in summer precipitation are projected by RCMs over western China, but model behaviors are quite different over eastern China, which is dominated by the Asian monsoon system. The inter-RCM difference of rainfall changes is more pronounced in spring over eastern China. North China and the southern part of South China are very likely to experience less summer rainfall in multi-RCM mean (MRM) projection, while limited credibility in increased summer rainfall MRM projection over the lower reaches of the Yangtze River Basin. The inter-RCM variability is the main contributor to the total uncertainty for the lower reaches of the Yangtze River Basin and South China during 2041-2060, while lowest for Northeast China, being less than 40%.

Climate Mitigation in Latin America: Implications for Energy and Land Use: Preface to the Special Section on the findings of the CLIMACAP-LAMP Project

DOE PAGES

van der Zwaan, Bob; Calvin, Katherine V.; Clarke, Leon E.

2016-05-01

The CLIMACAP-LAMP project, completed in December 2015, was an inter-model comparison exercise that focused on energy and climate change economics issues in Latin America. The project partners – co-financed by the EC / EuropeAid (CLIMACAP part) and EPA / USAID (LAMP part) and co-coordinated by respectively the Energy research Centre of the Netherlands (ECN) and the Pacific Northwest National Laboratory (PNNL) – report their main and detailed findings in this Special Issue of Energy Economics, exclusively dedicated to climate mitigation, low-carbon development and implications for energy and land use in Latin America. Our research endeavor included several of the mostmore » prominent regional energy modeling groups from Latin America, as well as a representative set of global integrated assessment modeling groups from a number of institutions from Europe and the US. About two dozen universities, research groups and environmental or consulting organizations took part in the CLIMACAP-LAMP cross-model comparison project, from both sides of the Atlantic. Over a handful of workshops were organized over the past four years in several countries in Latin America, attended by between 30 and 50 participants from, amongst others, Argentina, Brazil, Colombia, Mexico, the EU, and the US.« less

GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics

USGS Publications Warehouse

Dunne, John P.; John, Jasmin G.; Adcroft, Alistair J.; Griffies, Stephen M.; Hallberg, Robert W.; Shevalikova, Elena; Stouffer, Ronald J.; Cooke, William; Dunne, Krista A.; Harrison, Matthew J.; Krasting, John P.; Malyshev, Sergey L.; Milly, P.C.D.; Phillipps, Peter J.; Sentman, Lori A.; Samuels, Bonita L.; Spelman, Michael J.; Winton, Michael; Wittenberg, Andrew T.; Zadeh, Niki

2012-01-01

We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.

A multimodel approach to interannual and seasonal prediction of Danube discharge anomalies

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Patrut, Simona; Dima, Mihai

2010-05-01

Interannual and seasonal predictability of Danube river discharge is investigated using three model types: 1) time series models 2) linear regression models of discharge with large-scale climate mode indices and 3) models based on stable teleconnections. All models are calibrated using discharge and climatic data for the period 1901-1977 and validated for the period 1978-2008 . Various time series models, like autoregressive (AR), moving average (MA), autoregressive and moving average (ARMA) or singular spectrum analysis and autoregressive moving average (SSA+ARMA) models have been calibrated and their skills evaluated. The best results were obtained using SSA+ARMA models. SSA+ARMA models proved to have the highest forecast skill also for other European rivers (Gamiz-Fortis et al. 2008). Multiple linear regression models using large-scale climatic mode indices as predictors have a higher forecast skill than the time series models. The best predictors for Danube discharge are the North Atlantic Oscillation (NAO) and the East Atlantic/Western Russia patterns during winter and spring. Other patterns, like Polar/Eurasian or Tropical Northern Hemisphere (TNH) are good predictors for summer and autumn discharge. Based on stable teleconnection approach (Ionita et al. 2008) we construct prediction models through a combination of sea surface temperature (SST), temperature (T) and precipitation (PP) from the regions where discharge and SST, T and PP variations are stable correlated. Forecast skills of these models are higher than forecast skills of the time series and multiple regression models. The models calibrated and validated in our study can be used for operational prediction of interannual and seasonal Danube discharge anomalies. References Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part I: intearannual predictability. J. Climate, 2484-2501, 2008. Gamiz-Fortis, S., D. Pozo-Vazquez, R.M. Trigo, and Y. Castro-Diez, Quantifying the predictability of winter river flow in Iberia. Part II: seasonal predictability. J. Climate, 2503-2518, 2008. Ionita, M., G. Lohmann, and N. Rimbu, Prediction of spring Elbe river discharge based on stable teleconnections with global temperature and precipitation. J. Climate. 6215-6226, 2008.

A review on regional convection permitting climate modeling

NASA Astrophysics Data System (ADS)

van Lipzig, Nicole; Prein, Andreas; Brisson, Erwan; Van Weverberg, Kwinten; Demuzere, Matthias; Saeed, Sajjad; Stengel, Martin

2016-04-01

With the increase of computational resources, it has recently become possible to perform climate model integrations where at least part the of convection is resolved. Since convection-permitting models (CPMs) are performing better than models where convection is parameterized, especially for high-impact weather like extreme precipitation, there is currently strong scientific progress in this research domain (Prein et al., 2015). Another advantage of CPMs, that have a horizontal grid spacing <4 km, is that they better resolve complex orography and land use. The regional climate model COSMO-CLM is frequently applied for CPM simulations, due to its non-hydrostatic dynamics and open international network of scientists. This presentation consists of an overview of the recent progress in CPM, with a focus on COSMO-CLM. It consists of three parts, namely the discussion of i) critical components of CPM, ii) the added value of CPM in the present-day climate and iii) the difference in climate sensitivity in CPM compared to coarser scale models. In terms of added value, the CPMs especially improve the representation of precipitation's, diurnal cycle, intensity and spatial distribution. However, an in depth-evaluation of cloud properties with CCLM over Belgium indicates a strong underestimation of the cloud fraction, causing an overestimation of high temperature extremes (Brisson et al., 2016). In terms of climate sensitivity, the CPMs indicate a stronger increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains compared to coarser scale models. In conclusion, CPMs are a very promising tool for future climate research. However, additional efforts are necessary to overcome remaining deficiencies, like improving the cloud characteristics. This will be a challenging task due to compensating deficiencies that currently exist in `state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using CPMs to study climate change it is necessary that these deficiencies are addressed in future research. Coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs. Brisson, E., K. Van Weverberg, M. Demuzere, A. Devis, S. Saeed, M. Stengel, N.P.M. van Lipzig, 2016. How well can a convection-permitting climate model reproduce 1 decadal statistics of precipitation, temperature and cloud characteristics? Clim. Dyn. (minor revisions). Prein, Andreas F., Wolfgang Langhans, Giorgia Fosser, Andrew Ferrone, Nikolina Ban, Klaus Goergen, Michael Keller, Merja Tölle, Oliver Gutjahr, Frauke Feser, Erwan Brisson, Stefan Kollet, Juerg Schmidli, Nicole P. M. van Lipzig, Ruby Leung. (2015) A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. Reviews of Geophysics 53:10.1002/rog.v53.2, 323-361

Implementation of Malaria Dynamic Models in Municipality Level Early Warning Systems in Colombia. Part I: Description of Study Sites

PubMed Central

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M.; Quiñónes, Martha L.; Jiménez, Mónica M.; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J.; Thomson, Madeleine C.

2014-01-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. PMID:24891460

Variability in Terrestrial Water Storage and its effect on polar motion

NASA Astrophysics Data System (ADS)

Śliwińska, Justyna; Nastula, Jolanta

2017-04-01

Explaining the hydrological part of observed polar motion excitation has been a major challenge over a dozen years. The terrestrial water storage (TWS) excitation of polar motion - hydrological angular momentum (HAM), has been investigated widely using global hydrological models mainly at seasonal timescales. Unfortunately, the results from the models do not fully explain the role of hydrological signal in polar motion excitation. The determination of TWS from the Earth's gravity field observations represents an indirect approach for estimating land hydrology. Throughout the past decade, the Gravity Recovery and Climate Experiment (GRACE) has given an unprecedented view on global variations in Terrestrial Water Storage. Our investigations are focused on the influence of Terrestrial Water Storage (TWS) variations obtained from Gravity Recovery and Climate Experiment (GRACE) mission on polar motion excitation functions at decadal and inter-annual timescales. The global and regional trend, seasonal cycle as well as some extremes in TWS variations are considered here. Here TWS are obtained from the monthly mass grids land GRACE Tellus data: GRACE CSR RL05, GRACE GFZ RL05 and GRACE JPL RL05. As a comparative dataset, we also use TWS estimates determined from the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5). GRACE data and state-of-the-art CMIP5 climate models allow us to show the variability of hydrological part of polar motion under climate changes. Our studies include two steps: first, the determination and comparisons of regional patterns of TWS obtained from GRACE data and climate models, and second, comparison of the regional and global hydrological excitation functions of polar motion with a hydrological signal in the geodetic excitation functions of polar motion.

Extending the Confrontation of Weather and Climate Models from Soil Moisture to Surface Flux Data

NASA Astrophysics Data System (ADS)

Dirmeyer, P.; Chen, L.; Wu, J.

2016-12-01

The atmosphere and land components of weather and climate models are typically developed separately and coupled as a last step before new model versions are released. Separate testing of land surface models (LSMs) and atmospheric models is often quite extensive in the development phase, but validation of coupled land-atmosphere behavior is often minimal if performed at all. This is partly because of this piecemeal model development approach and partly because the necessary in situ data to confront coupled land-atmosphere models (LAMs) has been meager until quite recently. Over the past 10-20 years there has been a growing number of networks of measurements of land surface states, surface fluxes, radiation and near-surface meteorology, although they have been largely uncoordinated and frequently incomplete across the range of variables necessary to validate LAMs. We extend recent work "confronting" a variety of LSMs and LAMs with in situ observations of soil moisture from cross-standardized networks to comparisons with measurements of surface latent and sensible heat fluxes at FLUXNET sites in a variety of climate regimes around the world. The motivation is to determine how well LSMs represent observed statistics of variability and co-variability, how much models differ from one another, and how those statistics change when the LSMs are coupled to atmospheric models. Furthermore, comparisons are made to several LAMs in both open-loop (free running) and reanalysis configurations. This shows to what extent data assimilation can constrain the processes involved in flux variability, and helps illuminate model development pathways to improve coupled land-atmosphere interactions in weather and climate models.

WRF model sensitivity to land surface model and cumulus parameterization under short-term climate extremes over the southern Great Plains of the United States

Treesearch

Lisi Pei; Nathan Moore; Shiyuan Zhong; Lifeng Luo; David W. Hyndman; Warren E. Heilman; Zhiqiu Gao

2014-01-01

Extreme weather and climate events, especially short-term excessive drought and wet periods over agricultural areas, have received increased attention. The Southern Great Plains (SGP) is one of the largest agricultural regions in North America and features the underlying Ogallala-High Plains Aquifer system worth great economic value in large part due to production...

The role of large-scale eddies in the climate equilibrium. Part 2: Variable static stability

NASA Technical Reports Server (NTRS)

Zhou, Shuntai; Stone, Peter H.

1993-01-01

Lorenz's two-level model on a sphere is used to investigate how the results of Part 1 are modified when the interaction of the vertical eddy heat flux and static stability is included. In general, the climate state does not depend very much on whether or not this interaction is included, because the poleward eddy heat transport dominates the eddy forcing of mean temperature and wind fields. However, the climatic sensitivity is significantly affected. Compared to two-level model results with fixed static stability, the poleward eddy heat flux is less sensitive to the meridional temperature gradient and the gradient is more sensitive to the forcing. For example, the logarithmic derivative of the eddy flux with respect to the gradient has a slope that is reduced from approximately 15 on a beta-plane with fixed static stability and approximately 6 on a sphere with fixed static stability, to approximately 3 to 4 in the present model. This last result is more in line with analyses from observations. The present model also has a stronger baroclinic adjustment than that in Part 1, more like that in two-level beta-plane models with fixed static stability, that is, the midlatitude isentropic slope is very insensitive to the forcing, the diabatic heating, and the friction, unless the forcing is very weak.

Energy, environment and climate assessment using the MARKAL energy system model

EPA Science Inventory

As part of EPA ORD’s efforts to develop an understanding of the potential environmental impacts of future changes in energy use, the Energy and Climate Assessment Team has developed a database representation of the U.S. energy system for use with the MARKet ALlocation (MARK...

Future socio-economic impacts and vulnerabilities

Treesearch

Balgis Osman-Elasha; Neil Adger; Maria Brockhaus; Carol J. Pierce Colfer; Brent Sohngen; Tallaat Dafalla; Linda A. Joyce; Nkem Johnson; Carmenza Robledo

2009-01-01

The projected impacts of climate change are significant, and despite the uncertainties associated with current climate and ecosystem model projections, the associated changes in the provision of forest ecosystem services are expected to be substantial in many parts of the world. These impacts will present significant social and economic challenges for affected...

Bringing a Realistic Global Climate Modeling Experience to a Broader Audience

NASA Astrophysics Data System (ADS)

Sohl, L. E.; Chandler, M. A.; Zhou, J.

2010-12-01

EdGCM, the Educational Global Climate Model, was developed with the goal of helping students learn about climate change and climate modeling by giving them the ability to run a genuine NASA global climate model (GCM) on a desktop computer. Since EdGCM was first publicly released in January 2005, tens of thousands of users on seven continents have downloaded the software. EdGCM has been utilized by climate science educators from middle school through graduate school levels, and on occasion even by researchers who otherwise do not have ready access to climate model at national labs in the U.S. and elsewhere. The EdGCM software is designed to walk users through the same process a climate scientist would use in designing and running simulations, and analyzing and visualizing GCM output. Although the current interface design gives users a clear view of some of the complexities involved in using a climate model, it can be daunting for users whose main focus is on climate science rather than modeling per se. As part of the work funded by NASA’s Global Climate Change Education (GCCE) program, we will begin modifications to the user interface that will improve the accessibility of EdGCM to a wider array of users, especially at the middle school and high school levels, by: 1) Developing an automated approach (a “wizard”) to simplify the user experience in setting up new climate simulations; 2) Produce a catalog of “rediscovery experiments” that allow users to reproduce published climate model results, and in some cases compare model projections to real world data; and 3) Enhance distance learning and online learning opportunities through the development of a web-based interface. The prototypes for these modifications will then be presented to educators belonging to an EdGCM Users Group for feedback, so that we can further refine the EdGCM software, and thus deliver the tools and materials educators want and need across a wider range of learning environments.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-02-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease of evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

The influence of land cover change in the Asian monsoon region on present-day and mid-Holocene climate

NASA Astrophysics Data System (ADS)

Dallmeyer, A.; Claussen, M.

2011-06-01

Using the general circulation model ECHAM5/JSBACH, we investigate the biogeophysical effect of large-scale afforestation and deforestation in the Asian monsoon domain on present-day and mid-Holocene climate. We demonstrate that the applied land cover change does not only modify the local climate but also change the climate in North Africa and the Middle East via teleconnections. Deforestation in the Asian monsoon domain enhances the rainfall in North Africa. In parts of the Sahara summer precipitation is more than doubled. In contrast, afforestation strongly decreases summer rainfall in the Middle East and even leads to the cessation of the rainfall-activity in some parts of this region. Regarding the local climate, deforestation results in a reduction of precipitation and a cooler climate as grass mostly has a higher albedo than forests. However, in the core region of the Asian monsoon the decrease in evaporative cooling in the monsoon season overcompensates this signal and results in a net warming. Afforestation has mainly the opposite effect, although the pattern of change is less clear. It leads to more precipitation in most parts of the Asian monsoon domain and a warmer climate except for the southern regions where a stronger evaporation decreases near-surface temperatures in the monsoon season. When prescribing mid-Holocene insolation, the pattern of local precipitation change differs. Afforestation particularly increases monsoon rainfall in the region along the Yellow River which was the settlement area of major prehistoric cultures. In this region, the effect of land cover change on precipitation is half as large as the orbitally-induced precipitation change. Thus, our model results reveal that mid- to late-Holocene land cover change could strongly have contributed to the decreasing Asian monsoon precipitation during the Holocene known from reconstructions.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

Understanding How Biomass Burning Impacts Climate Change

ScienceCinema

Aiken, Allison

2018-06-12

Biomass burning in Africa is creating a plume that spreads across the Atlantic Ocean all the way to Brazil. Allison Aiken, a research scientist at Los Alamos National Laboratory, collects data about the black carbon aerosols within this plume and their impact on the environment to help improve global climate modeling. A leader in energy science, Los Alamos develops climate models in support of the Laboratory’s mission to strengthen the nation’s energy security. Allison’s work is part of FIDO, a field operations team funded by the Energy Department’s Office of Science’s ARM Climate Research Facility.

The potential impacts of climate change and variability on forests and forestry in the Mid-Atlantic Region

Treesearch

Mary McKenney-Easterling; David R. DeWalle; Louis R. Iverson; Anantha M. Prasad; Anthony R. Buda; Anthony R. Buda

2000-01-01

As part of the Mid-Atlantic Regional Assessment, an evaluation is being made of the impacts of climate variability and potential future climate change on forests and forestry in the Mid-Atlantic Region. This paper provides a brief overview of the current status of forests in the region, and then focuses on 2 components of this evaluation: (1) modeling of the potential...

Conceptual Model of Climate Change Impacts at LANL

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

Dewart, Jean Marie

Goal 9 of the LANL FY15 Site Sustainability Plan (LANL 2014a) addresses Climate Change Adaptation. As part of Goal 9, the plan reviews many of the individual programs the Laboratory has initiated over the past 20 years to address climate change impacts to LANL (e.g. Wildland Fire Management Plan, Forest Management Plan, etc.). However, at that time, LANL did not yet have a comprehensive approach to climate change adaptation. To fill this gap, the FY15 Work Plan for the LANL Long Term Strategy for Environmental Stewardship and Sustainability (LANL 2015) included a goal of (1) establishing a comprehensive conceptual modelmore » of climate change impacts at LANL and (2) establishing specific climate change indices to measure climate change and impacts at Los Alamos. Establishing a conceptual model of climate change impacts will demonstrate that the Laboratory is addressing climate change impacts in a comprehensive manner. This paper fulfills the requirement of goal 1. The establishment of specific indices of climate change at Los Alamos (goal 2), will improve our ability to determine climate change vulnerabilities and assess risk. Future work will include prioritizing risks, evaluating options/technologies/costs, and where appropriate, taking actions. To develop a comprehensive conceptual model of climate change impacts, we selected the framework provided in the National Oceanic and Atmospheric Administration (NOAA) Climate Resilience Toolkit (http://toolkit.climate.gov/).« less

Schistosoma japonicum transmission risk maps at present and under climate change in mainland China.

PubMed

Zhu, Gengping; Fan, Jingyu; Peterson, A Townsend

2017-10-01

The South-to-North Water Diversion (SNWD) project is designed to channel fresh water from the Yangtze River north to more industrialized parts of China. An important question is whether future climate change and dispersal via the SNWD may synergistically favor a northward expansion of species involved in hosting and transmitting schistosomiasis in China, specifically the intermediate host, Oncomelania hupensis. In this study, climate spaces occupied by the four subspecies of O. hupensis (O. h. hupensis, O. h. robertsoni, O. h. guangxiensis and O. h. tangi) were estimated, and niche conservatism tested among each pair of subspecies. Fine-tuned Maxent (fMaxent) and ensemble models were used to anticipate potential distributions of O. hupensis under future climate change scenarios. We were largely unable to reject the null hypothesis that climatic niches are conserved among the four subspecies, so factors other than climate appear to account for the divergence of O. hupensis populations across mainland China. Both model approaches indicated increased suitability and range expansion in O. h. hupensis in the future; an eastward and northward shift in O. h. robertsioni and O. h. guangxiensis, respectively; and relative distributional stability in O. h. gangi. The southern parts of the Central Route of SNWD will coincide with suitable areas for O. h. hupensis in 2050-2060; its suitable areas will also expand northward along the southern parts of the Eastern Route by 2080-2090. Our results call for rigorous monitoring and surveillance of schistosomiasis along the southern Central Route and Eastern Route of the SNWD in a future, warmer China.

Response of permafrost to projected climate change: Results from global offline model simulations with JSBACH

NASA Astrophysics Data System (ADS)

Blome, Tanja; Ekici, Altug; Beer, Christian; Hagemann, Stefan

2014-05-01

Permafrost or perennially frozen ground is an important part of the terrestrial cryosphere; roughly one quarter of Earth's land surface is underlain by permafrost. As it is a thermal phenomenon, its characteristics are highly dependent on climatic factors. The impact of the currently observed warming, which is projected to persist during the coming decades due to anthropogenic CO2 input, certainly has effects for the vast permafrost areas of the high northern latitudes. The quantification of these effects, however, is scientifically still an open question. This is partly due to the complexity of the system, where several feedbacks are interacting between land and atmosphere, sometimes counterbalancing each other. Moreover, until recently, many global circulation models (GCMs) lacked the sufficient representation of permafrost physics in their land surface schemes. In order to assess the response of permafrost to projected climate change for the 21st century, the land surface scheme of the Max-Planck-Institute for Meteorology, JSBACH, has recently been equipped with the important physical processes for permafrost studies, and was driven globally with bias corrected climate data, thereby spanning a period from 1850 until 2100. The applied land surface scheme JSBACH now considers the effects of freezing and thawing of soil water for both energy and water cycles, thermal properties depending on soil water and ice contents, and soil moisture movement being influenced by the presence of soil ice. To address the uncertainty range arising through different greenhouse gas concentrations as well as through different climate realisations when using various climate models, combinations of two Representative Concentration Pathways (RCPs) and two GCMs were used as driving data. In order to focus only on the climatic impact on permafrost, effects due to feedbacks between climate and permafrost (namely via carbon fluxes between land and atmosphere) are excluded in the experiments. Differences between future time slices and today's climate are analysed. The effect in relevant variables, such as permafrost extent, depth of the Active Layer, ground temperature, and amount of soil carbon, is investigated. The experiments (as well as the development of JSBACH with respect to permafrost soil physics) are part of the European project PAGE21, where a focus is set on interactions between the changing climate and its impact on permafrost, especially for the 21st century.

Climate vs. carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

NASA Astrophysics Data System (ADS)

Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

2014-02-01

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness; CO2 availability, in turn, constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence CO2 availability, the links between atmospheric CO2 and biomass burning are not well known. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to CO2 increase, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided Last Glacial Maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase 2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes in biomass burning were corrected for the model's observed biases in contemporary biome-average values. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux was 70 to 80% lower at the LGM than in PI time. LGM climate with pre-industrial CO2 (280 ppm) however yielded unrealistic results, with global and Northern Hemisphere biomass burning fluxes greater than in the pre-industrial climate. Using the PI CO2 concentration increased the modelled LGM biomass burning fluxes for all climate models and latitudinal bands to between four and ten times their values under LGM CO2 concentration. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on productivity and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

Solar Geoengineering as part of an overall strategy for meeting the 1.5C Paris target

NASA Astrophysics Data System (ADS)

Ricke, K.; MacMartin, D. G.; Keith, D.

2017-12-01

If future mitigation proves insufficient to limit the rise in global mean temperature to less than 1.5C above preindustrial, it is plausible that some additional and limited deployment of solar geoengineering could reduce climate damages. That is, these approaches could eventually be considered as part of an overall strategy to manage the risks of climate change, combining emissions reduction, net-negative emissions technologies, and solar geoengineering to meet climate goals. Since few climate model simulations have considered these limited deployment scenarios, we use a climate emulator trained from GeoMIP output to assess the projected response if solar geoengineering were used to limit global mean temperature to 1.5C above preindustrial in an overshoot scenario that would otherwise peak near 3C. The resulting climate is much closer in many respects to a climate where the 1.5C target is achieved through mitigation alone than either is to the 3C climate with no geoengineering, although there are some important differences. In this limited deployment scenario, there is no "over-compensation" of global-mean precipitation changes, nor are there any regions where a majority of models project that the use of geoengineering would lead to a statistically-significant change in precipitation further away from preindustrial than would have occurred without using geoengineering. This highlights the importance of evaluating geoengineering impacts in the context of specific policy-relevant scenarios.

Climate, weather, space weather: model development in an operational context

NASA Astrophysics Data System (ADS)

Folini, Doris

2018-05-01

Aspects of operational modeling for climate, weather, and space weather forecasts are contrasted, with a particular focus on the somewhat conflicting demands of "operational stability" versus "dynamic development" of the involved models. Some common key elements are identified, indicating potential for fruitful exchange across communities. Operational model development is compelling, driven by factors that broadly fall into four categories: model skill, basic physics, advances in computer architecture, and new aspects to be covered, from costumer needs over physics to observational data. Evaluation of model skill as part of the operational chain goes beyond an automated skill score. Permanent interaction between "pure research" and "operational forecast" people is beneficial to both sides. This includes joint model development projects, although ultimate responsibility for the operational code remains with the forecast provider. The pace of model development reflects operational lead times. The points are illustrated with selected examples, many of which reflect the author's background and personal contacts, notably with the Swiss Weather Service and the Max Planck Institute for Meteorology, Hamburg, Germany. In view of current and future challenges, large collaborations covering a range of expertise are a must - within and across climate, weather, and space weather. To profit from and cope with the rapid progress of computer architectures, supercompute centers must form part of the team.

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Development and application of downscaled hydroclimatic predictor variables for use in climate vulnerability and assessment studies

USGS Publications Warehouse

Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy

2012-01-01

This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process-based model with modules representing different hydrological pathways that can be inter-linked.

The impact of regional climate change on malaria risk due to greenhouse forcing and land-use changes in tropical Africa.

PubMed

Ermert, Volker; Fink, Andreas H; Morse, Andrew P; Paeth, Heiko

2012-01-01

Climate change will probably alter the spread and transmission intensity of malaria in Africa. In this study, we assessed potential changes in the malaria transmission via an integrated weather-disease model. We simulated mosquito biting rates using the Liverpool Malaria Model (LMM). The input data for the LMM were bias-corrected temperature and precipitation data from the regional model (REMO) on a 0.5° latitude-longitude grid. A Plasmodium falciparum infection model expands the LMM simulations to incorporate information on the infection rate among children. Malaria projections were carried out with this integrated weather-disease model for 2001 to 2050 according to two climate scenarios that include the effect of anthropogenic land-use and land-cover changes on climate. Model-based estimates for the present climate (1960 to 2000) are consistent with observed data for the spread of malaria in Africa. In the model domain, the regions where malaria is epidemic are located in the Sahel as well as in various highland territories. A decreased spread of malaria over most parts of tropical Africa is projected because of simulated increased surface temperatures and a significant reduction in annual rainfall. However, the likelihood of malaria epidemics is projected to increase in the southern part of the Sahel. In most of East Africa, the intensity of malaria transmission is expected to increase. Projections indicate that highland areas that were formerly unsuitable for malaria will become epidemic, whereas in the lower-altitude regions of the East African highlands, epidemic risk will decrease. We project that climate changes driven by greenhouse-gas and land-use changes will significantly affect the spread of malaria in tropical Africa well before 2050. The geographic distribution of areas where malaria is epidemic might have to be significantly altered in the coming decades.

Climatic effects of large-scale deforestation in Earth System Models

NASA Astrophysics Data System (ADS)

Brovkin, V.; Boysen, L.; Pongratz, J.

2017-12-01

Processes in terrestrial ecosystems, to a large extent, are controlled by climate and CO2 concentration. In turn, geographical distribution of vegetation cover strongly affects heat, moisture, and momentum fluxes between land surface and atmosphere (biogeophysical effects). Anthropogenic land use and land cover changes (LULCC) are now included into Earth System Models (ESMs) in the form of historical and hypothetical future scenarios as a forcing in the Coupled Model Intercomparison project, phase 6 (CMIP6). A propagation of climatic effects from land to the ocean in ESMs allows to investigate a global climate response to LULCC in addition to analysis of local effects over deforested land. One complication in the analysis of global climatic effects of historical and future LULCC scenarios is their relatively small amplitude. To increase the signal-to-noise ratio, the Land Use Model Intercomparison Project (LUMIP) suggested an idealized deforestation simulation following a prototype of 1%-CO2 increase experiment commonly used in CMIPs. The idealized experiment allows to investigate - in a harmonized way across models - a response of land surface biophysics and climate to a large-scale deforestation of 20 million km2 distributed over the most forested parts of globe. The forest is removed linearly over a period of 50 years, with an additional 30 years with no specified change in forest cover. Boundary conditions such as CO2 concentration and other forcings are kept at the pre-industrial level. We will present results of idealized deforestation experiments and other sensitivity runs with the CMIP6-version of MPI-ESM, which will be part of the later multi-model comparison. A special focus will be put on less well investigated aspects of LULCC that the idealized setup is particularly well suited for studying, such as non-linearities of the model response to the deforestation forcing and detectability of the signal over time.

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 1: Greenland (1958-2016)

NASA Astrophysics Data System (ADS)

Noël, Brice; van de Berg, Willem Jan; Melchior van Wessem, J.; van Meijgaard, Erik; van As, Dirk; Lenaerts, Jan T. M.; Lhermitte, Stef; Kuipers Munneke, Peter; Smeets, C. J. P. Paul; van Ulft, Lambertus H.; van de Wal, Roderik S. W.; van den Broeke, Michiel R.

2018-03-01

We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 (1958-2016). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

Climate Simulations based on a different-grid nested and coupled model

NASA Astrophysics Data System (ADS)

Li, Dan; Ji, Jinjun; Li, Yinpeng

2002-05-01

An atmosphere-vegetation interaction model (A VIM) has been coupled with a nine-layer General Cir-culation Model (GCM) of Institute of Atmospheic Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (IAP/LASG), which is rhomboidally truncated at zonal wave number 15, to simulate global climatic mean states. A VIM is a model having inter-feedback between land surface processes and eco-physiological processes on land. As the first step to couple land with atmosphere completely, the physiological processes are fixed and only the physical part (generally named the SVAT (soil-vegetation-atmosphere-transfer scheme) model) of AVIM is nested into IAP/LASG L9R15 GCM. The ocean part of GCM is prescribed and its monthly sea surface temperature (SST) is the climatic mean value. With respect to the low resolution of GCM, i.e., each grid cell having lon-gitude 7.5° and latitude 4.5°, the vegetation is given a high resolution of 1.5° by 1.5° to nest and couple the fine grid cells of land with the coarse grid cells of atmosphere. The coupling model has been integrated for 15 years and its last ten-year mean of outputs was chosen for analysis. Compared with observed data and NCEP reanalysis, the coupled model simulates the main characteris-tics of global atmospheric circulation and the fields of temperature and moisture. In particular, the simu-lated precipitation and surface air temperature have sound results. The work creates a solid base on coupling climate models with the biosphere.

Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries

USGS Publications Warehouse

Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won

2012-01-01

As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data.

PubMed

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960-2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60-70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

PubMed Central

Dalsgaard, Lise; Astrup, Rasmus; Antón-Fernández, Clara; Borgen, Signe Kynding; Breidenbach, Johannes; Lange, Holger; Lehtonen, Aleksi; Liski, Jari

2016-01-01

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures. PMID:26901763

Flood projections within the Niger River Basin under future land use and climate change.

PubMed

Aich, Valentin; Liersch, Stefan; Vetter, Tobias; Fournet, Samuel; Andersson, Jafet C M; Calmanti, Sandro; van Weert, Frank H A; Hattermann, Fred F; Paton, Eva N

2016-08-15

This study assesses future flood risk in the Niger River Basin (NRB), for the first time considering the simultaneous effects of both projected climate change and land use changes. For this purpose, an ecohydrological process-based model (SWIM) was set up and validated for past climate and land use dynamics of the entire NRB. Model runs for future flood risks were conducted with an ensemble of 18 climate models, 13 of them dynamically downscaled from the CORDEX Africa project and five statistically downscaled Earth System Models. Two climate and two land use change scenarios were used to cover a broad range of potential developments in the region. Two flood indicators (annual 90th percentile and the 20-year return flood) were used to assess the future flood risk for the Upper, Middle and Lower Niger as well as the Benue. The modeling results generally show increases of flood magnitudes when comparing a scenario period in the near future (2021-2050) with a base period (1976-2005). Land use effects are more uncertain, but trends and relative changes for the different catchments of the NRB seem robust. The dry areas of the Sahelian and Sudanian regions of the basin show a particularly high sensitivity to climatic and land use changes, with an alarming increase of flood magnitudes in parts. A scenario with continuing transformation of natural vegetation into agricultural land and urbanization intensifies the flood risk in all parts of the NRB, while a "regreening" scenario can reduce flood magnitudes to some extent. Yet, land use change effects were smaller when compared to the effects of climate change. In the face of an already existing adaptation deficit to catastrophic flooding in the region, the authors argue for a mix of adaptation and mitigation efforts in order to reduce the flood risk in the NRB. Copyright © 2016 Elsevier B.V. All rights reserved.

Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

NASA Astrophysics Data System (ADS)

Screen, James A.; Deser, Clara; Smith, Doug M.; Zhang, Xiangdong; Blackport, Russell; Kushner, Paul J.; Oudar, Thomas; McCusker, Kelly E.; Sun, Lantao

2018-03-01

The decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.

Anthropogenic albedo changes and the earth's climate

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

Sagan, C.; Toole, O.B.; Pollack, J.B.

1979-12-21

Investigators have long discounted the possibility that anthropogenic environmental changes not involving sophisticated modern technology could significantly influence climate. However, physical models suggest a causal connection between several such changes and significant climatic variation experienced in many regions of the world. In the Rajasthan Desert, parts of the Sahara, and Lebanon, overgrazing and lack of vegetation have led to desertification of once-fertile areas. The deforestation of parts of Brazil, Indonesia, and African equatorial forests by residents of those areas, and the extensive North American and European deforestation that occurred during the Little Ice Age demonstrate the relationship between temperate deforestationmore » and macroclimatic change. (32 references, 2 tables)« less

Representative Agricultural Pathways and Climate Impact Assessment for Pacific Northwest Agricultural Systems

NASA Astrophysics Data System (ADS)

MU, J.; Antle, J. M.; Zhang, H.; Capalbo, S. M.; Eigenbrode, S.; Kruger, C.; Stockle, C.; Wolfhorst, J. D.

2013-12-01

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.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

Decadal application of WRF/chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 2: Current vs. future simulations

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Campbell, Patrick; Zhang, Yang

2017-03-01

Following a comprehensive model evaluation, this Part II paper presents projected changes in future (2046-2055) climate, air quality, and their interactions under the RCP4.5 and RCP8.5 scenarios using the Weather, Research and Forecasting model with Chemistry (WRF/Chem). In general, both WRF/Chem RCP4.5 and RCP8.5 simulations predict similar increases on average (∼2 °C) for 2-m temperature (T2) but different spatial distributions of the projected changes in T2, 2-m relative humidity, 10-m wind speed, precipitation, and planetary boundary layer height, due to differences in the spatial distributions of projected emissions, and their feedbacks into climate. Future O3 mixing ratios will decrease for most parts of the U.S. under the RCP4.5 scenario but increase for all areas under the RCP8.5 scenario due to higher projected temperature, greenhouse gas concentrations and biogenic volatile organic compounds (VOC) emissions, higher O3 values for boundary conditions, and disbenefit of NOx reduction and decreased NO titration over VOC-limited O3 chemistry regions. Future PM2.5 concentrations will decrease for both RCP4.5 and RCP8.5 scenarios with different trends in projected concentrations of individual PM species. Total cloud amounts decrease under both scenarios in the future due to decreases in PM and cloud droplet number concentration thus increased radiation. Those results illustrate the impacts of carbon policies with different degrees of emission reductions on future climate and air quality. The WRF/Chem and WRF simulations show different spatial patterns for projected changes in T2 for future decade, indicating different impacts of prognostic and prescribed gas/aerosol concentrations, respectively, on climate change.

An index-based robust decision making framework for watershed management in a changing climate.

PubMed

Kim, Yeonjoo; Chung, Eun-Sung

2014-03-01

This study developed an index-based robust decision making framework for watershed management dealing with water quantity and quality issues in a changing climate. It consists of two parts of management alternative development and analysis. The first part for alternative development consists of six steps: 1) to understand the watershed components and process using HSPF model, 2) to identify the spatial vulnerability ranking using two indices: potential streamflow depletion (PSD) and potential water quality deterioration (PWQD), 3) to quantify the residents' preferences on water management demands and calculate the watershed evaluation index which is the weighted combinations of PSD and PWQD, 4) to set the quantitative targets for water quantity and quality, 5) to develop a list of feasible alternatives and 6) to eliminate the unacceptable alternatives. The second part for alternative analysis has three steps: 7) to analyze all selected alternatives with a hydrologic simulation model considering various climate change scenarios, 8) to quantify the alternative evaluation index including social and hydrologic criteria with utilizing multi-criteria decision analysis methods and 9) to prioritize all options based on a minimax regret strategy for robust decision. This framework considers the uncertainty inherent in climate models and climate change scenarios with utilizing the minimax regret strategy, a decision making strategy under deep uncertainty and thus this procedure derives the robust prioritization based on the multiple utilities of alternatives from various scenarios. In this study, the proposed procedure was applied to the Korean urban watershed, which has suffered from streamflow depletion and water quality deterioration. Our application shows that the framework provides a useful watershed management tool for incorporating quantitative and qualitative information into the evaluation of various policies with regard to water resource planning and management. Copyright © 2013 Elsevier B.V. All rights reserved.

Skilful multi-year predictions of tropical trans-basin climate variability

PubMed Central

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-01-01

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

Skilful multi-year predictions of tropical trans-basin climate variability.

PubMed

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-04-21

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

Coupled Climate-Economy-Biosphere (CoCEB) model - Part 2: Deforestation control and investment in carbon capture and storage technologies

NASA Astrophysics Data System (ADS)

Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.

2015-04-01

This study uses the global climate-economy-biosphere (CoCEB) model developed in Part 1 to investigate economic aspects of deforestation control and carbon sequestration in forests, as well as the efficiency of carbon capture and storage (CCS) technologies as policy measures for climate change mitigation. We assume - as in Part 1 - that replacement of one technology with another occurs in terms of a logistic law, so that the same law also governs the dynamics of reduction in carbon dioxide emission using CCS technologies. In order to take into account the effect of deforestation control, a slightly more complex description of the carbon cycle than in Part 1 is needed. Consequently, we add a biomass equation into the CoCEB model and analyze the ensuing feedbacks and their effects on per capita gross domestic product (GDP) growth. Integrating biomass into the CoCEB and applying deforestation control as well as CCS technologies has the following results: (i) low investment in CCS contributes to reducing industrial carbon emissions and to increasing GDP, but further investment leads to a smaller reduction in emissions, as well as in the incremental GDP growth; and (ii) enhanced deforestation control contributes to a reduction in both deforestation emissions and in atmospheric carbon dioxide concentration, thus reducing the impacts of climate change and contributing to a slight appreciation of GDP growth. This effect is however very small compared to that of low-carbon technologies or CCS. We also find that the result in (i) is very sensitive to the formulation of CCS costs, while to the contrary, the results for deforestation control are less sensitive.

Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies

NASA Astrophysics Data System (ADS)

Shellito, Cindy J.; Sloan, Lisa C.

2006-02-01

Models that allow vegetation to respond to and interact with climate provide a unique method for addressing questions regarding feedbacks between the ecosystem and climate in pre-Quaternary time periods. In this paper, we consider how Dynamic Global Vegetation Models (DGVMs), which have been developed for simulations with present day climate, can be used for paleoclimate studies. We begin with a series of tests in the NCAR Land Surface Model (LSM)-DGVM with Eocene geography to examine (1) the effect of removing C 4 grasses from the available plant functional types in the model; (2) model sensitivity to a change in soil texture; and (3), model sensitivity to a change in the value of pCO 2 used in the photosynthetic rate equations. The tests were designed to highlight some of the challenges of using these models and prompt discussion of possible improvements. We discuss how lack of detail in model boundary conditions, uncertainties in the application of modern plant functional types to paleo-flora simulations, and inaccuracies in the model climatology used to drive the DGVM can affect interpretation of model results. However, we also review a number of DGVM features that can facilitate understanding of past climates and offer suggestions for improving paleo-DGVM studies.

Military Cooperation Frameworks: Effective Models to Address Transnational Security Challenges of the Asia-Pacific Region

DTIC Science & Technology

2011-05-04

evolving security challenges. Issues such as terrorism, proliferation of weapons of mass destruction, impacts of climate change , and the ever...impacts of climate change , and the ever-growing competition for valuable natural resources are a few of the these challenges. As an integral part...destruction, impacts of climate change , and the ever-growing competition for valuable natural resources have resulted in a new set of security

A Case Study: Climate Change Decision Support for the Apalachicola, Chattahoochee, Flint Basins

NASA Astrophysics Data System (ADS)

Day, G. N.; McMahon, G.; Friesen, N.; Carney, S.

2011-12-01

Riverside Technology, inc. has developed a Climate Change Decision Support System (DSS) to provide water managers with a tool to explore a range of current Global Climate Model (GCM) projections to evaluate their potential impacts on streamflow and the reliability of future water supplies. The system was developed as part of a National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) project. The DSS uses downscaled GCM data as input to small-scale watershed models to produce time series of projected undepleted streamflow for various emission scenarios and GCM simulations. Until recently, water managers relied on historical streamflow data for water resources planning. In many parts of the country, great effort has been put into estimating long-term historical undepleted streamflow accounting for regulation, diversions, and return flows to support planning and water rights administration. In some cases, longer flow records have been constructed using paleohydrologic data in an attempt to capture climate variability beyond what is evident during the observed historical record. Now, many water managers are recognizing that historical data may not be representative of an uncertain climate future, and they have begun to explore the use of climate projections in their water resources planning. The Climate Change DSS was developed to support water managers in planning by accounting for both climate variability and potential climate change. In order to use the information for impact analysis, the projected streamflow time series can be exported and substituted for the historical streamflow data traditionally applied in their system operations models for water supply planning. This paper presents a case study in which climate-adjusted flows are coupled with the U.S. Army Corps of Engineers (USACE) ResSim model for the Apalachicola, Chattahoochee, and Flint (ACF) River basins. The study demonstrates how climate scenarios can be used with existing or proposed operating rules to explore the range of potential climate impacts on lake levels, drought trigger frequency, hydropower generation, and low-flow statistics. Initial system implementation of the Climate Change DSS was focused in the State of Colorado working with water supply agencies in the Front Range to assess local water supply vulnerability to climate change. To facilitate national implementation, the system capitalizes on National Weather Service (NWS) watershed models currently used for operational river forecasting. These models are well calibrated and available for the entire country. The system has been extended to include the ACF and the Sacramento River basins because of the importance of the water resources in these basins. Plans are now being made to expand coverage to include the Baltimore-Washington, D.C. water supply area. The DSS is operational and publicly available (www.climatechangedss.com).

Humor Climate of the Primary Schools

ERIC Educational Resources Information Center

Sahin, Ahmet

2018-01-01

The aim of this study is to determine the opinions primary school administrators and teachers on humor climates in primary schools. The study was modeled as a convergent parallel design, one of the mixed methods. The data gathered from 253 administrator questionnaires, and 651 teacher questionnaires was evaluated for the quantitative part of the…

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

Climate Change Impacts on Hydrology and Water Management of the San Juan Basin

NASA Astrophysics Data System (ADS)

Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.

2005-12-01

Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.

Modelling coffee leaf rust risk in Colombia with climate reanalysis data.

PubMed

Bebber, Daniel P; Castillo, Ángela Delgado; Gurr, Sarah J

2016-12-05

Many fungal plant diseases are strongly controlled by weather, and global climate change is thus likely to have affected fungal pathogen distributions and impacts. Modelling the response of plant diseases to climate change is hampered by the difficulty of estimating pathogen-relevant microclimatic variables from standard meteorological data. The availability of increasingly sophisticated high-resolution climate reanalyses may help overcome this challenge. We illustrate the use of climate reanalyses by testing the hypothesis that climate change increased the likelihood of the 2008-2011 outbreak of Coffee Leaf Rust (CLR, Hemileia vastatrix) in Colombia. We develop a model of germination and infection risk, and drive this model using estimates of leaf wetness duration and canopy temperature from the Japanese 55-Year Reanalysis (JRA-55). We model germination and infection as Weibull functions with different temperature optima, based upon existing experimental data. We find no evidence for an overall trend in disease risk in coffee-growing regions of Colombia from 1990 to 2015, therefore, we reject the climate change hypothesis. There was a significant elevation in predicted CLR infection risk from 2008 to 2011 compared with other years. JRA-55 data suggest a decrease in canopy surface water after 2008, which may have helped terminate the outbreak. The spatial resolution and accuracy of climate reanalyses are continually improving, increasing their utility for biological modelling. Confronting disease models with data requires not only accurate climate data, but also disease observations at high spatio-temporal resolution. Investment in monitoring, storage and accessibility of plant disease observation data are needed to match the quality of the climate data now available.This article is part of the themed issue 'Tackling emerging fungal threats to animal health, food security and ecosystem resilience'. © 2016 The Authors.

Development of a High-Resolution Climate Model for Future Climate Change Projection on the Earth Simulator

NASA Astrophysics Data System (ADS)

Kanzawa, H.; Emori, S.; Nishimura, T.; Suzuki, T.; Inoue, T.; Hasumi, H.; Saito, F.; Abe-Ouchi, A.; Kimoto, M.; Sumi, A.

2002-12-01

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).

Constraints and potentials of future irrigation water availability on agricultural production under climate change.

PubMed

Elliott, Joshua; Deryng, Delphine; Müller, Christoph; Frieler, Katja; Konzmann, Markus; Gerten, Dieter; Glotter, Michael; Flörke, Martina; Wada, Yoshihide; Best, Neil; Eisner, Stephanie; Fekete, Balázs M; Folberth, Christian; Foster, Ian; Gosling, Simon N; Haddeland, Ingjerd; Khabarov, Nikolay; Ludwig, Fulco; Masaki, Yoshimitsu; Olin, Stefan; Rosenzweig, Cynthia; Ruane, Alex C; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Tang, Qiuhong; Wisser, Dominik

2014-03-04

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400-1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

High-resolution ensemble projections of near-term regional climate over the continental United States

DOE PAGES

Ashfaq, Moetasim; Rastogi, Deeksha; Mei, Rui; ...

2016-09-01

We present high-resolution near-term ensemble projections of hydro-climatic changes over the contiguous U.S. using a regional climate model (RegCM4) that dynamically downscales 11 Global Climate Models from the 5th phase of Coupled Model Inter-comparison Project at 18km horizontal grid spacing. All model integrations span 41 years in the historical period (1965 – 2005) and 41 years in the near-term future period (2010 – 2050) under Representative Concentration Pathway 8.5 and cover a domain that includes the contiguous U.S. and parts of Canada and Mexico. Should emissions continue to rise, surface temperatures in every region within the U.S. will reach amore » new climate norm well before mid 21st century regardless of the magnitudes of regional warming. Significant warming will likely intensify the regional hydrological cycle through the acceleration of the historical trends in cold, warm and wet extremes. The future temperature response will be partly regulated by changes in snow hydrology over the regions that historically receive a major portion of cold season precipitation in the form of snow. Our results indicate the existence of the Clausius-Clapeyron scaling at regional scales where per degree centigrade rise in surface temperature will lead to a 7.4% increase in precipitation from extremes. More importantly, both winter (snow) and summer (liquid) extremes are projected to increase across the U.S. These changes in precipitation characteristics will be driven by a shift towards shorter and wetter seasons. Altogether, projected changes in the regional hydro-climate can have substantial impacts on the natural and human systems across the U.S.« less

Strategies for Effective Implementation of Science Models into 6-9 Grade Classrooms on Climate, Weather, and Energy Topics

NASA Astrophysics Data System (ADS)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2011-12-01

As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. According to the National Science Education Standards, teachers are encouraged to science models into the classroom as a way to aid in the understanding of the nature of science. However, there is very little description of what constitutes a science model, so the term is often associated with scale models. Therefore, teachers often use drawings or scale representations of physical entities, such as DNA, the solar system, or bacteria. In other words, models used in classrooms are often used as visual representations, but the purpose of science models is often overlooked. The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. However, there are few resources available to help teachers implement science models into the science curriculum effectively. Therefore, this research project looks at strategies middle school science teachers use to implement science models into their classrooms. These teachers in this study took part in a week-long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The goal of this project is to describe the professional development and describe how teachers intend to incorporate science models into each of their individual classrooms.

Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.

Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 1: Theory

NASA Astrophysics Data System (ADS)

Sundberg, R.; Moberg, A.; Hind, A.

2012-08-01

A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

Solar geoengineering as part of an overall strategy for meeting the 1.5°C Paris target.

PubMed

MacMartin, Douglas G; Ricke, Katharine L; Keith, David W

2018-05-13

Solar geoengineering refers to deliberately reducing net radiative forcing by reflecting some sunlight back to space, in order to reduce anthropogenic climate changes; a possible such approach would be adding aerosols to the stratosphere. If future mitigation proves insufficient to limit the rise in global mean temperature to less than 1.5°C above preindustrial, it is plausible that some additional and limited deployment of solar geoengineering could reduce climate damages. That is, these approaches could eventually be considered as part of an overall strategy to manage the risks of climate change, combining emissions reduction, net-negative emissions technologies and solar geoengineering to meet climate goals. We first provide a physical-science review of current research, research trends and some of the key gaps in knowledge that would need to be addressed to support informed decisions. Next, since few climate model simulations have considered these limited-deployment scenarios, we synthesize prior results to assess the projected response if solar geoengineering were used to limit global mean temperature to 1.5°C above preindustrial in an overshoot scenario that would otherwise peak near 3°C. While there are some important differences, the resulting climate is closer in many respects to a climate where the 1.5°C target is achieved through mitigation alone than either is to the 3°C climate with no geoengineering. This holds for both regional temperature and precipitation changes; indeed, there are no regions where a majority of models project that this moderate level of geoengineering would produce a statistically significant shift in precipitation further away from preindustrial levels.This article is part of the theme issue 'The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'. © 2018 The Author(s).

Solar geoengineering as part of an overall strategy for meeting the 1.5°C Paris target

NASA Astrophysics Data System (ADS)

MacMartin, Douglas G.; Ricke, Katharine L.; Keith, David W.

2018-05-01

Solar geoengineering refers to deliberately reducing net radiative forcing by reflecting some sunlight back to space, in order to reduce anthropogenic climate changes; a possible such approach would be adding aerosols to the stratosphere. If future mitigation proves insufficient to limit the rise in global mean temperature to less than 1.5°C above preindustrial, it is plausible that some additional and limited deployment of solar geoengineering could reduce climate damages. That is, these approaches could eventually be considered as part of an overall strategy to manage the risks of climate change, combining emissions reduction, net-negative emissions technologies and solar geoengineering to meet climate goals. We first provide a physical-science review of current research, research trends and some of the key gaps in knowledge that would need to be addressed to support informed decisions. Next, since few climate model simulations have considered these limited-deployment scenarios, we synthesize prior results to assess the projected response if solar geoengineering were used to limit global mean temperature to 1.5°C above preindustrial in an overshoot scenario that would otherwise peak near 3°C. While there are some important differences, the resulting climate is closer in many respects to a climate where the 1.5°C target is achieved through mitigation alone than either is to the 3°C climate with no geoengineering. This holds for both regional temperature and precipitation changes; indeed, there are no regions where a majority of models project that this moderate level of geoengineering would produce a statistically significant shift in precipitation further away from preindustrial levels. This article is part of the theme issue `The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the use of conceptual models for hydrological projections in northern Tunisia.

Characterizing and Addressing the Need for Statistical Adjustment of Global Climate Model Data

NASA Astrophysics Data System (ADS)

White, K. D.; Baker, B.; Mueller, C.; Villarini, G.; Foley, P.; Friedman, D.

2017-12-01

As part of its mission to research and measure the effects of the changing climate, the U. S. Army Corps of Engineers (USACE) regularly uses the World Climate Research Programme's Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset. However, these data are generated at a global level and are not fine-tuned for specific watersheds. This often causes CMIP5 output to vary from locally observed patterns in the climate. Several downscaling methods have been developed to increase the resolution of the CMIP5 data and decrease systemic differences to support decision-makers as they evaluate results at the watershed scale. Evaluating preliminary comparisons of observed and projected flow frequency curves over the US revealed a simple framework for water resources decision makers to plan and design water resources management measures under changing conditions using standard tools. Using this framework as a basis, USACE has begun to explore to use of statistical adjustment to alter global climate model data to better match the locally observed patterns while preserving the general structure and behavior of the model data. When paired with careful measurement and hypothesis testing, statistical adjustment can be particularly effective at navigating the compromise between the locally observed patterns and the global climate model structures for decision makers.

Observationally-based Metrics of Ocean Carbon and Biogeochemical Variables are Essential for Evaluating Earth System Model Projections

NASA Astrophysics Data System (ADS)

Russell, J. L.; Sarmiento, J. L.

2017-12-01

The Southern Ocean is central to the climate's response to increasing levels of atmospheric greenhouse gases as it ventilates a large fraction of the global ocean volume. Global coupled climate models and earth system models, however, vary widely in their simulations of the Southern Ocean and its role in, and response to, the ongoing anthropogenic forcing. Due to its complex water-mass structure and dynamics, Southern Ocean carbon and heat uptake depend on a combination of winds, eddies, mixing, buoyancy fluxes and topography. Understanding how the ocean carries heat and carbon into its interior and how the observed wind changes are affecting this uptake is essential to accurately projecting transient climate sensitivity. Observationally-based metrics are critical for discerning processes and mechanisms, and for validating and comparing climate models. As the community shifts toward Earth system models with explicit carbon simulations, more direct observations of important biogeochemical parameters, like those obtained from the biogeochemically-sensored floats that are part of the Southern Ocean Carbon and Climate Observations and Modeling project, are essential. One goal of future observing systems should be to create observationally-based benchmarks that will lead to reducing uncertainties in climate projections, and especially uncertainties related to oceanic heat and carbon uptake.

A new framework for climate sensitivity and prediction: a modelling perspective

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.

The future of the Devon Ice cap: results from climate and ice dynamics modelling

NASA Astrophysics Data System (ADS)

Mottram, Ruth; Rodehacke, Christian; Boberg, Fredrik

2017-04-01

The Devon Ice Cap is an example of a relatively well monitored small ice cap in the Canadian Arctic. Close to Greenland, it shows a similar surface mass balance signal to glaciers in western Greenland. Here we use high resolution (5km) simulations from HIRHAM5 to drive the PISM glacier model in order to model the present day and future prospects of this small Arctic ice cap. Observational data from the Devon Ice Cap in Arctic Canada is used to evaluate the surface mass balance (SMB) data output from the HIRHAM5 model for simulations forced with the ERA-Interim climate reanalysis data and the historical emissions scenario run by the EC-Earth global climate model. The RCP8.5 scenario simulated by EC-Earth is also downscaled by HIRHAM5 and this output is used to force the PISM model to simulate the likely future evolution of the Devon Ice Cap under a warming climate. We find that the Devon Ice Cap is likely to continue its present day retreat, though in the future increased precipitation partly offsets the enhanced melt rates caused by climate change.

Perspectives on Climate Effects on Agriculture: The International Efforts of AgMIP in Sub-Saharan Africa

NASA Technical Reports Server (NTRS)

Kihara, Job; MacCarthy, Dilys S.; Bationo, Andre; Koala, Saidou; Hickman, Jonathon; Koo, Jawoo; Vanya, Charles; Adiku, Samuel; Beletse, Yacob; Masikate, Patricia;

Climate versus carbon dioxide controls on biomass burning: a model analysis of the glacial-interglacial contrast

NASA Astrophysics Data System (ADS)

Calvo, M. Martin; Prentice, I. C.; Harrison, S. P.

2014-11-01

Climate controls fire regimes through its influence on the amount and types of fuel present and their dryness. CO2 concentration constrains primary production by limiting photosynthetic activity in plants. However, although fuel accumulation depends on biomass production, and hence on CO2 concentration, the quantitative relationship between atmospheric CO2 concentration and biomass burning is not well understood. Here a fire-enabled dynamic global vegetation model (the Land surface Processes and eXchanges model, LPX) is used to attribute glacial-interglacial changes in biomass burning to an increase in CO2, which would be expected to increase primary production and therefore fuel loads even in the absence of climate change, vs. climate change effects. Four general circulation models provided last glacial maximum (LGM) climate anomalies - that is, differences from the pre-industrial (PI) control climate - from the Palaeoclimate Modelling Intercomparison Project Phase~2, allowing the construction of four scenarios for LGM climate. Modelled carbon fluxes from biomass burning were corrected for the model's observed prediction biases in contemporary regional average values for biomes. With LGM climate and low CO2 (185 ppm) effects included, the modelled global flux at the LGM was in the range of 1.0-1.4 Pg C year-1, about a third less than that modelled for PI time. LGM climate with pre-industrial CO2 (280 ppm) yielded unrealistic results, with global biomass burning fluxes similar to or even greater than in the pre-industrial climate. It is inferred that a substantial part of the increase in biomass burning after the LGM must be attributed to the effect of increasing CO2 concentration on primary production and fuel load. Today, by analogy, both rising CO2 and global warming must be considered as risk factors for increasing biomass burning. Both effects need to be included in models to project future fire risks.

An Improved Radiative Transfer Model for Climate Calculations

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Hydrological Modeling in the Bull Run Watershed in Support of a Piloting Utility Modeling Applications (PUMA) Project

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chiao, T. H.; Lettenmaier, D. P.; Vano, J. A.

2016-12-01

Hydrologic models with varying complexities and structures are commonly used to evaluate the impact of climate change on future hydrology. While the uncertainties in future climate projections are well documented, uncertainties in streamflow projections associated with hydrologic model structure and parameter estimation have received less attention. In this study, we implemented and calibrated three hydrologic models (the Distributed Hydrology Soil Vegetation Model (DHSVM), the Precipitation-Runoff Modeling System (PRMS), and the Variable Infiltration Capacity model (VIC)) for the Bull Run watershed in northern Oregon using consistent data sources and best practice calibration protocols. The project was part of a Piloting Utility Modeling Applications (PUMA) project with the Portland Water Bureau (PWB) under the umbrella of the Water Utility Climate Alliance (WUCA). Ultimately PWB would use the model evaluation to select a model to perform in-house climate change analysis for Bull Run Watershed. This presentation focuses on the experimental design of the comparison project, project findings and the collaboration between the team at the University of Washington and at PWB. After calibration, the three models showed similar capability to reproduce seasonal and inter-annual variations in streamflow, but differed in their ability to capture extreme events. Furthermore, the annual and seasonal hydrologic sensitivities to changes in climate forcings differed among models, potentially attributable to different model representations of snow and vegetation processes.

Assessing the Impact of Climatic Variability and Change on Maize Production in the Midwestern USA

NASA Astrophysics Data System (ADS)

Andresen, J.; Jain, A. K.; Niyogi, D. S.; Alagarswamy, G.; Biehl, L.; Delamater, P.; Doering, O.; Elias, A.; Elmore, R.; Gramig, B.; Hart, C.; Kellner, O.; Liu, X.; Mohankumar, E.; Prokopy, L. S.; Song, C.; Todey, D.; Widhalm, M.

2013-12-01

Weather and climate remain among the most important uncontrollable factors in agricultural production systems. In this study, three process-based crop simulation models were used to identify the impacts of climate on the production of maize in the Midwestern U.S.A. during the past century. The 12-state region is a key global production area, responsible for more than 80% of U.S. domestic and 25% of total global production. The study is a part of the Useful to Useable (U2U) Project, a USDA NIFA-sponsored project seeking to improve the resilience and profitability of farming operations in the region amid climate variability and change. Three process-based crop simulation models were used in the study: CERES-Maize (DSSAT, Hoogenboom et al., 2012), the Hybrid-Maize model (Yang et al., 2004), and the Integrated Science Assessment Model (ISAM, Song et al., 2013). Model validation was carried out with individual plot and county observations. The models were run with 4 to 50 km spatial resolution gridded weather data for representative soils and cultivars, 1981-2012, to examine spatial and temporal yield variability within the region. We also examined the influence of different crop models and spatial scales on regional scale yield estimation, as well as a yield gap analysis between observed and attainable yields. An additional study was carried out with the CERES-Maize model at 18 individual site locations 1901-2012 to examine longer term historical trends. For all simulations, all input variables were held constant in order to isolate the impacts of climate. In general, the model estimates were in good agreement with observed yields, especially in central sections of the region. Regionally, low precipitation and soil moisture stress were chief limitations to simulated crop yields. The study suggests that at least part of the observed yield increases in the region during recent decades have occurred as the result of wetter, less stressful growing season weather conditions.

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

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

Strzepek, K.; Neumann, Jim; Smith, Joel

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

Benefits of Greenhouse Gas Mitigation on the Supply, Management, and Use of Water Resources in the United States

DOE PAGES

Strzepek, K.; Neumann, Jim; Smith, Joel; ...

2014-11-29

Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less

Schistosoma japonicum transmission risk maps at present and under climate change in mainland China

PubMed Central

Fan, Jingyu; Peterson, A. Townsend

2017-01-01

Background The South-to-North Water Diversion (SNWD) project is designed to channel fresh water from the Yangtze River north to more industrialized parts of China. An important question is whether future climate change and dispersal via the SNWD may synergistically favor a northward expansion of species involved in hosting and transmitting schistosomiasis in China, specifically the intermediate host, Oncomelania hupensis. Methodology/ Principal findings In this study, climate spaces occupied by the four subspecies of O. hupensis (O. h. hupensis, O. h. robertsoni, O. h. guangxiensis and O. h. tangi) were estimated, and niche conservatism tested among each pair of subspecies. Fine-tuned Maxent (fMaxent) and ensemble models were used to anticipate potential distributions of O. hupensis under future climate change scenarios. We were largely unable to reject the null hypothesis that climatic niches are conserved among the four subspecies, so factors other than climate appear to account for the divergence of O. hupensis populations across mainland China. Both model approaches indicated increased suitability and range expansion in O. h. hupensis in the future; an eastward and northward shift in O. h. robertsioni and O. h. guangxiensis, respectively; and relative distributional stability in O. h. gangi. Conclusions/Significance The southern parts of the Central Route of SNWD will coincide with suitable areas for O. h. hupensis in 2050–2060; its suitable areas will also expand northward along the southern parts of the Eastern Route by 2080–2090. Our results call for rigorous monitoring and surveillance of schistosomiasis along the southern Central Route and Eastern Route of the SNWD in a future, warmer China. PMID:29040273

Climate change impact on North Sea wave conditions: a consistent analysis of ten projections

NASA Astrophysics Data System (ADS)

Grabemann, Iris; Groll, Nikolaus; Möller, Jens; Weisse, Ralf

2015-02-01

Long-term changes in the mean and extreme wind wave conditions as they may occur in the course of anthropogenic climate change can influence and endanger human coastal and offshore activities. A set of ten wave climate projections derived from time slice and transient simulations of future conditions is analyzed to estimate the possible impact of anthropogenic climate change on mean and extreme wave conditions in the North Sea. This set includes different combinations of IPCC SRES emission scenarios (A2, B2, A1B, and B1), global and regional models, and initial states. A consistent approach is used to provide a more robust assessment of expected changes and uncertainties. While the spatial patterns and the magnitude of the climate change signals vary, some robust features among the ten projections emerge: mean and severe wave heights tend to increase in the eastern parts of the North Sea towards the end of the twenty-first century in nine to ten projections, but the magnitude of the increase in extreme waves varies in the order of decimeters between these projections. For the western parts of the North Sea more than half of the projections suggest a decrease in mean and extreme wave heights. Comparing the different sources of uncertainties due to models, scenarios, and initial conditions, it can be inferred that the influence of the emission scenario on the climate change signal seems to be less important. Furthermore, the transient projections show strong multi-decadal fluctuations, and changes towards the end of the twenty-first century might partly be associated with internal variability rather than with systematic changes.

Long-run evolution of the global economy: 2. Hindcasts of innovation and growth

NASA Astrophysics Data System (ADS)

Garrett, T. J.

2015-03-01

Long-range climate forecasts rely upon integrated assessment models that link the global economy to greenhouse gas emissions. This paper evaluates an alternative economic framework, outlined in Part 1, that is based on physical principles rather than explicitly resolved societal dynamics. Relative to a reference model of persistence in trends, model hindcasts that are initialized with data from 1950 to 1960 reproduce trends in global economic production and energy consumption between 2000 and 2010 with a skill score greater than 90%. In part, such high skill appears to be because civilization has responded to an impulse of fossil fuel discovery in the mid-twentieth century. Forecasting the coming century will be more of a challenge because the effect of the impulse appears to have nearly run its course. Nonetheless, the model offers physically constrained futures for the coupled evolution of civilization and climate during the Anthropocene.

Perspectives on Hydro-Climatic Change in Rivers Sourced From the Khangai Mountains, Mongolia

NASA Astrophysics Data System (ADS)

Venable, N. B.; Fassnacht, S. R.; Tumenjargal, S.; Batbuyan, B.; Odgarav, J.; Sukhbataar, J.; Fernandez-Gimenez, M.; Adyabadam, G.

2012-12-01

Patterns of pastoralism have shaped the Mongolian countryside throughout history. These patterns are largely dictated by seasonal and extreme climate and water conditions. While change has always been a part of the traditional herder lifestyle, the magnitude and variety of impacts imposed by natural and human-induced changes in the last few decades has increased, negatively affecting the coupled natural-human systems of Mongolia. Regional hydrologic impacts from increased mining, irrigation, urbanization, and climate change are challenging to measure and model due to sparse and relatively short meteorological and hydrological records. Characterization of the variability inherent in Mongolian hydrological systems in the international literature remains limited. To quantify recent changes to these systems, several river basins near the Khangai Mountains were analyzed. These basins adjoin and include community-based managed and non-managed grazing lands under study as part of an ongoing National Science Foundation Coupled Natural and Human Systems (NSF-CNH) project. Statistically significant increasing temperatures and decreasing streamflows in the study areas support herder's perceptions of hydro-climatic changes and variability. The results of basin characterization combined with water balance modeling and trend analyses illustrate the future potential for further change in these hydro-climatic systems. Alternate land-uses and herder lifestyle modifications may amplify impacts from climatic change. Recent fieldwork also revealed complex surface-groundwater interactions in some areas that may affect model outcomes. Future explorations of longer-term variability through the use of proxies and the development of hydrologic scenarios will place the current basin analyses in context to more fully assess possible impacts to the hydrologic-human systems of Mongolia.

Projected Impact of Climate Change on Hydrological Regimes in the Philippines

PubMed Central

Kanamaru, Hideki; Keesstra, Saskia; Maroulis, Jerry; David, Carlos Primo C.; Ritsema, Coen J.

2016-01-01

The Philippines is one of the most vulnerable countries in the world to the potential impacts of climate change. To fully understand these potential impacts, especially on future hydrological regimes and water resources (2010-2050), 24 river basins located in the major agricultural provinces throughout the Philippines were assessed. Calibrated using existing historical interpolated climate data, the STREAM model was used to assess future river flows derived from three global climate models (BCM2, CNCM3 and MPEH5) under two plausible scenarios (A1B and A2) and then compared with baseline scenarios (20th century). Results predict a general increase in water availability for most parts of the country. For the A1B scenario, CNCM3 and MPEH5 models predict an overall increase in river flows and river flow variability for most basins, with higher flow magnitudes and flow variability, while an increase in peak flow return periods is predicted for the middle and southern parts of the country during the wet season. However, in the north, the prognosis is for an increase in peak flow return periods for both wet and dry seasons. These findings suggest a general increase in water availability for agriculture, however, there is also the increased threat of flooding and enhanced soil erosion throughout the country. PMID:27749908

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

PubMed

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C

2014-07-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.

A nonparametric stochastic method for generating daily climate-adjusted streamflows

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Moglen, G. E.

2013-10-01

A daily stochastic streamflow generation model is presented, which successfully replicates statistics of the historical streamflow record and can produce climate-adjusted daily time series. A monthly climate model relates general circulation model (GCM)-scale climate indicators to discrete climate-streamflow states, which in turn control parameters in a daily streamflow generation model. Daily flow is generated by a two-state (increasing/decreasing) Markov chain, with rising limb increments randomly sampled from a Weibull distribution and the falling limb modeled as exponential recession. When applied to the Potomac River, a 38,000 km2 basin in the Mid-Atlantic United States, the model reproduces the daily, monthly, and annual distribution and dynamics of the historical streamflow record, including extreme low flows. This method can be used as part of water resources planning, vulnerability, and adaptation studies and offers the advantage of a parsimonious model, requiring only a sufficiently long historical streamflow record and large-scale climate data. Simulation of Potomac streamflows subject to the Special Report on Emissions Scenarios (SRES) A1b, A2, and B1 emission scenarios predict a slight increase in mean annual flows over the next century, with the majority of this increase occurring during the winter and early spring. Conversely, mean summer flows are projected to decrease due to climate change, caused by a shift to shorter, more sporadic rain events. Date of the minimum annual flow is projected to shift 2-5 days earlier by the 2070-2099 period.

Climate consequences of large-scale land-use changes as climate engineering tools

NASA Astrophysics Data System (ADS)

Mayer, Dorothea; Kracher, Daniela; Reick, Christian; Pongratz, Julia

2015-04-01

Terrestrial carbon sinks are much-discussed as climate engineering methods both in politics and science. The debate focuses mostly on their potential for carbon sequestration and fossil-fuel substitution, whereas other effects such as changes in heat and water fluxes are often ignored. We assess potentials and side-effects of two different land-use types suggested as climate engineering tools, forest and herbaceous biomass plantations. We integrate herbaceous biomass plantations as new plant functional types into the land component (JSBACH) of the Max-Planck-Institute Earth System Model (MPI-ESM). Herbaceous biomass plantations alter surface albedo, carbon and water cycles compared to forests. We adapted the JSBACH carbon cycle (assimilation and respiration) to reflect a highly productive biomass grass and the phenology to account for harvests just before the beginning of the growing season. The harvested material is transferred to a separate pool that can be adapted to reflect different biomass utilization pathways. Where possible, the model was validated using yield measurements and water-use efficiency calculations available from literature data. We compare the potentials and side-effects of afforestation and herbaceous biomass plantations in a plausible global scenario: under the representative concentration pathway (RCP) 4.5, large areas of agricultural lands are projected to be abandoned as food production intensifies on the most productive soils. We intend to model the climatic consequences of using these abandoned croplands for afforestation or biomass plantations, under an RCP 8.5 forcing (high CO2 emissions). We emphasize differences between biogeochemical and biogeophysical effects of land-use on climate and how these factors interact on the local and global scale. Apart from direct climatic effects (energy, water, and carbon fluxes), we attempt to consistently account for fossil-fuel substitution effects of biomass plantations in a coupled model. This study comprises the fist part of a larger project analyzing four different land-use types: unmanaged forest, managed forest, woody biomass plantations and herbaceous biomass plantations. Our study is part of the interdisciplinary program 'Climate Engineering: Risks, Challenges and Opportunities?' which allows for a consistent comparison of land-based climate engineering to other methods such as solar radiation management or ocean alkalinization.

12 CFR Appendix A to Part 1010 - Standard and Model Forms and Clauses

Code of Federal Regulations, 2013 CFR

2013-01-01

....114 Subdivision Characteristics and Climate 1010.115 (a) General Topography (b) Water Coverage (c) Drainage and Fill (d) Flood Plain (e) Flooding and Soil Erosion (f) Nuisances (g) Hazards (h) Climate (i... of the land. Changes in plant and animal life, air and water quality and noise levels may affect your...

12 CFR Appendix A to Part 1010 - Standard and Model Forms and Clauses

Code of Federal Regulations, 2012 CFR

2012-01-01

....114 Subdivision Characteristics and Climate 1010.115 (a) General Topography (b) Water Coverage (c) Drainage and Fill (d) Flood Plain (e) Flooding and Soil Erosion (f) Nuisances (g) Hazards (h) Climate (i... of the land. Changes in plant and animal life, air and water quality and noise levels may affect your...

12 CFR Appendix A to Part 1010 - Standard and Model Forms and Clauses

Code of Federal Regulations, 2014 CFR

2014-01-01

....114 Subdivision Characteristics and Climate 1010.115 (a) General Topography (b) Water Coverage (c) Drainage and Fill (d) Flood Plain (e) Flooding and Soil Erosion (f) Nuisances (g) Hazards (h) Climate (i... of the land. Changes in plant and animal life, air and water quality and noise levels may affect your...

Validation and application of a forest gap model to the southern Rocky Mountains

Treesearch

Adrianna C. Foster; Jacquelyn K. Shuman; Herman H. Shugart; Kathleen A. Dwire; Paula J. Fornwalt; Jason Sibold; Jose Negron

2017-01-01

Rocky Mountain forests are highly important for their part in carbon cycling and carbon storage as well as ecosystem services such as water retention and storage and recreational values. These forests are shaped by complex interactions among vegetation, climate, and disturbances. Thus, climate change and shifting disturbances may lead to significant changes in species...

Sources of uncertainty in hydrological climate impact assessment: a cross-scale study

NASA Astrophysics Data System (ADS)

Hattermann, F. F.; Vetter, T.; Breuer, L.; Su, Buda; Daggupati, P.; Donnelly, C.; Fekete, B.; Flörke, F.; Gosling, S. N.; Hoffmann, P.; Liersch, S.; Masaki, Y.; Motovilov, Y.; Müller, C.; Samaniego, L.; Stacke, T.; Wada, Y.; Yang, T.; Krysnaova, V.

2018-01-01

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge—however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

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.

Incorporating water table dynamics in climate modeling: 1. Water table observations and equilibrium water table simulations

NASA Astrophysics Data System (ADS)

Fan, Ying; Miguez-Macho, Gonzalo; Weaver, Christopher P.; Walko, Robert; Robock, Alan

2007-05-01

Soil moisture is a key participant in land-atmosphere interactions and an important determinant of terrestrial climate. In regions where the water table is shallow, soil moisture is coupled to the water table. This paper is the first of a two-part study to quantify this coupling and explore its implications in the context of climate modeling. We examine the observed water table depth in the lower 48 states of the United States in search of salient spatial and temporal features that are relevant to climate dynamics. As a means to interpolate and synthesize the scattered observations, we use a simple two-dimensional groundwater flow model to construct an equilibrium water table as a result of long-term climatic and geologic forcing. Model simulations suggest that the water table depth exhibits spatial organization at watershed, regional, and continental scales, which may have implications for the spatial organization of soil moisture at similar scales. The observations suggest that water table depth varies at diurnal, event, seasonal, and interannual scales, which may have implications for soil moisture memory at these scales.

A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.

Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

NASA Astrophysics Data System (ADS)

Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

2016-02-01

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

Long-run evolution of the global economy - Part 2: Hindcasts of innovation and growth

NASA Astrophysics Data System (ADS)

Garrett, T. J.

2015-10-01

Long-range climate forecasts use integrated assessment models to link the global economy to greenhouse gas emissions. This paper evaluates an alternative economic framework outlined in part 1 of this study (Garrett, 2014) that approaches the global economy using purely physical principles rather than explicitly resolved societal dynamics. If this model is initialized with economic data from the 1950s, it yields hindcasts for how fast global economic production and energy consumption grew between 2000 and 2010 with skill scores > 90 % relative to a model of persistence in trends. The model appears to attain high skill partly because there was a strong impulse of discovery of fossil fuel energy reserves in the mid-twentieth century that helped civilization to grow rapidly as a deterministic physical response. Forecasting the coming century may prove more of a challenge because the effect of the energy impulse appears to have nearly run its course. Nonetheless, an understanding of the external forces that drive civilization may help development of constrained futures for the coupled evolution of civilization and climate during the Anthropocene.

Flood Risk in the Danube basin under climate change

NASA Astrophysics Data System (ADS)

Schröter, Kai; Wortmann, Michel; del Rocio Rivas Lopez, Maria; Liersch, Stefan; Viet Nguyen, Dung; Hardwick, Stephen; Hattermann, Fred

2017-04-01

The projected increase in temperature is expected to intensify the hydrological cycle, and thus more intense precipitation is likely to increase hydro-meteorological extremes and flood hazard. However to assess the future dynamics of hazard and impact induced by these changes it is necessary to consider extreme events and to take a spatially differentiated perspective. The Future Danube Model is a multi-hazard and risk model suite for the Danube region which has been developed in the OASIS project. The model comprises modules for estimating potential perils from heavy precipitation, heat-waves, floods, droughts, and damage risk considering hydro-climatic extremes under current and climate change conditions. Web-based open Geographic Information Systems (GIS) technology allows customers to graphically analyze and overlay perils and other spatial information such as population density or assets exposed. The Future Danube Model combines modules for weather generation, hydrological and hydrodynamic processes, and supports risk assessment and adaptation planning support. This contribution analyses changes in flood hazard in the Danube basin and in flood risk for the German part of the Danube basin. As climate change input, different regionalized climate ensemble runs of the newest IPCC generation are used, the so-called Representative Concentration Pathways (RCPs). They are delivered by the CORDEX initiative (Coordinated Downscaling Experiments). The CORDEX data sample is extended using the statistical weather generator (IMAGE) in order to also consider extreme events. Two time slices are considered: near future 2020-2049 and far future 2050-2079. This data provides the input for the hydrological, hydraulic and flood loss model chain. Results for RCP4.5 and RCP8.5 indicate an increase in intensity and frequency of peak discharges and thus in flood hazard for many parts of the Danube basin.

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.

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

Climate Change Impacts for the Conterminous USA: An Integrated Assessment Part 4. Water Resources

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

Thomson, Allison M.; Brown, Robert A.; Rosenberg, Norman J.

Global warming will impact the hydrologic cycle by increasing the capacity of the atmosphere to hold moisture. Anticipated impacts are generally increased evaporation at low latitudes and increased precipitation at middle and high latitudes. The impacts on specific regions will depend on changes in weather patterns and are certain to be complex. Here we apply a suite of 12 potential climate change scenarios that could occur over the next century as atmospheric CO2 concentrations reach double the pre-industrial level to the Hydrologic Unit Model of the United States (HUMUS) to simulate water supply in the conterminous United States. In Partmore » 4 we examine the sufficiency of this water supply to meet changing demands of irrigated agriculture. General Circulation Models (GCMs) used to simulate climate disagree on whether the US as a whole and its constituent regions will receive more or less precipitation as global warming occurs. The changes in water yield driven by changes in climate will likely be most consequential in the semi-arid western parts of the country where water yield is currently scarce and the resource is intensively managed. Changes of greater than +/-50% with respect to present day water yield are projected in parts of the Midwest and Southwest US. Interannual variability is likely to increase with reduced water yield but decrease with wetter conditions.« less

Shifts in comparative advantages for maize, oat and wheat cropping under climate change in Europe.

PubMed

Elsgaard, L; Børgesen, C D; Olesen, J E; Siebert, S; Ewert, F; Peltonen-Sainio, P; Rötter, R P; Skjelvåg, A O

2012-01-01

Climate change is anticipated to affect European agriculture, including the risk of emerging or re-emerging feed and food hazards. Indirectly, climate change may influence such hazards (e.g. the occurrence of mycotoxins) due to geographic shifts in the distribution of major cereal cropping systems and the consequences this may have for crop rotations. This paper analyses the impact of climate on cropping shares of maize, oat and wheat on a 50-km square grid across Europe (45-65°N) and provides model-based estimates of the changes in cropping shares in response to changes in temperature and precipitation as projected for the time period around 2040 by two regional climate models (RCM) with a moderate and a strong climate change signal, respectively. The projected cropping shares are based on the output from the two RCMs and on algorithms derived for the relation between meteorological data and observed cropping shares of maize, oat and wheat. The observed cropping shares show a south-to-north gradient, where maize had its maximum at 45-55°N, oat had its maximum at 55-65°N, and wheat was more evenly distributed along the latitudes in Europe. Under the projected climate changes, there was a general increase in maize cropping shares, whereas for oat no areas showed distinct increases. For wheat, the projected changes indicated a tendency towards higher cropping shares in the northern parts and lower cropping shares in the southern parts of the study area. The present modelling approach represents a simplification of factors determining the distribution of cereal crops, and also some uncertainties in the data basis were apparent. A promising way of future model improvement could be through a systematic analysis and inclusion of other variables, such as key soil properties and socio-economic conditions, influencing the comparative advantages of specific crops.

Climate change communication through networks and partnerships: A successful model of engaging and educating non-specialist audience in India

NASA Astrophysics Data System (ADS)

Choudhary, S.; Nayak, R.; Gore, A.

2013-12-01

There is an overwhelming international scientific consensus on climate change; however, the global community still lacks the resolve to implement meaningful solutions. No meaningful solutions can be found without educating and engaging non-scientific community in addressing the climate change. With more than 41 percent of world's population falling under 10-34 years age group, the future citizens, inspiring them is a great challenge for the climate scientists. In order to educate the youth and students in India, a model program named 'Climeducate' was created with the help of scientists in Indian Polar Research Network (IPRN), trained climate leaders in ';The Climate Reality Project', and a local organization (Planature Consultancy Services). This model was developed keeping in mind the obstacles that may be faced in reaching out to non-specialist audiences in different parts of India. The identified obstacles were 1- making such a presentation that could reveal the truth about the climate crisis in a way that ignites the moral courage in non-specialist audience 2- lack of funding for travel and boarding expenses of a climate communicator, 3- language barrier in educating local audiences, 4- logistical arrangements at the venue. In this presentation we will share how all the four obstacles were overcome. Audiences were also given short questionnaires before and after the presentation. Remarkable changes in the pattern of answers, data would be shared in the presentation, were observed between the two questionnaires. More importantly, a significant difference in audience engagement was observed comparing a presentation that integrated scientific data with audiovisuals prepared by The Climate Reality Project Chairman, Al Gore (also Former US Vice President) and the other using simple PowerPoint slides. With the success of this program which was implemented among 500 audiences in the eastern India, we aim to replicate this program soon in other parts of India. This presentation will outline how scientific story telling through an effective collaboration of network of scientists, climate mentors, school teachers and local organizations would derive significant results in inspiring, engaging and preparing non-specialists audiences to face the realities of climate change.

Bias-correction of CORDEX-MENA projections using the Distribution Based Scaling method

NASA Astrophysics Data System (ADS)

Bosshard, Thomas; Yang, Wei; Sjökvist, Elin; Arheimer, Berit; Graham, L. Phil

2014-05-01

Within the Regional Initiative for the Assessment of the Impact of Climate Change on Water Resources and Socio-Economic Vulnerability in the Arab Region (RICCAR) lead by UN ESCWA, CORDEX RCM projections for the Middle East Northern Africa (MENA) domain are used to drive hydrological impacts models. Bias-correction of newly available CORDEX-MENA projections is a central part of this project. In this study, the distribution based scaling (DBS) method has been applied to 6 regional climate model projections driven by 2 RCP emission scenarios. The DBS method uses a quantile mapping approach and features a conditional temperature correction dependent on the wet/dry state in the climate model data. The CORDEX-MENA domain is particularly challenging for bias-correction as it spans very diverse climates showing pronounced dry and wet seasons. Results show that the regional climate models simulate too low temperatures and often have a displaced rainfall band compared to WATCH ERA-Interim forcing data in the reference period 1979-2008. DBS is able to correct the temperature biases as well as some aspects of the precipitation biases. Special focus is given to the analysis of the influence of the dry-frequency bias (i.e. climate models simulating too few rain days) on the bias-corrected projections and on the modification of the climate change signal by the DBS method.

Construction of Gridded Daily Weather Data and its Use in Central-European Agroclimatic Study

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Trnka, M.; Skalak, P.

2013-12-01

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).

Assessing the Impacts of Climate Change on Tourism-Dependent Communities in the Great Lakes

NASA Astrophysics Data System (ADS)

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

2013-12-01

Tourism is an essential element of the Laurentian Great Lakes economy as well as one of the sectors expected to be affected most by climate change, particularly through extreme weather events. While studies looking at climate change impacts on the Great Lakes tourism, specifically, are limited, the results of other studies suggest that both summer tourism activities, such as beach-going, and winter tourism activities, such as skiing and snowboarding, could feel the effects of a changing climate. The purpose of this study was to determine how existing data and models might be used to predict the potential impacts of climate change on tourism-dependent communities at the local scale. Future climate projections and variable infiltration capacity (VIC) model simulations based on historical climate data were used to quantify trends in environmental metrics with a potential influence on tourism for several tourism-dependent Great Lakes communities. The results of this research show that the potential impacts of climate change vary at the local scale and could require different adaptation strategies for different communities and for different sectors of the tourism industry. For example, communities in the northern parts of the Great Lakes may find benefit in a greater diversification of their tourism industries, given that warming temperatures could be beneficial for summer tourism activities, while communities in the southern parts of the Great Lakes may have to find other ways to cope with climate conditions that are less conducive to summer tourism activities. Stakeholder input could also help inform the process of producing scientific information that is useful to policymakers when it comes to tourism sector-related decision making.

Climate Modeling and Causal Identification for Sea Ice Predictability

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

Diagnosing GCM errors over West Africa using relaxation experiments. Part II: intraseasonal variability and African easterly waves

NASA Astrophysics Data System (ADS)

Pohl, Benjamin; Douville, Hervé

2011-10-01

A near-global grid-point nudging of the Arpege-Climat atmospheric General Circulation Model towards ECMWF reanalyses is used to diagnose the regional versus remote origin of the summer model biases and variability over West Africa. First part of this study revealed a limited impact on the monsoon climatology compared to a control experiment without nudging, but a significant improvement of interannual variability, although the amplitude of the seasonal anomalies remained underestimated. Focus is given here on intraseasonal variability of monsoon rainfall and dynamics. The reproducible part of these signals is investigated through 30-member ensemble experiments computed for the 1994 rainy season, a year abnormally wet over the Sahel but representative of the model systematic biases. In the control experiment, Arpege-Climat simulates too few rainy days that are associated with too low rainfall amounts over the central and western Sahel, in line with the seasonal dry biases. Nudging the model outside Africa tends to slightly increase the number of rainy days over the Sahel, but has little effect on associated rainfall amounts. However, results do indicate that a significant part of the monsoon intraseasonal variability simulated by Arpege-Climat is controlled by lateral boundary conditions. Parts of the wet/dry spells over the Sahel occur in phase in the 30 members of the nudging experiment, and are therefore embedded in larger-scale variability patterns. Inter-member spread is however not constant across the selected summer season. It is partly controlled by African Easterly Waves, which show dissimilar amplitude from one member to another, but a coherent phasing in all members. A lowpass filtering of the nudging fields suggests that low frequency variations in the lateral boundary conditions can lead to eastward extensions of the African Easterly Jet, creating a favorable environment for easterly waves, while high frequency perturbations seem to control their phasing.

Eutrophication status of the North Sea, Skagerrak, Kattegat and the Baltic Sea in present and future climates: A model study

NASA Astrophysics Data System (ADS)

Skogen, Morten D.; Eilola, Kari; Hansen, Jørgen L. S.; Meier, H. E. Markus; Molchanov, Mikhail S.; Ryabchenko, Vladimir A.

2014-04-01

A method to combine observations and an ensemble of ecological models has been used to assess eutrophication. Using downscaled forcing from two GCMs under the A1B emission scenario, an assessment of the eutrophication status was made for a control (1970-2000) and a future climate (2070-2100) period. By using validation results from a hindcast to compute individual weights between the models, an assessment of eutrophication is done using a set of threshold values. The final classification distinguishes between three categories: problem area, potential problem area, and non-problem area, in accordance with current management practice as suggested by the Oslo and Paris Commissions (OSPAR) and the Helsinki Commission (HELCOM). For the control run the assessment indicates that the Kattegat, the Danish Straits, the Gulf of Finland, the Gotland Basin as well as main parts of the Arkona Basin, the Bornholm Basin, and the Baltic proper may be classified as problem areas. The main part of the North Sea and also the Skagerrak are non-problem areas while the main parts of the Gulf of Bothnia, Gulf of Riga and the entire southeastern continental coast of the North Sea may be classified as potential problem areas. In the future climate scenarios most of the previous potential problem areas in the Baltic Sea have become problem areas, except for the Bothnian Bay where the situation remain fairly unchanged. In the North Sea there seems to be no obvious changes in eutrophication status in the projected future climate.

Climate model simulations of the mid-Pliocene: Earth's last great interval of global warmth

USGS Publications Warehouse

Dolan, A.M.; Haywood, A.M.; Dowsett, H.J.

2012-01-01

Pliocene Model Intercomparison Project Workshop; Reston, Virginia, 2–4 August 2011 The Pliocene Model Intercomparison Project (PlioMIP), supported by the U.S. Geological Survey's (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) project and Powell Center, is an integral part of a third iteration of the Paleoclimate Modelling Intercomparison Project (PMIP3). PlioMIP's aim is to systematically compare structurally different climate models. This is done in the context of the mid-Pliocene (~3.3–3.0 million years ago), a geological interval when the global annual mean temperature was similar to predictions for the next century.

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.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

A modelling approach to assessing the timescale uncertainties in proxy series with chronological errors

NASA Astrophysics Data System (ADS)

Divine, D.; Godtliebsen, F.; Rue, H.

2012-04-01

Detailed knowledge of past climate variations is of high importance for gaining a better insight into the possible future climate scenarios. The relative shortness of available high quality instrumental climate data conditions the use of various climate proxy archives in making inference about past climate evolution. It, however, requires an accurate assessment of timescale errors in proxy-based paleoclimatic reconstructions. We here propose an approach to assessment of timescale errors in proxy-based series with chronological uncertainties. The method relies on approximation of the physical process(es) forming a proxy archive by a random Gamma process. Parameters of the process are partly data-driven and partly determined from prior assumptions. For a particular case of a linear accumulation model and absolutely dated tie points an analytical solution is found suggesting the Beta-distributed probability density on age estimates along the length of a proxy archive. In a general situation of uncertainties in the ages of the tie points the proposed method employs MCMC simulations of age-depth profiles yielding empirical confidence intervals on the constructed piecewise linear best guess timescale. It is suggested that the approach can be further extended to a more general case of a time-varying expected accumulation between the tie points. The approach is illustrated by using two ice and two lake/marine sediment cores representing the typical examples of paleoproxy archives with age models constructed using tie points of mixed origin.

Impact of the climate change to shallow groundwater in Baltic artesian basin

NASA Astrophysics Data System (ADS)

Lauva, D.; Bethers, P.; Timuhins, A.; Sennikovs, J.

2012-04-01

The purpose of our work was to find the long term pattern of annual shallow ground water changes in region of Latvia, ground water level modelling for the contemporary climate and future climate scenarios and the model generalization to the Baltic artesian basin (BAB) region. Latvia is located in the middle part of BAB. It occupies about 65'000 square kilometers. BAB territory (480'000 square kilometres) also includes Lithuania, Estonia as well as parts of Poland, Russia, Belarus and the Baltic Sea. Territory of BAB is more than seven times bigger than Latvia. Precipitation and spring snow melt are the main sources of the ground water recharge in BAB territory. The long term pattern of annual shallow ground water changes was extracted from the data of 25 monitoring wells in the territory of Latvia. The main Latvian groundwater level fluctuation regime can be described as a function with two maximums (in spring and late autumn) and two minimums (in winter and late summer). The mathematical model METUL (developed by Latvian University of Agriculture) was chosen for the ground water modelling. It was calibrated on the observations in 25 gauging wells around Latvia. After the calibration we made calculations using data provided by an ensemble of regional climate models, yielding a continuous groundwater table time-series from 1961 to 2100, which were analysed and split into 3 time windows for further analysis: contemporary climate (1961-1990), near future (2021-2050) and far future (2071-2100). The daily average temperature, precipitation and humidity time series were used as METUL forcing parameters. The statistical downscaling method (Sennikovs and Bethers, 2009) was applied for the bias correction of RCM calculated and measured variables. The qualitative differences in future and contemporary annual groundwater regime are expected. The future Latvian annual groundwater cycle according to the RCM climate projection changes to curve with one peak and one drought point. Acknowledgements. This research was supported by the European Social Fund project "Establishment of interdisciplinary scientist group and modelling system for groundwater research" (Project Nr. 2009/0212/1DP/1.1.1.2.0/09/APIA/VIAA/060). Regional climate model data was provided through the ENSEMBLES data archive, funded by the EU FP6 Integrated Project ENSEMBLES (Contract number 505539). Reference: Sennikovs, J., Bethers, U. 2009. Statistical downscaling method of regional climate model results for hydrological modelling. In: Proceedings of 18th World IMACS / MODSIM Congress.

Weakening of tropical Pacific atmospheric circulation due to anthropogenic forcing

NASA Astrophysics Data System (ADS)

Vecchi, Gabriel A.; Soden, Brian J.; Wittenberg, Andrew T.; Held, Isaac M.; Leetmaa, Ants; Harrison, Matthew J.

2006-05-01

Since the mid-nineteenth century the Earth's surface has warmed, and models indicate that human activities have caused part of the warming by altering the radiative balance of the atmosphere. Simple theories suggest that global warming will reduce the strength of the mean tropical atmospheric circulation. An important aspect of this tropical circulation is a large-scale zonal (east-west) overturning of air across the equatorial Pacific Ocean-driven by convection to the west and subsidence to the east-known as the Walker circulation. Here we explore changes in tropical Pacific circulation since the mid-nineteenth century using observations and a suite of global climate model experiments. Observed Indo-Pacific sea level pressure reveals a weakening of the Walker circulation. The size of this trend is consistent with theoretical predictions, is accurately reproduced by climate model simulations and, within the climate models, is largely due to anthropogenic forcing. The climate model indicates that the weakened surface winds have altered the thermal structure and circulation of the tropical Pacific Ocean. These results support model projections of further weakening of tropical atmospheric circulation during the twenty-first century.

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

NASA Astrophysics Data System (ADS)

Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

2017-04-01

Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

NASA Astrophysics Data System (ADS)

Pankatz, Klaus; Kerkweg, Astrid

2015-04-01

The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations. Theoretically, regional down-scaling should act like a magnifying glass. It should reveal details on small scales which a global model cannot resolve, but it should not affect the large scale flow. As the development of the small scale features takes some time, it is important that the air stays long enough within the regional domain. The spin-up time of the small scale features is, of course, dependent on the resolution of the LBC and the resolution of the RCM. The second study examines the quality of decadal hind-casts over Europe of the decade 2001-2010 when the horizontal resolution of the driving model, namely 2.8°, 1.8°, 1.4°, 1.1°, from which the LBC are calculated, is altered. The study shows, that a smaller resolution gap between LBC resolution and RCM resolution might be beneficial.

The effects of global climate change on Southeast Asia: A survey of likely impacts and problems of adaptation

NASA Technical Reports Server (NTRS)

Njoto, Sukrisno; Howe, Charles W.

1991-01-01

Study results indicate the likelihood of significant net damages from climate change, in particular damages from sea-level rise and higher temperatures that seem unlikely to be offset by favorable shifts in precipitation and carbon dioxide. Also indicated was the importance of better climate models, in particular models that can calculate climate change on a regional scale appropriate to policy-making. In spite of this potential for damage, there seems to be a low level of awareness and concern, probably caused by the higher priority given to economic growth and reinforced by the great uncertainty in the forecasts. The common property nature of global environment systems also leads to a feeling of helplessness on the part of country governments.

Building Quantitative Hydrologic Storylines from Process-based Models for Managing Water Resources in the U.S. Under Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, J.; Gutmann, E. D.; Clark, M. P.; Nijssen, B.; Vano, J. A.; Addor, N.; Wood, A.; Newman, A. J.; Mizukami, N.; Brekke, L. D.; Rasmussen, R.; Mendoza, P. A.

2016-12-01

Climate change narratives for water-resource applications must represent the change signals contextualized by hydroclimatic process variability and uncertainty at multiple scales. Building narratives of plausible change includes assessing uncertainties across GCM structure, internal climate variability, climate downscaling methods, and hydrologic models. Work with this linked modeling chain has dealt mostly with GCM sampling directed separately to either model fidelity (does the model correctly reproduce the physical processes in the world?) or sensitivity (of different model responses to CO2 forcings) or diversity (of model type, structure, and complexity). This leaves unaddressed any interactions among those measures and with other components in the modeling chain used to identify water-resource vulnerabilities to specific climate threats. However, time-sensitive, real-world vulnerability studies typically cannot accommodate a full uncertainty ensemble across the whole modeling chain, so a gap has opened between current scientific knowledge and most routine applications for climate-changed hydrology. To close that gap, the US Army Corps of Engineers, the Bureau of Reclamation, and the National Center for Atmospheric Research are working on techniques to subsample uncertainties objectively across modeling chain components and to integrate results into quantitative hydrologic storylines of climate-changed futures. Importantly, these quantitative storylines are not drawn from a small sample of models or components. Rather, they stem from the more comprehensive characterization of the full uncertainty space for each component. Equally important from the perspective of water-resource practitioners, these quantitative hydrologic storylines are anchored in actual design and operations decisions potentially affected by climate change. This talk will describe part of our work characterizing variability and uncertainty across modeling chain components and their interactions using newly developed observational data, models and model outputs, and post-processing tools for making the resulting quantitative storylines most useful in practical hydrology applications.

The projected demise of Barnes Ice Cap: Evidence of an unusually warm 21st century Arctic

NASA Astrophysics Data System (ADS)

Gilbert, A.; Flowers, G. E.; Miller, G. H.; Refsnider, K. A.; Young, N. E.; Radić, V.

2017-03-01

As a remnant of the Laurentide Ice Sheet, Barnes Ice Cap owes its existence and present form in part to the climate of the last glacial period. The ice cap has been sustained in the present interglacial climate by its own topography through the mass balance-elevation feedback. A coupled mass balance and ice-flow model, forced by Coupled Model Intercomparison Project Phase 5 climate model output, projects that the current ice cap will likely disappear in the next 300 years. For greenhouse gas Representative Concentration Pathways of +2.6 to +8.5 Wm-2, the projected ice-cap survival times range from 150 to 530 years. Measured concentrations of cosmogenic radionuclides 10Be, 26Al, and 14C at sites exposed near the ice-cap margin suggest the pending disappearance of Barnes Ice Cap is very unusual in the last million years. The data and models together point to an exceptionally warm 21st century Arctic climate.

Combining climatic and soil properties better predicts covers of Brazilian biomes.

PubMed

Arruda, Daniel M; Fernandes-Filho, Elpídio I; Solar, Ricardo R C; Schaefer, Carlos E G R

2017-04-01

Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km 2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.

Combining climatic and soil properties better predicts covers of Brazilian biomes

NASA Astrophysics Data System (ADS)

Arruda, Daniel M.; Fernandes-Filho, Elpídio I.; Solar, Ricardo R. C.; Schaefer, Carlos E. G. R.

2017-04-01

Several techniques have been used to model the area covered by biomes or species. However, most models allow little freedom of choice of response variables and are conditioned to the use of climate predictors. This major restriction of the models has generated distributions of low accuracy or inconsistent with the actual cover. Our objective was to characterize the environmental space of the most representative biomes of Brazil and predict their cover, using climate and soil-related predictors. As sample units, we used 500 cells of 100 km2 for ten biomes, derived from the official vegetation map of Brazil (IBGE 2004). With a total of 38 (climatic and soil-related) predictors, an a priori model was run with the random forest classifier. Each biome was calibrated with 75% of the samples. The final model was based on four climate and six soil-related predictors, the most important variables for the a priori model, without collinearity. The model reached a kappa value of 0.82, generating a highly consistent prediction with the actual cover of the country. We showed here that the richness of biomes should not be underestimated, and that in spite of the complex relationship, highly accurate modeling based on climatic and soil-related predictors is possible. These predictors are complementary, for covering different parts of the multidimensional niche. Thus, a single biome can cover a wide range of climatic space, versus a narrow range of soil types, so that its prediction is best adjusted by soil-related variables, or vice versa.

Effects of climate variability on global scale flood risk

NASA Astrophysics Data System (ADS)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change research. We carried out the research by simulating daily river discharge using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series. From this, we derived peak annual flood volumes for large-scale river basins globally. These were used to force a global inundation model (dynRout) to map inundation extent and depth for return periods between 2 and 1000 years, under El Niño conditions, neutral conditions, and La Niña conditions. Theses flood hazard maps were combined with global datasets on socioeconomic variables such as population and income to represent the socioeconomic exposure to flooding, and depth-damage curves to represent vulnerability.

Solar influence on climate during the past millennium: Results from transient simulations with the NCAR Climate System Model

PubMed Central

Ammann, Caspar M.; Joos, Fortunat; Schimel, David S.; Otto-Bliesner, Bette L.; Tomas, Robert A.

2007-01-01

The potential role of solar variations in modulating recent climate has been debated for many decades and recent papers suggest that solar forcing may be less than previously believed. Because solar variability before the satellite period must be scaled from proxy data, large uncertainty exists about phase and magnitude of the forcing. We used a coupled climate system model to determine whether proxy-based irradiance series are capable of inducing climatic variations that resemble variations found in climate reconstructions, and if part of the previously estimated large range of past solar irradiance changes could be excluded. Transient simulations, covering the published range of solar irradiance estimates, were integrated from 850 AD to the present. Solar forcing as well as volcanic and anthropogenic forcing are detectable in the model results despite internal variability. The resulting climates are generally consistent with temperature reconstructions. Smaller, rather than larger, long-term trends in solar irradiance appear more plausible and produced modeled climates in better agreement with the range of Northern Hemisphere temperature proxy records both with respect to phase and magnitude. Despite the direct response of the model to solar forcing, even large solar irradiance change combined with realistic volcanic forcing over past centuries could not explain the late 20th century warming without inclusion of greenhouse gas forcing. Although solar and volcanic effects appear to dominate most of the slow climate variations within the past thousand years, the impacts of greenhouse gases have dominated since the second half of the last century. PMID:17360418

Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.

Reliability of the North America CORDEX and NARCCAP simulations in the context of uncertainty in regional climate change projections

NASA Astrophysics Data System (ADS)

Karmalkar, A.

2017-12-01

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.

Preparing Middle School Teachers to Use Science Models Effectively when Teaching about Weather and Climate Topics

NASA Astrophysics Data System (ADS)

Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.

2012-12-01

According to the National Science Education Standards (NSES), teachers are encouraged to use science models in the classroom as a way to aid in the understanding of the nature of the scientific process. This is of particular importance to the atmospheric science community because climate and weather models are very important when it comes to understanding current and future behaviors of our atmosphere. Although familiar with weather forecasts on television and the Internet, most people do not understand the process of using computer models to generate weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Therefore, it makes sense that recent research in science education indicates that scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. The purpose of this research study is to describe how three middle school teachers use science models to teach about topics in climate and weather, as well as the challenges they face incorporating models effectively into the classroom. Participants in this study took part in a week long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The course design was based on empirically tested features of effective professional development for science teachers and was aimed at teaching content to the teachers while simultaneously orienting them towards effective use of science models in the classroom in a way that both aids in learning about the content knowledge as well as how models are used in scientific inquiry. Results indicate that teachers perceive models to be physical representations that can be used as evidence to convince students that the teacher's conception of the concept is correct. Additionally, teachers tended to use them as ways to explain an idea to their students; they rarely discussed the idea that models are a representation of reality (as opposed to a replication of reality) and never discussed the predictive power of models and how they are used to further scientific knowledge. The results indicate that these teachers do not have a complete understanding of science models and the role they play in the scientific process. Therefore, the teachers struggled to incorporate modeling into the classroom in a way that aligns with what the NSES suggests. They tended to lean on models as "proof" of a particular concept rather than a representation of a concept. In actuality, scientists do not just use models to explain a concept, they also use them to make projections and as a way to improve our understanding the atmosphere. A possible consequence of teachers using models as "proof" of a concept is that students expect climate and forecast models to be concrete and exact, rather than tentative and representative. Increasing student understanding of climate and weather models is important to meet the needs of future STEM professionals, decision-makers, and the general populace to support rational decision-making about weather and the future of climate by an educated society.

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 - Part 2: Antarctica (1979-2016)

NASA Astrophysics Data System (ADS)

Melchior van Wessem, Jan; van de Berg, Willem Jan; Noël, Brice P. Y.; van Meijgaard, Erik; Amory, Charles; Birnbaum, Gerit; Jakobs, Constantijn L.; Krüger, Konstantin; Lenaerts, Jan T. M.; Lhermitte, Stef; Ligtenberg, Stefan R. M.; Medley, Brooke; Reijmer, Carleen H.; van Tricht, Kristof; Trusel, Luke D.; van Ulft, Lambertus H.; Wouters, Bert; Wuite, Jan; van den Broeke, Michiel R.

2018-04-01

We evaluate modelled Antarctic ice sheet (AIS) near-surface climate, surface mass balance (SMB) and surface energy balance (SEB) from the updated polar version of the regional atmospheric climate model, RACMO2 (1979-2016). The updated model, referred to as RACMO2.3p2, incorporates upper-air relaxation, a revised topography, tuned parameters in the cloud scheme to generate more precipitation towards the AIS interior and modified snow properties reducing drifting snow sublimation and increasing surface snowmelt. Comparisons of RACMO2 model output with several independent observational data show that the existing biases in AIS temperature, radiative fluxes and SMB components are further reduced with respect to the previous model version. The model-integrated annual average SMB for the ice sheet including ice shelves (minus the Antarctic Peninsula, AP) now amounts to 2229 Gt y-1, with an interannual variability of 109 Gt y-1. The largest improvement is found in modelled surface snowmelt, which now compares well with satellite and weather station observations. For the high-resolution ( ˜ 5.5 km) AP simulation, results remain comparable to earlier studies. The updated model provides a new, high-resolution data set of the contemporary near-surface climate and SMB of the AIS; this model version will be used for future climate scenario projections in a forthcoming study.

Future changes in summer mean and extreme precipitation frequency in Japan by d4PDF regional climate simulations

NASA Astrophysics Data System (ADS)

Okada, Y.; Ishii, M.; Endo, H.; Kawase, H.; Sasaki, H.; Takayabu, I.; Watanabe, S.; Fujita, M.; Sugimoto, S.; Kawazoe, S.

2017-12-01

Precipitation in summer plays a vital role in sustaining life across East Asia, but the heavy rain that is often generated during this period can also cause serious damage. Developing a better understanding of the features and occurrence frequency of this heavy rain is an important element of disaster prevention. We investigated future changes in summer mean and extreme precipitation frequency in Japan using large ensemble dataset which simulated by the Non-Hydrostatic Regional Climate Model with a horizontal resolution of 20km (NHRCM20). This dataset called database for Policy Decision making for Future climate changes (d4PDF), which is intended to be utilized for the impact assessment studies and adaptation planning to global warming. The future climate experiments assume the global mean surface air temperature rise 2K and 4K from the pre-industrial period. We investigated using this dataset future changes of precipitation in summer over the Japanese archipelago based on observational locations. For mean precipitation in the present-day climate, the bias of the rainfall for each month is within 25% even considering all members (30 members). The bias at each location is found to increase by over 50% on the Pacific Ocean side of eastern part of Japan and interior locations of western part of Japan. The result in western part of Japan depends on the effect of the elevations in this model. The future changes in mean precipitation show a contrast between northern and southern Japan, with the north showing a slight increase but the south a decrease. The future changes in the frequency of extreme precipitation in the national average of Japan increase at 2K and 4K simulations compared with the present-day climate, respectively. The authors were supported by the Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Simulating Heinrich events in a coupled atmosphere-ocean-ice sheet model

NASA Astrophysics Data System (ADS)

Mikolajewicz, Uwe; Ziemen, Florian

2016-04-01

Heinrich events are among the most prominent events of long-term climate variability recorded in proxies across the northern hemisphere. They are the archetype of ice sheet - climate interactions on millennial time scales. Nevertheless, the exact mechanisms that cause Heinrich events are still under discussion, and their climatic consequences are far from being fully understood. We contribute to answering the open questions by studying Heinrich events in a coupled ice sheet model (ISM) atmosphere-ocean-vegetation general circulation model (AOVGCM) framework, where this variability occurs as part of the model generated internal variability without the need to prescribe external perturbations, as was the standard approach in almost all model studies so far. The setup consists of a northern hemisphere setup of the modified Parallel Ice Sheet Model (mPISM) coupled to the global coarse resolution AOVGCM ECHAM5/MPIOM/LPJ. The simulations used for this analysis were an ensemble covering substantial parts of the late Glacial forced with transient insolation and prescribed atmospheric greenhouse gas concentrations. The modeled Heinrich events show a marked influence of the ice discharge on the Atlantic circulation and heat transport, but none of the Heinrich events during the Glacial did show a complete collapse of the North Atlantic meridional overturning circulation. The simulated main consequences of the Heinrich events are a freshening and cooling over the North Atlantic and a drying over northern Europe.

Comparison and interactions between the long-term pursuit of energy independence and climate policies

NASA Astrophysics Data System (ADS)

Jewell, Jessica; Vinichenko, Vadim; McCollum, David; Bauer, Nico; Riahi, Keywan; Aboumahboub, Tino; Fricko, Oliver; Harmsen, Mathijs; Kober, Tom; Krey, Volker; Marangoni, Giacomo; Tavoni, Massimo; van Vuuren, Detlef P.; van der Zwaan, Bob; Cherp, Aleh

2016-06-01

Ensuring energy security and mitigating climate change are key energy policy priorities. The recent Intergovernmental Panel on Climate Change Working Group III report emphasized that climate policies can deliver energy security as a co-benefit, in large part through reducing energy imports. Using five state-of-the-art global energy-economy models and eight long-term scenarios, we show that although deep cuts in greenhouse gas emissions would reduce energy imports, the reverse is not true: ambitious policies constraining energy imports would have an insignificant impact on climate change. Restricting imports of all fuels would lower twenty-first-century emissions by only 2-15% against the Baseline scenario as compared with a 70% reduction in a 450 stabilization scenario. Restricting only oil imports would have virtually no impact on emissions. The modelled energy independence targets could be achieved at policy costs comparable to those of existing climate pledges but a fraction of the cost of limiting global warming to 2 ∘C.

An Overview of the Future Development of Climate and Earth System Models for Scientific and Policy Use (Invited)

NASA Astrophysics Data System (ADS)

Washington, W. M.

2010-12-01

The development of climate and earth system models has been regarded primarily as the making of scientific tools to study the complex nature of the Earth’s climate. These models have a long history starting with very simple physical models based on fundamental physics in the 1960s and over time they have become much more complex with atmospheric, ocean, sea ice, land/vegetation, biogeochemical, glacial and ecological components. The policy use aspects of these models did not start in the 1960s and 1970s as decision making tools but were used to answer fundamental scientific questions such as what happens when the atmospheric carbon dioxide concentration increases or is doubled. They gave insights into the various interactions and were extensively compared with observations. It was realized that models of the earlier time periods could only give first order answers to many of the fundamental policy questions. As societal concerns about climate change rose, the policy questions of anthropogenic climate change became better defined; they were mostly concerned with the climate impacts of increasing greenhouse gases, aerosols, and land cover change. In the late 1980s, the United Nations set up the Intergovernmental Panel on Climate Change to perform assessments of the published literature. Thus, the development of climate and Earth system models became intimately linked to the need to not only improve our scientific understanding but also answering fundamental policy questions. In order to meet this challenge, the models became more complex and realistic so that they could address these policy oriented science questions such as rising sea level. The presentation will discuss the past and future development of global climate and earth system models for science and policy purposes. Also to be discussed is their interactions with economic integrated assessment models, regional and specialized models such as river transport or ecological components. As an example of one development pathway, the NSF/Department of Energy supported Community Climate System and Earth System Models will be featured in the presentation. Computational challenges will also part of the discussion.

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

Chen, Gang

Mid-latitude extreme weather events are responsible for a large part of climate-related damage. Yet large uncertainties remain in climate model projections of heat waves, droughts, and heavy rain/snow events on regional scales, limiting our ability to effectively use these projections for climate adaptation and mitigation. These uncertainties can be attributed to both the lack of spatial resolution in the models, and to the lack of a dynamical understanding of these extremes. The approach of this project is to relate the fine-scale features to the large scales in current climate simulations, seasonal re-forecasts, and climate change projections in a very widemore » range of models, including the atmospheric and coupled models of ECMWF over a range of horizontal resolutions (125 to 10 km), aqua-planet configuration of the Model for Prediction Across Scales and High Order Method Modeling Environments (resolutions ranging from 240 km – 7.5 km) with various physics suites, and selected CMIP5 model simulations. The large scale circulation will be quantified both on the basis of the well tested preferred circulation regime approach, and very recently developed measures, the finite amplitude Wave Activity (FAWA) and its spectrum. The fine scale structures related to extremes will be diagnosed following the latest approaches in the literature. The goal is to use the large scale measures as indicators of the probability of occurrence of the finer scale structures, and hence extreme events. These indicators will then be applied to the CMIP5 models and time-slice projections of a future climate.« less

Is carbon storage enough? Can plants adapt? New questions in climate change research.

Treesearch

Sally Duncan

2002-01-01

As it becomes increasingly apparent that human activities are partly responsible for global warming, the focus of climate change research is shifting from the churning out of assessments to the pursuit of science that can test the robustness of existing models. The questions now being addressed are becoming more challenging: Can water-use efficiency of plants keep up...

Assessing the Role of Climate Variability on Liver Fluke Risk in the UK Through Mechanistic Hydro-Epidemiological Modelling

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2016-12-01

Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

Life history trade-off moderates model predictions of diversity loss from climate change.

PubMed

Moor, Helen

2017-01-01

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.

Use of North American and European Air Quality Networks to Evaluate Global Chemistry-Climate Modeling of Surface Ozone

NASA Technical Reports Server (NTRS)

Schnell, J. L.; Prather, M. J.; Josse, B.; Naik, V.; Horowitz, L. W.; Cameron-Smith, P.; Bergmann, D.; Zeng, G.; Plummer, D. A.; Sudo, K.;

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.; Mlawer, Eli J.; Sokolik, Irina N.; Clough, Shepard A.; Toon, Owen B.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications, we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Improvement and Application of Atmospheric Radiative Transfer Models for Prediction of the Climatic Effects of Aerosol

NASA Technical Reports Server (NTRS)

Bergstrom, Robert W.

1998-01-01

This paper presents a radiative transfer model that has been developed to accurately predict the atmospheric radiant flux in both the infrared and the solar spectrum with a minimum of computational effort. The model is designed to be included in numerical climate models. To assess the accuracy of the model, the results are compared to other more detailed models for several standard cases in the solar and thermal spectrum. As the thermal spectrum has been treated in other publications we focus here on the solar part of the spectrum. We perform several example calculations focussing on the question of absorption of solar radiation by gases and aerosols.

Constraints and potentials of future irrigation water availability on agricultural production under climate change

PubMed Central

Elliott, Joshua; Deryng, Delphine; Müller, Christoph; Frieler, Katja; Konzmann, Markus; Gerten, Dieter; Glotter, Michael; Flörke, Martina; Wada, Yoshihide; Best, Neil; Eisner, Stephanie; Fekete, Balázs M.; Folberth, Christian; Foster, Ian; Gosling, Simon N.; Haddeland, Ingjerd; Khabarov, Nikolay; Ludwig, Fulco; Masaki, Yoshimitsu; Olin, Stefan; Rosenzweig, Cynthia; Ruane, Alex C.; Satoh, Yusuke; Schmid, Erwin; Stacke, Tobias; Tang, Qiuhong; Wisser, Dominik

2014-01-01

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. PMID:24344283

Arctic climate tipping points.

PubMed

Lenton, Timothy M

2012-02-01

There is widespread concern that anthropogenic global warming will trigger Arctic climate tipping points. The Arctic has a long history of natural, abrupt climate changes, which together with current observations and model projections, can help us to identify which parts of the Arctic climate system might pass future tipping points. Here the climate tipping points are defined, noting that not all of them involve bifurcations leading to irreversible change. Past abrupt climate changes in the Arctic are briefly reviewed. Then, the current behaviour of a range of Arctic systems is summarised. Looking ahead, a range of potential tipping phenomena are described. This leads to a revised and expanded list of potential Arctic climate tipping elements, whose likelihood is assessed, in terms of how much warming will be required to tip them. Finally, the available responses are considered, especially the prospects for avoiding Arctic climate tipping points.

Understanding the drivers of the future water gap in the Indus-Ganges-Brahmaputra basins

NASA Astrophysics Data System (ADS)

Immerzeel, W. W.; Wijngaard, R. R.; Biemans, H.; Lutz, A. F.

2017-12-01

The Indus, Ganges, and Brahmaputra (IGB) river systems provide water resources for the agricultural, domestic and industrial sectors sustaining the lives of about 700 million people. The region is globally a hotspot for climate change as the headwaters of these rivers are fed by melt water from snow and glaciers, both strongly influenced by temperature change. In addition, the hydrology in the region is determined by the monsoon and its future dynamics as a results of climate change remains very uncertain. Simultaneously, the population is projected to grow rapidly over the coming decades, which in combination with strong economic developments, will likely result in a rapid increase in water demand. In this study we attempt to quantify the future water gap in the IGB and attribute this water gap to climate change and socio-economic growth. For the upstream mountainous parts of the basins we use the SPHY model, which is calibrated based on historical streamflow and glacier mass balance data and forced by the latest CMIP5 future climate model data for RCP4.5 and 8.5. Output of this model feeds into the downstream LPJmL model, which allows assessment of downstream climate change impacts and projected changes in water demand as a result of socio-economic developments. The LPJmL model is run for different combinations of RCPs and Shared Socio Economic Pathways (SSPs). Our results show that for the IGB as a whole climate change will increase water availability in the coming decades, due to an overall, albeit uncertain, increase in monsoon precipitation in combination with a sustained melt water supply from the upstream parts of the basins. However, irrespective of the SSP and RCP, the water demand as a result of socio-economic growth is expected to increase extremely fast in the near future and this is likely to be the main adaptation challenge for the IGB as far as water shortages are concerned. Our results also show that regional and temporal variation in the water gap is large and that basin specific adaptation measures are required that take into account both socio-economic developments as well as climate change.

Projected changes in climate extremes over Qatar and the Arabian Gulf region

NASA Astrophysics Data System (ADS)

Kundeti, K.; Kanikicharla, K. K.; Al sulaiti, M.; Khulaifi, M.; Alboinin, N.; Kito, A.

2015-12-01

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.

Multi-decadal trend and space-time variability of sea level over the Indian Ocean since the 1950s: impact of decadal climate modes

NASA Astrophysics Data System (ADS)

Han, W.; Stammer, D.; Meehl, G. A.; Hu, A.; Sienz, F.

2016-12-01

Sea level varies on decadal and multi-decadal timescales over the Indian Ocean. The variations are not spatially uniform, and can deviate considerably from the global mean sea level rise (SLR) due to various geophysical processes. One of these processes is the change of ocean circulation, which can be partly attributed to natural internal modes of climate variability. Over the Indian Ocean, the most influential climate modes on decadal and multi-decadal timescales are the Interdecadal Pacific Oscillation (IPO) and decadal variability of the Indian Ocean dipole (IOD). Here, we first analyze observational datasets to investigate the impacts of IPO and IOD on spatial patterns of decadal and interdecadal (hereafter decal) sea level variability & multi-decadal trend over the Indian Ocean since the 1950s, using a new statistical approach of Bayesian Dynamical Linear regression Model (DLM). The Bayesian DLM overcomes the limitation of "time-constant (static)" regression coefficients in conventional multiple linear regression model, by allowing the coefficients to vary with time and therefore measuring "time-evolving (dynamical)" relationship between climate modes and sea level. For the multi-decadal sea level trend since the 1950s, our results show that climate modes and non-climate modes (the part that cannot be explained by climate modes) have comparable contributions in magnitudes but with different spatial patterns, with each dominating different regions of the Indian Ocean. For decadal variability, climate modes are the major contributors for sea level variations over most region of the tropical Indian Ocean. The relative importance of IPO and decadal variability of IOD, however, varies spatially. For example, while IOD decadal variability dominates IPO in the eastern equatorial basin (85E-100E, 5S-5N), IPO dominates IOD in causing sea level variations in the tropical southwest Indian Ocean (45E-65E, 12S-2S). To help decipher the possible contribution of external forcing to the multi-decadal sea level trend and decadal variability, we also analyze the model outputs from NCAR's Community Earth System Model (CESM) Large Ensemble Experiments, and compare the results with our observational analyses.

Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

NASA Astrophysics Data System (ADS)

Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.

2009-04-01

The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional investigations in this region of the planet. Reported is an overview of some risk consequences of Climate/Global Change for Siberia environment as follows from results of current scientific activity in climate monitoring and modelling. At present, the challenge facing the weather and climate scientists is to improve the prediction of interactions between weather/climate and Earth system. Taking into account significantly increased computing capacity, a special attention in the report is paid to perspectives of the Earth system modelling.

Enhancement of Local Climate Analysis Tool

NASA Astrophysics Data System (ADS)

Horsfall, F. M.; Timofeyeva, M. M.; Dutton, J.

2012-12-01

The National Oceanographic and Atmospheric Administration (NOAA) National Weather Service (NWS) will enhance its Local Climate Analysis Tool (LCAT) to incorporate specific capabilities to meet the needs of various users including energy, health, and other communities. LCAT is an online interactive tool that provides quick and easy access to climate data and allows users to conduct analyses at the local level such as time series analysis, trend analysis, compositing, correlation and regression techniques, with others to be incorporated as needed. LCAT uses principles of Artificial Intelligence in connecting human and computer perceptions on application of data and scientific techniques in multiprocessing simultaneous users' tasks. Future development includes expanding the type of data currently imported by LCAT (historical data at stations and climate divisions) to gridded reanalysis and General Circulation Model (GCM) data, which are available on global grids and thus will allow for climate studies to be conducted at international locations. We will describe ongoing activities to incorporate NOAA Climate Forecast System (CFS) reanalysis data (CFSR), NOAA model output data, including output from the National Multi Model Ensemble Prediction System (NMME) and longer term projection models, and plans to integrate LCAT into the Earth System Grid Federation (ESGF) and its protocols for accessing model output and observational data to ensure there is no redundancy in development of tools that facilitate scientific advancements and use of climate model information in applications. Validation and inter-comparison of forecast models will be included as part of the enhancement to LCAT. To ensure sustained development, we will investigate options for open sourcing LCAT development, in particular, through the University Corporation for Atmospheric Research (UCAR).

Redesigning mental healthcare delivery: is there an effect on organizational climate?

PubMed

Joosten, T C M; Bongers, I M B; Janssen, R T J M

2014-02-01

Many studies have investigated the effect of redesign on operational performance; fewer studies have evaluated the effects on employees' perceptions of their working environment (organizational climate). Some authors state that redesign will lead to poorer organizational climate, while others state the opposite. The goal of this study was to empirically investigate this relation. Organizational climate was measured in a field experiment, before and after a redesign intervention. At one of the sites, a redesign project was conducted. At the other site, no redesign efforts took place. Two Dutch child- and adolescent-mental healthcare providers. Professionals that worked at one of the units at the start and/or the end of the intervention period. The main intervention was a redesign project aimed at improving timely delivery of services (modeled after the breakthrough series). Scores on the four models of the organizational climate measure, a validated questionnaire that measures organizational climate. Our analysis showed that climate at the intervention site changed on factors related to productivity and goal achievement (rational goal model). The intervention group scored worse than the comparison group on the part of the questionnaire that focuses on sociotechnical elements of organizational climate. However, observed differences were so small, that their practical relevance seems rather limited. Redesign efforts in healthcare, so it seems, do not influence organizational climate as much as expected.

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.

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

DOE PAGES

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; ...

2016-09-28

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. Here, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide rangemore » of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. Furthermore, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. In order to serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less

Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

NASA Astrophysics Data System (ADS)

Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

2018-01-01

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

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

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.

2016-01-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate amore » wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

NASA Astrophysics Data System (ADS)

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; Eyring, Veronika; Friedlingstein, Pierre; Hurtt, George; Knutti, Reto; Kriegler, Elmar; Lamarque, Jean-Francois; Lowe, Jason; Meehl, Gerald A.; Moss, Richard; Riahi, Keywan; Sanderson, Benjamin M.

2016-09-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017-2018 time frame, and output from the climate model projections made available and analyses performed over the 2018-2020 period.

Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1

How will climate change affect the potential distribution of Eurasian Tree Sparrows Passer montanus in North America?

USGS Publications Warehouse

Graham, Jim; Jarnevich, Catherine; Young, Nick; Newman, Greg; Stohlgren, Thomas

2011-01-01

Habitat suitability models have been used to predict the present and future potential distribution of a variety of species. Eurasian tree sparrows Passer montanus, native to Eurasia, have established populations in other parts of the world. In North America, their current distribution is limited to a relatively small region around its original introduction to St. Louis, Missouri. We combined data from the Global Biodiversity Information Facility with current and future climate data to create habitat suitability models using Maxent for this species. Under projected climate change scenarios, our models show that the distribution and range of the Eurasian tree sparrow could increase as far as the Pacific Northwest and Newfoundland. This is potentially important information for prioritizing the management and control of this non-native species.

A Synoptic Weather Typing Approach to Assess Climate Change Impacts on Meteorological and Hydrological Risks at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Cheng, Chad Shouquan; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been applied in Environment Canada to analyze climatic change impacts on various meteorological/hydrological risks, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the hazardous events, (2) statistical downscaling to provide station-scale future climate information, and (3) estimates of changes in frequency and magnitude of future hazardous meteorological/hydrological events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and various linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into the entire modeling exercise. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. This paper will briefly summarize these research projects, focusing on the modeling exercise and results.

Wave climate and trends along the eastern Chukchi Arctic Alaska coast

USGS Publications Warehouse

Erikson, L.H.; Storlazzi, C.D.; Jensen, R.E.

2011-01-01

Due in large part to the difficulty of obtaining measurements in the Arctic, little is known about the wave climate along the coast of Arctic Alaska. In this study, numerical model simulations encompassing 40 years of wave hind-casts were used to assess mean and extreme wave conditions. Results indicate that the wave climate was strongly modulated by large-scale atmospheric circulation patterns and that mean and extreme wave heights and periods exhibited increasing trends in both the sea and swell frequency bands over the time-period studied (1954-2004). Model simulations also indicate that the upward trend was not due to a decrease in the minimum icepack extent. ?? 2011 ASCE.

Validation of catchment models for predicting land-use and climate change impacts. 1. Method

NASA Astrophysics Data System (ADS)

Ewen, J.; Parkin, G.

1996-02-01

Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (Parkin et al., J. Hydrol., 175:595-613, 1996).

The I.A.G. / A.I.G. SEDIBUD Book Project: Source-to-Sink Fluxes in Undisturbed Cold Environments

NASA Astrophysics Data System (ADS)

Beylich, Achim A.; Dixon, John C.; Zwolinski, Zbigniew

2015-04-01

The currently prepared SEDIBUD Book on "Source-to-Sink Fluxes in Undisturbed Cold Environments" (edited by Achim A. Beylich, John C. Dixon and Zbigniew Zwolinski and published by Cambridge University Press) is summarizing and synthesizing the achievements of the International Association of Geomorphologists` (I.A.G./A.I.G.) Working Group SEDIBUD (Sediment Budgets in Cold Environments), which has been active since 2005 (http://www.geomorph.org/wg/wgsb.html). Amplified climate change and ecological sensitivity of largely undisturbed polar and high-altitude cold climate environments have been highlighted as key global environmental issues. The effects of projected climate change will change surface environments in cold regions and will alter the fluxes of sediments, nutrients and solutes, but the absence of quantitative data and coordinated geomorphic process monitoring and analysis to understand the sensitivity of the Earth surface environment in these largely undisturbed environments is acute. Our book addresses this existing key knowledge gap. The applied approach of integrating comparable and longer-term field datasets on contemporary solute and sedimentary fluxes from a number of different defined cold climate catchment geosystems for better understanding (i) the environmental drivers and rates of contemporary denudational surface processes and (ii) possible effects of projected climate change in cold regions is unique in the field of geomorphology. Largely undisturbed cold climate environments can provide baseline data for modeling the effects of environmental change. The book synthesizes work carried out by numerous SEDIBUD Members over the last decade in numerous cold climate catchment geosystems worldwide. For reaching a global cover of different cold climate environments the book is - after providing an introduction part and a basic part on climate change in cold environments and general implications for solute and sedimentary fluxes - dealing in different defined parts with Sub-Arctic and Arctic Environments, Sub-Antarctic and Antarctic Environments, and Alpine / Mountain Environments. The book includes a synthesis key chapter where comparable datasets on contemporary solute and sedimentary fluxes generated during the conducted coordinated research efforts in different cold climate catchment geosystems are integrated with the key goals to (i) identify the main environmental drivers and rates of contemporary solute and sedimentary fluxes, and (ii) model possible effects of projected climate change on solute and sedimentary fluxes in cold climate environments. The SEDIBUD Book provides new key findings on environmental drivers and rates of contemporary solute and sedimentary fluxes, and on spatial variability within global cold climate environments. The book will go in production in July 2015.

AmeriFlux US-MRf Mary's River (Fir) site

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

Law, Bev

This is the AmeriFlux version of the carbon flux data for the site US-MRf Mary's River (Fir) site. Site Description - The Marys River Fir site is part of the "Synthesis of Remote Sensing and Field Observations to Model and Understand Disturbance and Climate Effects on the Carbon Balance of Oregon and Northern California (ORCA)". Located in the western region of Oregon the Marys River site represents the western extent of the climate gradient that spans eastward into the semi-arid basin of central Oregon. The sites that make up the eastern extent of the ORCA climate gradient is the Metoliusmore » site network (US-Me1, US-ME2, US-ME4, US-Me5) all of which are part of the TERRA PNW project at Oregon State University.« less

The 1430s: a cold period of extraordinary internal climate variability during the early Spörer Minimum with social and economic impacts in north-western and central Europe

NASA Astrophysics Data System (ADS)

Camenisch, Chantal; Keller, Kathrin M.; Salvisberg, Melanie; Amann, Benjamin; Bauch, Martin; Blumer, Sandro; Brázdil, Rudolf; Brönnimann, Stefan; Büntgen, Ulf; Campbell, Bruce M. S.; Fernández-Donado, Laura; Fleitmann, Dominik; Glaser, Rüdiger; González-Rouco, Fidel; Grosjean, Martin; Hoffmann, Richard C.; Huhtamaa, Heli; Joos, Fortunat; Kiss, Andrea; Kotyza, Oldřich; Lehner, Flavio; Luterbacher, Jürg; Maughan, Nicolas; Neukom, Raphael; Novy, Theresa; Pribyl, Kathleen; Raible, Christoph C.; Riemann, Dirk; Schuh, Maximilian; Slavin, Philip; Werner, Johannes P.; Wetter, Oliver

2016-12-01

Changes in climate affected human societies throughout the last millennium. While European cold periods in the 17th and 18th century have been assessed in detail, earlier cold periods received much less attention due to sparse information available. New evidence from proxy archives, historical documentary sources and climate model simulations permit us to provide an interdisciplinary, systematic assessment of an exceptionally cold period in the 15th century. Our assessment includes the role of internal, unforced climate variability and external forcing in shaping extreme climatic conditions and the impacts on and responses of the medieval society in north-western and central Europe.Climate reconstructions from a multitude of natural and anthropogenic archives indicate that the 1430s were the coldest decade in north-western and central Europe in the 15th century. This decade is characterised by cold winters and average to warm summers resulting in a strong seasonal cycle in temperature. Results from comprehensive climate models indicate consistently that these conditions occurred by chance due to the partly chaotic internal variability within the climate system. External forcing like volcanic eruptions tends to reduce simulated temperature seasonality and cannot explain the reconstructions. The strong seasonal cycle in temperature reduced food production and led to increasing food prices, a subsistence crisis and a famine in parts of Europe. Societies were not prepared to cope with failing markets and interrupted trade routes. In response to the crisis, authorities implemented numerous measures of supply policy and adaptation such as the installation of grain storage capacities to be prepared for future food production shortfalls.

The impact of climate change on the distribution of two threatened Dipterocarp trees.

PubMed

Deb, Jiban C; Phinn, Stuart; Butt, Nathalie; McAlpine, Clive A

2017-04-01

Two ecologically and economically important, and threatened Dipterocarp trees Sal ( Shorea robusta ) and Garjan ( Dipterocarpus turbinatus ) form mono-specific canopies in dry deciduous, moist deciduous, evergreen, and semievergreen forests across South Asia and continental parts of Southeast Asia. They provide valuable timber and play an important role in the economy of many Asian countries. However, both Dipterocarp trees are threatened by continuing forest clearing, habitat alteration, and global climate change. While climatic regimes in the Asian tropics are changing, research on climate change-driven shifts in the distribution of tropical Asian trees is limited. We applied a bioclimatic modeling approach to these two Dipterocarp trees Sal and Garjan. We used presence-only records for the tree species, five bioclimatic variables, and selected two climatic scenarios (RCP4.5: an optimistic scenario and RCP8.5: a pessimistic scenario) and three global climate models (GCMs) to encompass the full range of variation in the models. We modeled climate space suitability for both species, projected to 2070, using a climate envelope modeling tool "MaxEnt" (the maximum entropy algorithm). Annual precipitation was the key bioclimatic variable in all GCMs for explaining the current and future distributions of Sal and Garjan (Sal: 49.97 ± 1.33; Garjan: 37.63 ± 1.19). Our models predict that suitable climate space for Sal will decline by 24% and 34% (the mean of the three GCMs) by 2070 under RCP4.5 and RCP8.5, respectively. In contrast, the consequences of imminent climate change appear less severe for Garjan, with a decline of 17% and 27% under RCP4.5 and RCP8.5, respectively. The findings of this study can be used to set conservation guidelines for Sal and Garjan by identifying vulnerable habitats in the region. In addition, the natural habitats of Sal and Garjan can be categorized as low to high risk under changing climates where artificial regeneration should be undertaken for forest restoration.

Mesoscale numerical modeling of meteorological events in a strong topographic gradient in the northeastern part of Mexico

NASA Astrophysics Data System (ADS)

Pineda-Martinez, Luis F.; Carbajal, Noel

2009-08-01

A series of numerical experiments were carried out to study the effect of meteorological events such as warm and cold air masses on climatic features and variability of a understudied region with strong topographic gradients in the northeastern part of Mexico. We applied the mesoscale model MM5. We investigated the influence of soil moisture availability in the performance of the model under two representative events for winter and summer. The results showed that a better resolution in land use cover improved the agreement among observed and calculated data. The topography induces atmospheric circulation patterns that determine the spatial distribution of climate and seasonal behavior. The numerical experiments reveal regions favorable to forced convection on the eastern side of the mountain chains Eastern Sierra Madre and Sierra de Alvarez. These processes affect the vertical and horizontal structure of the meteorological variables along the topographic gradient.

The continuum of hydroclimate variability in western North America during the last millennium

USGS Publications Warehouse

Ault, Toby R.; Cole, Julia E.; Overpeck, Jonathan T.; Pederson, Gregory T.; St. George, Scott; Otto-Bliesner, Bette; Woodhouse, Connie A.; Deser, Clara

2013-01-01

The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here we estimate power spectra and power laws (ß) from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). We test the significance of our estimates of spectral densities and ß against the null hypothesis that they reflect solely the effects of local (non-climate) sources of autocorrelation at the monthly timescale. Although tree-ring based hydroclimate reconstructions are generally consistent with this null hypothesis, values of ß calculated from long-moisture sensitive chronologies (as opposed to reconstructions), and other types of hydroclimate proxies, exceed null expectations. We therefore argue that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of the Climate Model Intercomparison Project 5 (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal to multidecadal timescales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future.

Building Systems from Scratch: an Exploratory Study of Students Learning About Climate Change

NASA Astrophysics Data System (ADS)

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual programming environment, Scratch, to design games to teach others about climate change. The experience was carefully constructed so that girls of widely differing levels of experience were able to engage in a cycle of game design. This qualitative study aimed to explore the representational choices the girls made as they took up aspects of climate change systems and modeled them in their games. Evidence points to the ways in which designing games about climate science fostered emergent systems thinking and engagement in modeling practices as learners chose what to represent in their games, grappled with the realism of their respective representations, and modeled interactions among systems components. Given the girls' levels of programming skill, parts of systems were more tractable to create than others. The educational purpose of the games was important to the girls' overall design experience, since it influenced their choice of topic, and challenged their emergent understanding of climate change as a systems problem.

Response of air-sea carbon fluxes and climate to orbital forcing changes in the Community Climate System Model

NASA Astrophysics Data System (ADS)

Jochum, M.; Peacock, S.; Moore, K.; Lindsay, K.

2010-07-01

A global general circulation model coupled to an ocean ecosystem model is used to quantify the response of carbon fluxes and climate to changes in orbital forcing. Compared to the present-day simulation, the simulation with the Earth's orbital parameters from 115,000 years ago features significantly cooler northern high latitudes but only moderately cooler southern high latitudes. This asymmetry is explained by a 30% reduction of the strength of the Atlantic Meridional Overturning Circulation that is caused by an increased Arctic sea ice export and a resulting freshening of the North Atlantic. The strong northern high-latitude cooling and the direct insolation induced tropical warming lead to global shifts in precipitation and winds to the order of 10%-20%. These climate shifts lead to regional differences in air-sea carbon fluxes of the same order. However, the differences in global net air-sea carbon fluxes are small, which is due to several effects, two of which stand out: first, colder sea surface temperature leads to a more effective solubility pump but also to increased sea ice concentration which blocks air-sea exchange, and second, the weakening of Southern Ocean winds that is predicted by some idealized studies occurs only in part of the basin, and is compensated by stronger winds in other parts.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century.

PubMed

Dessler, A E; Ye, H; Wang, T; Schoeberl, M R; Oman, L D; Douglass, A R; Butler, A H; Rosenlof, K H; Davis, S M; Portmann, R W

2016-03-16

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Transport of ice into the stratosphere and the humidification of the stratosphere over the 21st century

PubMed Central

Dessler, A.E.; Ye, H.; Wang, T.; Schoeberl, M.R.; Oman, L.D.; Douglass, A.R.; Butler, A.H.; Rosenlof, K.H.; Davis, S.M.; Portmann, R.W.

2018-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by ~1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50–80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales — on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community. PMID:29551841

Transport of Ice into the Stratosphere and the Humidification of the Stratosphere over the 21st Century

NASA Technical Reports Server (NTRS)

Dessler, A. E.; Ye, H.; Wang, T.; Schoeberl, M. R.; Oman, L. D.; Douglass, A. R.; Butler, A. H.; Rosenlof, K. H.; Davis, S. M.; Portmann, R. W.

2016-01-01

Climate models predict that tropical lower-stratospheric humidity will increase as the climate warms. We examine this trend in two state-of-the-art chemistry-climate models. Under high greenhouse gas emissions scenarios, the stratospheric entry value of water vapor increases by approx. 1 part per million by volume (ppmv) over this century in both models. We show with trajectory runs driven by model meteorological fields that the warming tropical tropopause layer (TTL) explains 50-80% of this increase. The remainder is a consequence of trends in evaporation of ice convectively lofted into the TTL and lower stratosphere. Our results further show that, within the models we examined, ice lofting is primarily important on long time scales - on interannual time scales, TTL temperature variations explain most of the variations in lower stratospheric humidity. Assessing the ability of models to realistically represent ice-lofting processes should be a high priority in the modeling community.

Modeling impacts of climate change on the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand.

PubMed

Suwannatrai, A; Pratumchart, K; Suwannatrai, K; Thinkhamrop, K; Chaiyos, J; Kim, C S; Suwanweerakamtorn, R; Boonmars, T; Wongsaroj, T; Sripa, B

2017-01-01

Global climate change is now regarded as imposing a significant threat of enhancing transmission of parasitic diseases. Maximum entropy species distribution modeling (MaxEnt) was used to explore how projected climate change could affect the potential distribution of the carcinogenic liver fluke, Opisthorchis viverrini, in Thailand. A range of climate variables was used: the Hadley Global Environment Model 2-Earth System (HadGEM2-ES) climate change model and also the IPCC scenarios A2a for 2050 and 2070. Occurrence data from surveys conducted in 2009 and 2014 were obtained from the Department of Disease Control, Ministry of Public Health, Thailand. The MaxEnt model performed better than random for O. viverrini with training AUC values greater than 0.8 under current and future climatic conditions. The current distribution of O. viverrini is significantly affected by precipitation and minimum temperature. According to current conditions, parts of Thailand climatically suitable for O. viverrini are mostly in the northeast and north, but the parasite is largely absent from southern Thailand. Under future climate change scenarios, the distribution of O. viverrini in 2050 should be significantly affected by precipitation, maximum temperature, and mean temperature of the wettest quarter, whereas in 2070, significant factors are likely to be precipitation during the coldest quarter, maximum, and minimum temperatures. Maps of predicted future distribution revealed a drastic decrease in presence of O. viverrini in the northeast region. The information gained from this study should be a useful reference for implementing long-term prevention and control strategies for O. viverrini in Thailand.

Workshop on early Mars: How warm and how wet, part 2?

NASA Technical Reports Server (NTRS)

Squyres, S. (Editor); Kasting, J. (Editor)

1993-01-01

In 1992 the MSATT program conducted a workshop on modeling of the Martian climate. At that workshop it became clear that a serious problem had arisen concerning the early climate of Mars. Based on the evidence for smallscale fluvial activity, the view had been widely held that early in its history Mars had a climate that was much warmer and wetter than today's. However, most plausible recent climate models have fallen far short of the warm temperatures often inferred from the geologic evidence. Moreover, recent geophysical work has suggested that early geothermal warming may also have played a significant role in allowing fluvial activity. In order to address the issue of just how warm and how wet early Mars was, a workshop was convened in July of 1993, in Breckenridge, Colorado. The results of the workshop are reported here.

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set

NASA Astrophysics Data System (ADS)

Day, J. J.; Tietsche, S.; Collins, M.; Goessling, H. F.; Guemas, V.; Guillory, A.; Hurlin, W. J.; Ishii, M.; Keeley, S. P. E.; Matei, D.; Msadek, R.; Sigmond, M.; Tatebe, H.; Hawkins, E.

2015-10-01

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.

Climate change or climate cycles? Snowpack trends in the Olympic and Cascade Mountains, Washington, USA.

PubMed

Barry, Dwight; McDonald, Shea

2013-01-01

Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region's precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models' relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses' time series. Posterior model probabilities of the 29 "most plausible" models ranged from 0.33 to 0.91 (mean = 0.58, s = 0.15). The majority of these time series (55%) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35% between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.

An overview of the South Atlantic Ocean climate variability and air-sea interaction processes

NASA Astrophysics Data System (ADS)

Pezzi, L. P.; Parise, C. K.; Souza, R.; Gherardi, D. F.; Camargo, R.; Soares, H. C.; Silveira, I.

2013-05-01

The Ocean Modeling Group at the National Institute of Space Research (INPE) in Brazil has been developing several studies to understand the role of the Atlantic ocean on the South America climate. Studies include simulating the dynamics of the Tropical South-Atlantic Ocean and Southern Ocean. This is part of an ongoing international cooperation, in which Brazil participates with in situ observations, numerical modeling and statistical analyses. We have focused on the understanding of the impacts of extreme weather events over the Tropical South Atlantic Ocean and their prediction on different time-scales. One such study is aimed at analyzing the climate signal generated by imposing an extreme condition on the Antarctic sea ice and considering different complexities of the sea ice model. The influence of the Brazil-Malvinas Confluence (BMC) region on the marine atmospheric boundary layer (MABL) is also investigated through in situ data analysis of different cruises and numerical experiments with a regional numerical model. There is also an ongoing investigation that revealed basin-scale interannual climate variation with impacts on the Brazilian Large Marine Ecosystems (LMEs), which are strongly correlated with climate indices such as ENSO, AAO and PDO.

Climate impacts on hydropower and consequences for global electricity supply investment needs

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

Turner, Sean W. D.; Hejazi, Mohamad; Kim, Son H.

Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore the possible consequences of these impacts for the electricity supply sector. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model with downscaled, bias-corrected climate realizations derived from sixteen general circulation models. Consequent impacts on power sector composition and associated emissions and investment costs are explored using the Global Change Assessment Model (GCAM). Changes in hydropower generation resulting from climate change can shift power demands onto andmore » away from carbon intensive technologies, resulting in significant impacts on power sector CO2 emissions for certain world regions—primarily those located in Latin America, as well as Canada and parts of Europe. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity—meaning impacts on power sector investment costs are similar for high and low emissions scenarios. Individual countries where impacts on investment costs imply significant risks or opportunities are identified.« less

Challenges in identifying sites climatically matched to the native ranges of animal invaders.

PubMed

Rodda, Gordon H; Jarnevich, Catherine S; Reed, Robert N

2011-02-09

Species distribution models are often used to characterize a species' native range climate, so as to identify sites elsewhere in the world that may be climatically similar and therefore at risk of invasion by the species. This endeavor provoked intense public controversy over recent attempts to model areas at risk of invasion by the Indian Python (Python molurus). We evaluated a number of MaxEnt models on this species to assess MaxEnt's utility for vertebrate climate matching. Overall, we found MaxEnt models to be very sensitive to modeling choices and selection of input localities and background regions. As used, MaxEnt invoked minimal protections against data dredging, multi-collinearity of explanatory axes, and overfitting. As used, MaxEnt endeavored to identify a single ideal climate, whereas different climatic considerations may determine range boundaries in different parts of the native range. MaxEnt was extremely sensitive to both the choice of background locations for the python, and to selection of presence points: inclusion of just four erroneous localities was responsible for Pyron et al.'s conclusion that no additional portions of the U.S. mainland were at risk of python invasion. When used with default settings, MaxEnt overfit the realized climate space, identifying models with about 60 parameters, about five times the number of parameters justifiable when optimized on the basis of Akaike's Information Criterion. When used with default settings, MaxEnt may not be an appropriate vehicle for identifying all sites at risk of colonization. Model instability and dearth of protections against overfitting, multi-collinearity, and data dredging may combine with a failure to distinguish fundamental from realized climate envelopes to produce models of limited utility. A priori identification of biologically realistic model structure, combined with computational protections against these statistical problems, may produce more robust models of invasion risk.

Challenges in Identifying Sites Climatically Matched to the Native Ranges of Animal Invaders

PubMed Central

Rodda, Gordon H.; Jarnevich, Catherine S.; Reed, Robert N.

2011-01-01

Background Species distribution models are often used to characterize a species' native range climate, so as to identify sites elsewhere in the world that may be climatically similar and therefore at risk of invasion by the species. This endeavor provoked intense public controversy over recent attempts to model areas at risk of invasion by the Indian Python (Python molurus). We evaluated a number of MaxEnt models on this species to assess MaxEnt's utility for vertebrate climate matching. Methodology/Principal Findings Overall, we found MaxEnt models to be very sensitive to modeling choices and selection of input localities and background regions. As used, MaxEnt invoked minimal protections against data dredging, multi-collinearity of explanatory axes, and overfitting. As used, MaxEnt endeavored to identify a single ideal climate, whereas different climatic considerations may determine range boundaries in different parts of the native range. MaxEnt was extremely sensitive to both the choice of background locations for the python, and to selection of presence points: inclusion of just four erroneous localities was responsible for Pyron et al.'s conclusion that no additional portions of the U.S. mainland were at risk of python invasion. When used with default settings, MaxEnt overfit the realized climate space, identifying models with about 60 parameters, about five times the number of parameters justifiable when optimized on the basis of Akaike's Information Criterion. Conclusions/Significance When used with default settings, MaxEnt may not be an appropriate vehicle for identifying all sites at risk of colonization. Model instability and dearth of protections against overfitting, multi-collinearity, and data dredging may combine with a failure to distinguish fundamental from realized climate envelopes to produce models of limited utility. A priori identification of biologically realistic model structure, combined with computational protections against these statistical problems, may produce more robust models of invasion risk. PMID:21347411

Challenges in identifying sites climatically matched to the native ranges of animal invaders

USGS Publications Warehouse

Rodda, G.H.; Jarnevich, C.S.; Reed, R.N.

2011-01-01

Background: Species distribution models are often used to characterize a species' native range climate, so as to identify sites elsewhere in the world that may be climatically similar and therefore at risk of invasion by the species. This endeavor provoked intense public controversy over recent attempts to model areas at risk of invasion by the Indian Python (Python molurus). We evaluated a number of MaxEnt models on this species to assess MaxEnt's utility for vertebrate climate matching. Methodology/Principal Findings: Overall, we found MaxEnt models to be very sensitive to modeling choices and selection of input localities and background regions. As used, MaxEnt invoked minimal protections against data dredging, multi-collinearity of explanatory axes, and overfitting. As used, MaxEnt endeavored to identify a single ideal climate, whereas different climatic considerations may determine range boundaries in different parts of the native range. MaxEnt was extremely sensitive to both the choice of background locations for the python, and to selection of presence points: inclusion of just four erroneous localities was responsible for Pyron et al.'s conclusion that no additional portions of the U.S. mainland were at risk of python invasion. When used with default settings, MaxEnt overfit the realized climate space, identifying models with about 60 parameters, about five times the number of parameters justifiable when optimized on the basis of Akaike's Information Criterion. Conclusions/Significance: When used with default settings, MaxEnt may not be an appropriate vehicle for identifying all sites at risk of colonization. Model instability and dearth of protections against overfitting, multi-collinearity, and data dredging may combine with a failure to distinguish fundamental from realized climate envelopes to produce models of limited utility. A priori identification of biologically realistic model structure, combined with computational protections against these statistical problems, may produce more robust models of invasion risk.

Effect of Climate Change on Invasion Risk of Giant African Snail (Achatina fulica Férussac, 1821: Achatinidae) in India

PubMed Central

Rekha Sarma, Roshmi; Munsi, Madhushree; Neelavara Ananthram, Aravind

2015-01-01

The Giant African Snail (Achatina fulica) is considered to be one the world’s 100 worst invasive alien species. The snail has an impact on native biodiversity, and on agricultural and horticultural crops. In India, it is known to feed on more than fifty species of native plants and agricultural crops and also outcompetes the native snails. It was introduced into India in 1847 and since then it has spread all across the country. In this paper, we use ecological niche modeling (ENM) to assess the distribution pattern of Giant African Snail (GAS) under different climate change scenarios. The niche modeling results indicate that under the current climate scenario, Eastern India, peninsular India and the Andaman and Nicobar Islands are at high risk of invasion. The three different future climate scenarios show that there is no significant change in the geographical distribution of invasion prone areas. However, certain currently invaded areas will be more prone to invasion in the future. These regions include parts of Bihar, Southern Karnataka, parts of Gujarat and Assam. The Andaman and Nicobar and Lakshadweep Islands are highly vulnerable to invasion under changed climate. The Central Indian region is at low risk due to high temperature and low rainfall. An understanding of the invasion pattern can help in better management of this invasive species and also in formulating policies for its control. PMID:26618637

Effect of Climate Change on Invasion Risk of Giant African Snail (Achatina fulica Férussac, 1821: Achatinidae) in India.

PubMed

Sarma, Roshmi Rekha; Munsi, Madhushree; Ananthram, Aravind Neelavara

2015-01-01

The Giant African Snail (Achatina fulica) is considered to be one the world's 100 worst invasive alien species. The snail has an impact on native biodiversity, and on agricultural and horticultural crops. In India, it is known to feed on more than fifty species of native plants and agricultural crops and also outcompetes the native snails. It was introduced into India in 1847 and since then it has spread all across the country. In this paper, we use ecological niche modeling (ENM) to assess the distribution pattern of Giant African Snail (GAS) under different climate change scenarios. The niche modeling results indicate that under the current climate scenario, Eastern India, peninsular India and the Andaman and Nicobar Islands are at high risk of invasion. The three different future climate scenarios show that there is no significant change in the geographical distribution of invasion prone areas. However, certain currently invaded areas will be more prone to invasion in the future. These regions include parts of Bihar, Southern Karnataka, parts of Gujarat and Assam. The Andaman and Nicobar and Lakshadweep Islands are highly vulnerable to invasion under changed climate. The Central Indian region is at low risk due to high temperature and low rainfall. An understanding of the invasion pattern can help in better management of this invasive species and also in formulating policies for its control.

The role of sea-ice albedo in the climate of slowly rotating aquaplanets

NASA Astrophysics Data System (ADS)

Salameh, Josiane; Popp, Max; Marotzke, Jochem

2018-04-01

We investigate the influence of the rotation period (P_{rot}) on the mean climate of an aquaplanet, with a focus on the role of sea-ice albedo. We perform aquaplanet simulations with the atmospheric general circulation model ECHAM6 for various rotation periods from one Earth-day to 365 Earth-days in which case the planet is synchronously rotating. The global-mean surface temperature decreases with increasing P_{rot} and sea ice expands equatorwards. The cooling of the mean climate with increasing P_{rot} is caused partly by the high surface albedo of sea ice on the dayside and partly by the high albedo of the deep convective clouds over the substellar region. The cooling caused by these deep convective clouds is weak for non-synchronous rotations compared to synchronous rotation. Sensitivity simulations with the sea-ice model switched off show that the global-mean surface temperature is up to 27 K higher than in our main simulations with sea ice and thus highlight the large influence of sea ice on the climate. We present the first estimates of the influence of the rotation period on the transition of an Earth-like climate to global glaciation. Our results suggest that global glaciation of planets with synchronous rotation occurs at substantially lower incoming solar irradiation than for planets with slow but non-synchronous rotation.

CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind

NASA Astrophysics Data System (ADS)

Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.

2010-12-01

We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.

Effects of climate change on residential infiltration and air pollution exposure.

PubMed

Ilacqua, Vito; Dawson, John; Breen, Michael; Singer, Sarany; Berg, Ashley

2017-01-01

Air exchange through infiltration is driven partly by indoor/outdoor temperature differences, and as climate change increases ambient temperatures, such differences could vary considerably even with small ambient temperature increments, altering patterns of exposures to both indoor and outdoor pollutants. We calculated changes in air fluxes through infiltration for prototypical detached homes in nine metropolitan areas in the United States (Atlanta, Boston, Chicago, Houston, Los Angeles, Minneapolis, New York, Phoenix, and Seattle) from 1970-2000 to 2040-2070. The Lawrence Berkeley National Laboratory model of infiltration was used in combination with climate data from eight regionally downscaled climate models from the North American Regional Climate Change Assessment Program. Averaged over all study locations, seasons, and climate models, air exchange through infiltration would decrease by ~5%. Localized increased infiltration is expected during the summer months, up to 20-30%. Seasonal and daily variability in infiltration are also expected to increase, particularly during the summer months. Diminished infiltration in future climate scenarios may be expected to increase exposure to indoor sources of air pollution, unless these ventilation reductions are otherwise compensated. Exposure to ambient air pollution, conversely, could be mitigated by lower infiltration, although peak exposure increases during summer months should be considered, as well as other mechanisms.

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model

Treesearch

Shanlei Sun; Ge Sun; Peter Caldwell; Steven G. McNulty; Erika Cohen; Jingfeng Xiao; Yang Zhang

2015-01-01

Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and...

Bayesian hierarchical models for regional climate reconstructions of the last glacial maximum

NASA Astrophysics Data System (ADS)

Weitzel, Nils; Hense, Andreas; Ohlwein, Christian

2017-04-01

Spatio-temporal reconstructions of past climate are important for the understanding of the long term behavior of the climate system and the sensitivity to forcing changes. Unfortunately, they are subject to large uncertainties, have to deal with a complex proxy-climate structure, and a physically reasonable interpolation between the sparse proxy observations is difficult. Bayesian Hierarchical Models (BHMs) are a class of statistical models that is well suited for spatio-temporal reconstructions of past climate because they permit the inclusion of multiple sources of information (e.g. records from different proxy types, uncertain age information, output from climate simulations) and quantify uncertainties in a statistically rigorous way. BHMs in paleoclimatology typically consist of three stages which are modeled individually and are combined using Bayesian inference techniques. The data stage models the proxy-climate relation (often named transfer function), the process stage models the spatio-temporal distribution of the climate variables of interest, and the prior stage consists of prior distributions of the model parameters. For our BHMs, we translate well-known proxy-climate transfer functions for pollen to a Bayesian framework. In addition, we can include Gaussian distributed local climate information from preprocessed proxy records. The process stage combines physically reasonable spatial structures from prior distributions with proxy records which leads to a multivariate posterior probability distribution for the reconstructed climate variables. The prior distributions that constrain the possible spatial structure of the climate variables are calculated from climate simulation output. We present results from pseudoproxy tests as well as new regional reconstructions of temperatures for the last glacial maximum (LGM, ˜ 21,000 years BP). These reconstructions combine proxy data syntheses with information from climate simulations for the LGM that were performed in the PMIP3 project. The proxy data syntheses consist either of raw pollen data or of normally distributed climate data from preprocessed proxy records. Future extensions of our method contain the inclusion of other proxy types (transfer functions), the implementation of other spatial interpolation techniques, the use of age uncertainties, and the extension to spatio-temporal reconstructions of the last deglaciation. Our work is part of the PalMod project funded by the German Federal Ministry of Education and Science (BMBF).

Future climate change scenarios in Central America at high spatial resolution.

PubMed

Imbach, Pablo; Chou, Sin Chan; Lyra, André; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

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.

Future climate change scenarios in Central America at high spatial resolution

PubMed Central

Imbach, Pablo; Chou, Sin Chan; Rodrigues, Daniela; Rodriguez, Daniel; Latinovic, Dragan; Siqueira, Gracielle; Silva, Adan; Garofolo, Lucas; Georgiou, Selena

2018-01-01

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

Towards Supporting Climate Scientists and Impact Assessment Analysts with the Big Data Europe Platform

NASA Astrophysics Data System (ADS)

Klampanos, Iraklis; Vlachogiannis, Diamando; Andronopoulos, Spyros; Cofiño, Antonio; Charalambidis, Angelos; Lokers, Rob; Konstantopoulos, Stasinos; Karkaletsis, Vangelis

2016-04-01

The EU, Horizon 2020, project Big Data Europe (BDE) aims to support European companies and institutions in effectively managing and making use of big data in activities critical to their progress and success. BDE focuses on seven areas of societal impact: Health, Food and Agriculture, Energy, Transport, Climate, Social Sciences and Security. By reaching out to partners and stakeholders, BDE aims to elicit data-intensive requirements for, and deliver an ICT platform to cover aspects of publishing and consuming semantically interoperable, large-scale, multi-lingual data assets and knowledge. In this presentation we will describe the first BDE pilot for Climate, focusing on SemaGrow, its core component, which provides data querying and management based on data semantics. Over the last few decades, extended scientific effort in understanding climate change has resulted in a huge volume of model and observational data. Large international global and regional model inter-comparison projects have focused on creating a framework in support of climate model diagnosis, validation, documentation and data access. The application of climate model ensembles, a system consisting of different possible realisations of a climate model, has further significantly increased the amount of climate and weather data generated. The provision of such models satisfies the crucial objective of assessing potential impacts of climate change on well-being for adaptation, prevention and mitigation. One of the methodologies applied by the climate research and impact assessment communities is that of dynamical downscaling. This calculates values of atmospheric variables in smaller spatial and temporal scales, given a global model. On the company or institution level, this process can be greatly improved in terms of querying, data ingestion from various sources and formats, automatic data mapping, etc. The first Climate BDE pilot will facilitate the process of dynamical downscaling by providing a semantics-based interface to climate open data, eg{} to ESGF services, searching, downloading and indexing climate model and observational data, according to user requirements, such as coverage and experimental scenarios, executing dynamical downscaling models on institutional computing resources, and establishing a framework for metadata mappings and data lineage. The objectives of this pilot will be met building on the SemaGrow system and tools, which have been developed as part of the SemaGrow project in order to scale data intensive techniques up to extremely large data volumes and improve real time performance for agricultural experiments and analyses. SemaGrow is a query resolution and ingestion system for data and semantics. It is able to extract semantic features from data, index them and expose APIs to other BDE platform components. Moreover, SemaGrow provides tools for transforming and managing data in various formats (e.g. NetCDF), and their metadata. It can also interface between users and distributed, external data sources via SPARQL endpoints. This has been demonstrated as part of the SemaGrow project, on diverse and large-scale scientific use-cases. SemaGrow is an active data service in agINFRA, a data infrastructure for agriculture. https://github.com/semagrow/semagrow Big Data Europe (http://www.big-data-europe.eu) - grant agreement no.644564. Earth System Grid Federation: http://esgf.llnl.gov http://www.semagrow.eu http://aginfra.eu

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation.

PubMed

Campbell, Patrick; Zhang, Yang; Yan, Fang; Lu, Zifeng; Streets, David

2018-07-01

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NO x ), volatile organic compounds (VOCs), ammonia (NH 3 ), and sulfur dioxide (SO 2 ) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NO x , VOC, and NH 3 , while emissions from both the on-road and non-road modes have strong contributions to PM and SO 2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Testing competing forms of the Milankovitch hypothesis: A multivariate approach

NASA Astrophysics Data System (ADS)

Kaufmann, Robert K.; Juselius, Katarina

2016-02-01

We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.

Climate Change Impact on Variability of Rainfall Intensity in Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, L. Y.

2015-12-01

Extreme rainfall events are major problems in Ethiopia with the resulting floods that usually could cause significant damage to agriculture, ecology, infrastructure, disruption to human activities, loss of property, loss of lives and disease outbreak. The aim of this study was to explore the likely changes of precipitation extreme changes due to future climate change. The study specifically focuses to understand the future climate change impact on variability of rainfall intensity-duration-frequency in Upper Blue Nile basin. Precipitations data from two Global Climate Models (GCMs) have been used in the study are HadCM3 and CGCM3. Rainfall frequency analysis was carried out to estimate quantile with different return periods. Probability Weighted Method (PWM) selected estimation of parameter distribution and L-Moment Ratio Diagrams (LMRDs) used to find the best parent distribution for each station. Therefore, parent distributions for derived from frequency analysis are Generalized Logistic (GLOG), Generalized Extreme Value (GEV), and Gamma & Pearson III (P3) parent distribution. After analyzing estimated quantile simple disaggregation model was applied in order to find sub daily rainfall data. Finally the disaggregated rainfall is fitted to find IDF curve and the result shows in most parts of the basin rainfall intensity expected to increase in the future. As a result of the two GCM outputs, the study indicates there will be likely increase of precipitation extremes over the Blue Nile basin due to the changing climate. This study should be interpreted with caution as the GCM model outputs in this part of the world have huge uncertainty.

Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

NASA Astrophysics Data System (ADS)

Stockhause, M.; Höck, H.; Toussaint, F.; Lautenschlager, M.

2012-08-01

The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

Modeling a polycentric approach to the problem of climate change. Comment on "Climate change governance, cooperation and self-organization" by Pacheco, Vasconcelos & Santos

NASA Astrophysics Data System (ADS)

Milinski, Manfred

2014-12-01

Climate change is a global problem. Because of unlimited use of fossil energy and resulting greenhouse gas emissions the global temperature is rising causing floods, draughts and storms in all parts of the world with increasing frequency and strength. Dangerous climate change will occur with high probability after the global temperature has passed a certain threshold [1]. To avoid dangerous climate change global greenhouse gas emissions must be reduced to a level of 50% or less of the year-2000 emissions by 2050 [2-4]. All people on earth take part in this global target public goods game, "a game that we cannot afford to loose" [5]. Simulating this scenario in a nutshell a collective risk social dilemma game has shown that a small group of subjects can achieve a collective goal by sequential individual contributions but only when the risk of loosing their not invested money is high, e.g. 90% [6]. Cooperation in public goods games usually decreases with increasing group size [7]. Thus, does this mean that the global game will be lost?

The carbon cycle in the Australian Community Climate and Earth System Simulator (ACCESS-ESM1) - Part 1: Model description and pre-industrial simulation

NASA Astrophysics Data System (ADS)

Law, Rachel M.; Ziehn, Tilo; Matear, Richard J.; Lenton, Andrew; Chamberlain, Matthew A.; Stevens, Lauren E.; Wang, Ying-Ping; Srbinovsky, Jhan; Bi, Daohua; Yan, Hailin; Vohralik, Peter F.

2017-07-01

Earth system models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1, which comprises atmosphere (UM7.3), land (CABLE), ocean (MOM4p1), and sea-ice (CICE4.1) components with OASIS-MCT coupling, to which ocean and land carbon modules have been added. The land carbon model (as part of CABLE) can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model (WOMBAT, added to MOM) simulates the evolution of phosphate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. We perform multi-centennial pre-industrial simulations with a fixed atmospheric CO2 concentration and different land carbon model configurations (prescribed or prognostic leaf area index). We evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. Simulating leaf area index results in a slight warming of the atmosphere relative to the prescribed leaf area index case. Seasonal and interannual variations in land carbon exchange are sensitive to whether leaf area index is simulated, with interannual variations driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations. While our model overestimates surface phosphate values, the global primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model and consequent limits on the applicability of this model version. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.

Impacts of Climate Change on Biofuels Production

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

Melillo, Jerry M.

2014-04-30

The overall goal of this research project was to improve and use our biogeochemistry model, TEM, to simulate the effects of climate change and other environmental changes on the production of biofuel feedstocks. We used the improved version of TEM that is coupled with the economic model, EPPA, a part of MIT’s Earth System Model, to explore how alternative uses of land, including land for biofuels production, can help society meet proposed climate targets. During the course of this project, we have made refinements to TEM that include development of a more mechanistic plant module, with improved ecohydrology and considerationmore » of plant-water relations, and a more detailed treatment of soil nitrogen dynamics, especially processes that add or remove nitrogen from ecosystems. We have documented our changes to TEM and used the model to explore the effects on production in land ecosystems, including changes in biofuels production.« less

Hydrologic Response and Watershed Sensitivity to Climate Warming in California's Sierra Nevada

PubMed Central

Null, Sarah E.; Viers, Joshua H.; Mount, Jeffrey F.

2010-01-01

This study focuses on the differential hydrologic response of individual watersheds to climate warming within the Sierra Nevada mountain region of California. We describe climate warming models for 15 west-slope Sierra Nevada watersheds in California under unimpaired conditions using WEAP21, a weekly one-dimensional rainfall-runoff model. Incremental climate warming alternatives increase air temperature uniformly by 2°, 4°, and 6°C, but leave other climatic variables unchanged from observed values. Results are analyzed for changes in mean annual flow, peak runoff timing, and duration of low flow conditions to highlight which watersheds are most resilient to climate warming within a region, and how individual watersheds may be affected by changes to runoff quantity and timing. Results are compared with current water resources development and ecosystem services in each watershed to gain insight into how regional climate warming may affect water supply, hydropower generation, and montane ecosystems. Overall, watersheds in the northern Sierra Nevada are most vulnerable to decreased mean annual flow, southern-central watersheds are most susceptible to runoff timing changes, and the central portion of the range is most affected by longer periods with low flow conditions. Modeling results suggest the American and Mokelumne Rivers are most vulnerable to all three metrics, and the Kern River is the most resilient, in part from the high elevations of the watershed. Our research seeks to bridge information gaps between climate change modeling and regional management planning, helping to incorporate climate change into the development of regional adaptation strategies for Sierra Nevada watersheds. PMID:20368984

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

van der Zwaan, Bob; Calvin, Katherine V.; Clarke, Leon E.

The CLIMACAP-LAMP project, completed in December 2015, was an inter-model comparison exercise that focused on energy and climate change economics issues in Latin America. The project partners – co-financed by the EC / EuropeAid (CLIMACAP part) and EPA / USAID (LAMP part) and co-coordinated by respectively the Energy research Centre of the Netherlands (ECN) and the Pacific Northwest National Laboratory (PNNL) – report their main and detailed findings in this Special Issue of Energy Economics, exclusively dedicated to climate mitigation, low-carbon development and implications for energy and land use in Latin America. Our research endeavor included several of the mostmore » prominent regional energy modeling groups from Latin America, as well as a representative set of global integrated assessment modeling groups from a number of institutions from Europe and the US. About two dozen universities, research groups and environmental or consulting organizations took part in the CLIMACAP-LAMP cross-model comparison project, from both sides of the Atlantic. Over a handful of workshops were organized over the past four years in several countries in Latin America, attended by between 30 and 50 participants from, amongst others, Argentina, Brazil, Colombia, Mexico, the EU, and the US.« less

The representation of low-level clouds during the West African monsoon in weather and climate models

NASA Astrophysics Data System (ADS)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and radiation data) and ground-based eye observations of clouds and radiation measurements from weather stations. Our results show that many of the climate models have great difficulties representing the diurnal cycle of winds and clouds, leading to associated errors in radiation. Typical errors include a substantial underestimation of the lowest clouds accompanied by an overestimation of clouds at the top of the monsoon layer, indicating systematic problems in vertical exchange processes, which are also reflected in large errors in jet speed. Consequently, many models show a too flat diurnal cycle in cloudiness. This contribution is part of the EU-funded DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa) project that aims to investigate the impact of the drastic increase in anthropogenic emissions in West Africa on the local weather and climate, for example through cloud-aerosol interactions. The analysis of the capability of state-of-the-art numerical models to represent low-level cloudiness presented here is an important requisite for the planned assessments of the influence of anthropogenic aerosol.

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Developing a protocol for long-term population monitoring and habitat projections for a climate-sensitive sentinel species to track ecosystem change and species range shifts

NASA Astrophysics Data System (ADS)

Beers, A.

2016-12-01

As a response to ongoing climate change, many species have started to shift their ranges poleward and toward higher elevations and mountain environments are predicted to experience especially rapid climatic changes. Because of this, there is likely a greater risk of habitat loss and local extinctions for species at high elevations compared to species at lower elevations. Among those potentially threatened habitat specialists is the American pika (Ochotona princeps), a climate sensitive indicator of climate change effects which may already be experiencing climate driven extirpations. Pikas are considered sentinels, indicators of greater ecosystem change. Changes in their distribution speaks to changes in availability of resources they require and shifts in the environment. Pika presence is closely tied to sub-surface ice features that act as a temperature buffer and water source. Those sub-surface ice features are critical in water cycling and long-term water storage and drive downstream hydrological and ecological processes. Understanding how this species responds to climate change therefore provides a model to inform landscape level conservation and management decisions. Pikas may be particularly vulnerable in parts of Colorado, including Rocky Mountain National Park (ROMO) and the Niwot Ridge LTER (NWT), where they may face population collapse as habitat suitability and connectivity both decline in response to various possible climate change scenarios, in large part because of cold stress and declining functional connectivity. Because of their potential role as an ecosystem indicator, their risk for decline, and how limitations to their survival likely vary across their range, management groups can use place based models of habitat suitability for pikas or other sentinel species in designing long term monitoring protocols to detect ecosystem responses to climate change. In this project we used remotely sensed data, occupancy surveys, and a random tessellation stratification to design a protocol for ROMO and NWT that best suits those environments. We also demonstrate the efficacy of habitat models based on remote sensing and their potential application toward tracking ecosystem change and species range shifts.

“Black Swans” of Hydrology: Can our Models Address the Science of Hydrologic Change?

NASA Astrophysics Data System (ADS)

Kumar, P.

2009-12-01

Coupled models of terrestrial hydrology and climate have grown in complexity leading to better understanding of the coupling between the hydrosphere, biosphere, and the climate system. During the past two decades, these models have evolved through generational changes as they have grown in sophistication in their ability to resolve spatial heterogeneity as well as vegetation dynamics and biogeochemistry. These developments have, in part, been driven by data collection efforts ranging from focused field campaigns to long-term observational networks, advances in remote sensing and other measurement technologies, along with sophisticated estimation and assimilation methods. However, the hydrologic cycle is changing leading to unexpected and unanticipated behavior through emergent dynamics and patterns that are not part of the historical milieu. Is there a new thinking that is needed to address this challenge? The goal of this talk is to draw from the modeling developments in the past two decades to foster a debate for moving forward.

Adaptive and plastic responses of Quercus petraea populations to climate across Europe.

PubMed

Sáenz-Romero, Cuauhtémoc; Lamy, Jean-Baptiste; Ducousso, Alexis; Musch, Brigitte; Ehrenmann, François; Delzon, Sylvain; Cavers, Stephen; Chałupka, Władysław; Dağdaş, Said; Hansen, Jon Kehlet; Lee, Steve J; Liesebach, Mirko; Rau, Hans-Martin; Psomas, Achilleas; Schneck, Volker; Steiner, Wilfried; Zimmermann, Niklaus E; Kremer, Antoine

2017-07-01

How temperate forests will respond to climate change is uncertain; projections range from severe decline to increased growth. We conducted field tests of sessile oak (Quercus petraea), a widespread keystone European forest tree species, including more than 150 000 trees sourced from 116 geographically diverse populations. The tests were planted on 23 field sites in six European countries, in order to expose them to a wide range of climates, including sites reflecting future warmer and drier climates. By assessing tree height and survival, our objectives were twofold: (i) to identify the source of differential population responses to climate (genetic differentiation due to past divergent climatic selection vs. plastic responses to ongoing climate change) and (ii) to explore which climatic variables (temperature or precipitation) trigger the population responses. Tree growth and survival were modeled for contemporary climate and then projected using data from four regional climate models for years 2071-2100, using two greenhouse gas concentration trajectory scenarios each. Overall, results indicated a moderate response of tree height and survival to climate variation, with changes in dryness (either annual or during the growing season) explaining the major part of the response. While, on average, populations exhibited local adaptation, there was significant clinal population differentiation for height growth with winter temperature at the site of origin. The most moderate climate model (HIRHAM5-EC; rcp4.5) predicted minor decreases in height and survival, while the most extreme model (CCLM4-GEM2-ES; rcp8.5) predicted large decreases in survival and growth for southern and southeastern edge populations (Hungary and Turkey). Other nonmarginal populations with continental climates were predicted to be severely and negatively affected (Bercé, France), while populations at the contemporary northern limit (colder and humid maritime regions; Denmark and Norway) will probably not show large changes in growth and survival in response to climate change. © 2017 John Wiley & Sons Ltd.

Tropical Atlantic climate response to different freshwater input in high latitudes with an ocean-only general circulation model

NASA Astrophysics Data System (ADS)

Men, Guang; Wan, Xiuquan; Liu, Zedong

2016-10-01

Tropical Atlantic climate change is relevant to the variation of Atlantic meridional overturning circulation (AMOC) through different physical processes. Previous coupled climate model simulation suggested a dipole-like SST structure cooling over the North Atlantic and warming over the South Tropical Atlantic in response to the slowdown of the AMOC. Using an ocean-only global ocean model here, an attempt was made to separate the total influence of various AMOC change scenarios into an oceanic-induced component and an atmospheric-induced component. In contrast with previous freshwater-hosing experiments with coupled climate models, the ocean-only modeling presented here shows a surface warming in the whole tropical Atlantic region and the oceanic-induced processes may play an important role in the SST change in the equatorial south Atlantic. Our result shows that the warming is partly governed by oceanic process through the mechanism of oceanic gateway change, which operates in the regime where freshwater forcing is strong, exceeding 0.3 Sv. Strong AMOC change is required for the gateway mechanism to work in our model because only when the AMOC is sufficiently weak, the North Brazil Undercurrent can flow equatorward, carrying warm and salty north Atlantic subtropical gyre water into the equatorial zone. This threshold is likely to be model-dependent. An improved understanding of these issues may have help with abrupt climate change prediction later.

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

NASA Astrophysics Data System (ADS)

Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.

2013-05-01

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

GEWEX - The Global Energy and Water Cycle Experiment

NASA Technical Reports Server (NTRS)

Chahine, Moustafa T.

1992-01-01

GEWEX, which is part of the World Climate Research Program, has as its goal an order-of-magnitude improvement in the ability to model global precipitation and evaporation and furnish an accurate assessment of the sensitivity of atmospheric radiation and clouds. Attention will also be given to the response of the hydrological cycle and water resources to climate change. GEWEX employs a single program to coordinate all aspects of climatology from model development to the deployment and operation of observational systems. GEWEX will operate over the next two decades.

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Effects of City Expansion on Heat Stress under Climate Change Conditions

PubMed Central

Argüeso, Daniel; Evans, Jason P.; Pitman, Andrew J.; Di Luca, Alejandro

2015-01-01

We examine the joint contribution of urban expansion and climate change on heat stress over the Sydney region. A Regional Climate Model was used to downscale present (1990–2009) and future (2040–2059) simulations from a Global Climate Model. The effects of urban surfaces on local temperature and vapor pressure were included. The role of urban expansion in modulating the climate change signal at local scales was investigated using a human heat-stress index combining temperature and vapor pressure. Urban expansion and climate change leads to increased risk of heat-stress conditions in the Sydney region, with substantially more frequent adverse conditions in urban areas. Impacts are particularly obvious in extreme values; daytime heat-stress impacts are more noticeable in the higher percentiles than in the mean values and the impact at night is more obvious in the lower percentiles than in the mean. Urban expansion enhances heat-stress increases due to climate change at night, but partly compensates its effects during the day. These differences are due to a stronger contribution from vapor pressure deficit during the day and from temperature increases during the night induced by urban surfaces. Our results highlight the inappropriateness of assessing human comfort determined using temperature changes alone and point to the likelihood that impacts of climate change assessed using models that lack urban surfaces probably underestimate future changes in terms of human comfort. PMID:25668390

Potential impact of climate change on the Intra-Americas Sea: Part 2. Implications for Atlantic bluefin tuna and skipjack tuna adult and larval habitats

NASA Astrophysics Data System (ADS)

Muhling, Barbara A.; Liu, Yanyun; Lee, Sang-Ki; Lamkin, John T.; Roffer, Mitchell A.; Muller-Karger, Frank; Walter, John F., III

2015-08-01

Increasing water temperatures due to climate change will likely have significant impacts on distributions and life histories of Atlantic tunas. In this study, we combined predictive habitat models with a downscaled climate model to examine potential impacts on adults and larvae of Atlantic bluefin tuna (Thunnus thynnus) and skipjack tuna (Katsuwonus pelamis) in the Intra-Americas Sea (IAS). An additional downscaled model covering the 20th century was used to compare habitat fluctuations from natural variability to predicted future changes under two climate change scenarios: Representative Concentration Pathway (RCP) 4.5 (medium-low) and RCP 8.5 (high). Results showed marked temperature-induced habitat losses for both adult and larval bluefin tuna on their northern Gulf of Mexico spawning grounds. In contrast, habitat suitability for skipjack tuna increased as temperatures warmed. Model error was highest for the two skipjack tuna models, particularly at higher temperatures. This work suggests that influences of climate change on highly migratory Atlantic tuna species are likely to be substantial, but strongly species-specific. While impacts on fish populations remain uncertain, these changes in habitat suitability will likely alter the spatial and temporal availability of species to fishing fleets, and challenge equilibrium assumptions of environmental stability, upon which fisheries management benchmarks are based.

Can a reduction of solar irradiance counteract CO2-induced climate change? - Results from four Earth system models

NASA Astrophysics Data System (ADS)

Schmidt, H.; Alterskjær, K.; Karam, D. Bou; Boucher, O.; Jones, A.; Kristjansson, J. E.; Niemeier, U.; Schulz, M.; Aaheim, A.; Benduhn, F.; Lawrence, M.; Timmreck, C.

2012-01-01

In this study we compare the response of four state-of-the-art Earth system models to climate engineering under scenario G1 of the GeoMIP and IMPLICC model intercomparison projects. In G1, the radiative forcing from an instantaneous quadrupling of the CO2 concentration, starting from the preindustrial level, is balanced by a reduction of the solar constant. Model responses to the two counteracting forcings in G1 are compared to the preindustrial climate in terms of global means and regional patterns and their robustness. While the global mean surface air temperature in G1 remains almost unchanged, the meridional temperature gradient is reduced in all models compared to the control simulation. Another robust response is the global reduction of precipitation with strong effects in particular over North and South America and northern Eurasia. It is shown that this reduction is only partly compensated by a reduction in evaporation so that large continental regions are drier in the engineered climate. In comparison to the climate response to a quadrupling of CO2 alone the temperature responses are small in experiment G1. Precipitation responses are, however, of comparable magnitude but in many regions of opposite sign.

Simulating the Response of Urban Water Quality to Climate and Land Use Change in Partially Urbanized Basins

NASA Astrophysics Data System (ADS)

Sun, N.; Yearsley, J. R.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

Urban stream quality is particularly susceptible to extreme precipitation events and land use change. Although the projected effects of extreme events and land use change on hydrology have been resonably well studied, the impacts on urban water quality have not been widely examined due in part to the scale mismatch between global climate models and the spatial scales required to represent urban hydrology and water quality signals. Here we describe a grid-based modeling system that integrates the Distributed Hydrology Soil Vegetation Model (DHSVM) and urban water quality module adpated from EPA's Storm Water Management Model (SWMM) and Soil and water assessment tool (SWAT). Using the model system, we evaluate, for four partially urbanized catchments within the Puget Sound basin, urban water quality under current climate conditions, and projected potential changes in urban water quality associated with future changes in climate and land use. We examine in particular total suspended solids, toal nitrogen, total phosphorous, and coliform bacteria, with catchment representations at the 150-meter spatial resolution and the sub-daily timestep. We report long-term streamflow and water quality predictions in response to extreme precipitation events of varying magnitudes in the four partially urbanized catchments. Our simulations show that urban water quality is highly sensitive to both climatic and land use change.

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

Reconstructing Holocene climate using a climate model: Model strategy and preliminary results

NASA Astrophysics Data System (ADS)

Haberkorn, K.; Blender, R.; Lunkeit, F.; Fraedrich, K.

2009-04-01

An Earth system model of intermediate complexity (Planet Simulator; PlaSim) is used to reconstruct Holocene climate based on proxy data. The Planet Simulator is a user friendly general circulation model (GCM) suitable for palaeoclimate research. Its easy handling and the modular structure allow for fast and problem dependent simulations. The spectral model is based on the moist primitive equations conserving momentum, mass, energy and moisture. Besides the atmospheric part, a mixed layer-ocean with sea ice and a land surface with biosphere are included. The present-day climate of PlaSim, based on an AMIP II control-run (T21/10L resolution), shows reasonable agreement with ERA-40 reanalysis data. Combining PlaSim with a socio-technological model (GLUES; DFG priority project INTERDYNAMIK) provides improved knowledge on the shift from hunting-gathering to agropastoral subsistence societies. This is achieved by a data assimilation approach, incorporating proxy time series into PlaSim to initialize palaeoclimate simulations during the Holocene. For this, the following strategy is applied: The sensitivities of the terrestrial PlaSim climate are determined with respect to sea surface temperature (SST) anomalies. Here, the focus is the impact of regionally varying SST both in the tropics and the Northern Hemisphere mid-latitudes. The inverse of these sensitivities is used to determine the SST conditions necessary for the nudging of land and coastal proxy climates. Preliminary results indicate the potential, the uncertainty and the limitations of the method.

Projected climate impacts for the amphibians of the western hemisphere

USGS Publications Warehouse

Lawler, Joshua J.; Shafer, Sarah L.; Bancroft, Betsy A.; Blaustein, Andrew R.

2010-01-01

Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate-driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071–2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate-change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted-range species not included in our range-shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted-range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad-scale guidance for directing conservation efforts.

Projected climate impacts for the amphibians of the Western hemisphere.

PubMed

Lawler, Joshua J; Shafer, Sarah L; Bancroft, Betsy A; Blaustein, Andrew R

2010-02-01

Given their physiological requirements, limited dispersal abilities, and hydrologically sensitive habitats, amphibians are likely to be highly sensitive to future climatic changes. We used three approaches to map areas in the western hemisphere where amphibians are particularly likely to be affected by climate change. First, we used bioclimatic models to project potential climate-driven shifts in the distribution of 413 amphibian species based on 20 climate simulations for 2071-2100. We summarized these projections to produce estimates of species turnover. Second, we mapped the distribution of 1099 species with restricted geographic ranges. Finally, using the 20 future climate-change simulations, we mapped areas that were consistently projected to receive less seasonal precipitation in the coming century and thus were likely to have altered microclimates and local hydrologies. Species turnover was projected to be highest in the Andes Mountains and parts of Central America and Mexico, where, on average, turnover rates exceeded 60% under the lower of two emissions scenarios. Many of the restricted-range species not included in our range-shift analyses were concentrated in parts of the Andes and Central America and in Brazil's Atlantic Forest. Much of Central America, southwestern North America, and parts of South America were consistently projected to experience decreased precipitation by the end of the century. Combining the results of the three analyses highlighted several areas in which amphibians are likely to be significantly affected by climate change for multiple reasons. Portions of southern Central America were simultaneously projected to experience high species turnover, have many additional restricted-range species, and were consistently projected to receive less precipitation. Together, our three analyses form one potential assessment of the geographic vulnerability of amphibians to climate change and as such provide broad-scale guidance for directing conservation efforts.

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

Allen, Melissa R.; Aziz, H. M. Abdul; Coletti, Mark A.

Changing human activity within a geographical location may have significant influence on the global climate, but that activity must be parameterized in such a way as to allow these high-resolution sub-grid processes to affect global climate within that modeling framework. Additionally, we must have tools that provide decision support and inform local and regional policies regarding mitigation of and adaptation to climate change. The development of next-generation earth system models, that can produce actionable results with minimum uncertainties, depends on understanding global climate change and human activity interactions at policy implementation scales. Unfortunately, at best we currently have only limitedmore » schemes for relating high-resolution sectoral emissions to real-time weather, ultimately to become part of larger regions and well-mixed atmosphere. Moreover, even our understanding of meteorological processes at these scales is imperfect. This workshop addresses these shortcomings by providing a forum for discussion of what we know about these processes, what we can model, where we have gaps in these areas and how we can rise to the challenge to fill these gaps.« less

Forests under climate change and air pollution: gaps in understanding and future directions for research.

PubMed

Matyssek, R; Wieser, G; Calfapietra, C; de Vries, W; Dizengremel, P; Ernst, D; Jolivet, Y; Mikkelsen, T N; Mohren, G M J; Le Thiec, D; Tuovinen, J-P; Weatherall, A; Paoletti, E

2012-01-01

Forests in Europe face significant changes in climate, which in interaction with air quality changes, may significantly affect forest productivity, stand composition and carbon sequestration in both vegetation and soils. Identified knowledge gaps and research needs include: (i) interaction between changes in air quality (trace gas concentrations), climate and other site factors on forest ecosystem response, (ii) significance of biotic processes in system response, (iii) tools for mechanistic and diagnostic understanding and upscaling, and (iv) the need for unifying modelling and empirical research for synthesis. This position paper highlights the above focuses, including the global dimension of air pollution as part of climate change and the need for knowledge transfer to enable reliable risk assessment. A new type of research site in forest ecosystems ("supersites") will be conducive to addressing these gaps by enabling integration of experimentation and modelling within the soil-plant-atmosphere interface, as well as further model development. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

NASA Astrophysics Data System (ADS)

Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

2012-06-01

This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA&D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA&D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA&D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA&D dataset in the context of regional climate research in the Euro-Mediterranean region.

Response of the pelagic system of the Pacific Ocean off Baja California Peninsula to the projected effects of climate change: insights from a numerical model.

NASA Astrophysics Data System (ADS)

Arellano, B.; Rivas, D.

2015-12-01

The response of the physical and biological dynamics of the Pacific Ocean off Baja California to the projected effects of climate change are studied using numerical simulations. This region is part of the California Current System, which is a highly productive ecosystem due to the seasonal upwelling, supporting all the trophic levels and important fisheries. The response of the ecosystem to the effects of climate change is uncertain and the information generated by models could be useful to predict future conditions. A three-dimensional hydrodinamical model is coupled to a Nitrate-Phytoplankton-Zooplankton-Detritus (NPZD) trophic model, and it is forced by the GFDL 3.0 model outputs. Monthly climatologies of variables such as temperature, nutrients, wind, and ocean circulation patterns during the historical period 1985-2005 are compared to the available observed data in order to assess the model's ability to reproduce the observed patterns. The system's response to a high-emission scenario proposed by the Intergovernmental Panel of Climate Change (IPCC) is also studied. The experiments are carried out using data correspondig to the RCP 6.0 scenario during the period 2006-2050.

Tropical Convection and Climate Processes in a Cumulus Ensemble Model

NASA Technical Reports Server (NTRS)

Sui, Chung-Hsiung

1999-01-01

Local convective-radiative equilibrium states of the tropical atmosphere are determined by the following external forcing: 1) Insolation, 2) Surface heat and moisture exchanges (primarily radiation and evaporation), 3) Heating and moistening induced by large-scale circulation. Understanding the equilibrium states of the tropical atmosphere in different external forcing conditions is of vital importance for studying cumulus parameterization, climate feedbacks, and climate changes. We extend our previous study using the Goddard Cumulus Ensemble (GCE) Model which resolves convective-radiative processes more explicitly than global climate models do. Several experiments are carried out under fixed insolation and sea surface temperature. The prescribed SST consists of a uniform warm pool (29C) surrounded by uniform cold SST (26C). The model produces "Walker"-type circulation with the ascending branch of the model atmosphere more humid than the descending part, but the vertically integrated temperature does not show a horizontal gradient. The results are compared with satellite measured moisture by SSM/I (Special Sensor Microwave/Imager) and temperature by MSU in the ascending and descending tropical atmosphere. The vertically integrated temperature and humidity in the two model regimes are comparable to the observed values in the tropics.

The Program for climate Model diagnosis and Intercomparison: 20-th anniversary Symposium

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

Potter, Gerald L; Bader, David C; Riches, Michael

Twenty years ago, W. Lawrence (Larry) Gates approached the U.S. Department of Energy (DOE) Office of Energy Research (now the Office of Science) with a plan to coordinate the comparison and documentation of climate model differences. This effort would help improve our understanding of climate change through a systematic approach to model intercomparison. Early attempts at comparing results showed a surprisingly large range in control climate from such parameters as cloud cover, precipitation, and even atmospheric temperature. The DOE agreed to fund the effort at the Lawrence Livermore National Laboratory (LLNL), in part because of the existing computing environment andmore » because of a preexisting atmospheric science group that contained a wide variety of expertise. The project was named the Program for Climate Model Diagnosis and Intercomparison (PCMDI), and it has changed the international landscape of climate modeling over the past 20 years. In spring 2009 the DOE hosted a 1-day symposium to celebrate the twentieth anniversary of PCMDI and to honor its founder, Larry Gates. Through their personal experiences, the morning presenters painted an image of climate science in the 1970s and 1980s, that generated early support from the international community for model intercomparison, thereby bringing PCMDI into existence. Four talks covered Gates's early contributions to climate research at the University of California, Los Angeles (UCLA), the RAND Corporation, and Oregon State University through the founding of PCMDI to coordinate the Atmospheric Model Intercomparison Project (AMIP). The speakers were, in order of presentation, Warren Washington [National Center for Atmospheric Research (NCAR)], Kelly Redmond (Western Regional Climate Center), George Boer (Canadian Centre for Climate Modelling and Analysis), and Lennart Bengtsson [University of Reading, former director of the European Centre for Medium-Range Weather Forecasts (ECMWF)]. The afternoon session emphasized the scientific ideas that are the basis of PCMDI's success, summarizing their evolution and impact. Four speakers followed the various PCMDI-supported climate model intercomparison projects, beginning with early work on cloud representations in models, presented by Robert D. Cess (Distinguished Professor Emeritus, Stony Brook University), and then the latest Cloud Feedback Model Intercomparison Projects (CFMIPs) led by Sandrine Bony (Laboratoire de M'©t'©orologie Dynamique). Benjamin Santer (LLNL) presented a review of the climate change detection and attribution (D & A) work pioneered at PCMDI, and Gerald A. Meehl (NCAR) ended the day with a look toward the future of climate change research.« less

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

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

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Hillel, Daniel

2015-01-01

Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

Effects of Irrigation on Global Climate During the 20th Century

NASA Technical Reports Server (NTRS)

Puma, M. J.; Cook, B. I.

2010-01-01

Various studies have documented the effects of modern ]day irrigation on regional and global climate, but none, to date, have considered the time ]varying impact of steadily increasing irrigation rates on climate during the 20th century. We investigate the impacts of observed irrigation changes over this century with two ensemble simulations using an atmosphere general circulation model. Both ensembles are forced with transient climate forcings and observed sea surface temperatures from 1902 to 2000; one ensemble includes irrigation specified by a time ]varying data set of irrigation water withdrawals. Early in the century, irrigation is primarily localized over southern and eastern Asia, leading to significant cooling in boreal summer (June.August) over these regions. This cooling spreads and intensifies by century fs end, following the rapid expansion of irrigation over North America, Europe, and Asia. Irrigation also leads to boreal winter (December.February) warming over parts of North America and Asia in the latter part of the century, due to enhanced downward longwave fluxes from increased near ]surface humidity. Precipitation increases occur primarily downwind of the major irrigation areas, although precipitation in parts of India decreases due to a weaker summer monsoon. Irrigation begins to significantly reduce temperatures and temperature trends during boreal summer over the Northern Hemisphere midlatitudes and tropics beginning around 1950; significant increases in precipitation occur in these same latitude bands. These trends reveal the varying importance of irrigation ]climate interactions and suggest that future climate studies should account for irrigation, especially in regions with unsustainable irrigation resources.

Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change

USGS Publications Warehouse

Sork, Victoria L.; Davis, Frank W.; Westfall, Robert; Flint, Alan L.; Ikegami, Makihiko; Wang, Hongfang; Grivet, Delphine

2010-01-01

Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata N??e, to assess how underlying genetic structure of populations might influence this species' ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region-specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971-2000) and future (2070-2100) climate grids. Future climatologies are based on a moderate-high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range-wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions. ?? 2010 Blackwell Publishing Ltd.

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

PubMed

Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

2014-09-15

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013 Elsevier B.V. All rights reserved.

Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change.

PubMed

Sork, Victoria L; Davis, Frank W; Westfall, Robert; Flint, Alan; Ikegami, Makihiko; Wang, Hongfang; Grivet, Delphine

2010-09-01

Rapid climate change jeopardizes tree populations by shifting current climate zones. To avoid extinction, tree populations must tolerate, adapt, or migrate. Here we investigate geographic patterns of genetic variation in valley oak, Quercus lobata Née, to assess how underlying genetic structure of populations might influence this species' ability to survive climate change. First, to understand how genetic lineages shape spatial genetic patterns, we examine historical patterns of colonization. Second, we examine the correlation between multivariate nuclear genetic variation and climatic variation. Third, to illustrate how geographic genetic variation could interact with regional patterns of 21st Century climate change, we produce region-specific bioclimatic distributions of valley oak using Maximum Entropy (MAXENT) models based on downscaled historical (1971-2000) and future (2070-2100) climate grids. Future climatologies are based on a moderate-high (A2) carbon emission scenario and two different global climate models. Chloroplast markers indicate historical range-wide connectivity via colonization, especially in the north. Multivariate nuclear genotypes show a strong association with climate variation that provides opportunity for local adaptation to the conditions within their climatic envelope. Comparison of regional current and projected patterns of climate suitability indicates that valley oaks grow in distinctly different climate conditions in different parts of their range. Our models predict widely different regional outcomes from local displacement of a few kilometres to hundreds of kilometres. We conclude that the relative importance of migration, adaptation, and tolerance are likely to vary widely for populations among regions, and that late 21st Century conditions could lead to regional extinctions.

Joint Applications Pilot of the National Climate Predictions and Projections Platform and the North Central Climate Science Center: Delivering climate projections on regional scales to support adaptation planning

NASA Astrophysics Data System (ADS)

Ray, A. J.; Ojima, D. S.; Morisette, J. T.

2012-12-01

The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in these projects is to provide the connections between climate data and running ecological models, and prototype these for future work. NCPP will develop capacities to provide enhanced climate information at relevant spatial and temporal scales, both for historical climate and projections of future climate, and will work to link expert guidance and understanding of modeling processes and evaluation of modeling with the use of numerical climate data. Translational information thus is a suite of information that aids in translation of numerical climate information into usable knowledge for applications, e.g. ecological response models, hydrologic risk studies. This information includes technical and scientific aspects including, but not limited to: 1) results of objective, quantitative evaluation of climate models & downscaling techniques, 2) guidance on appropriate uses and interpretation, i.e., understanding the advantages and limitations of various downscaling techniques for specific user applications, 3) characterizing and interpreting uncertainty, 4) Descriptions meaningful to applications, e.g. narratives. NCPP believes that translational information is best co-developed between climate scientists and applications scientists, such as the NC-CSC pilot.

Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

NASA Astrophysics Data System (ADS)

Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

The Integration of Climate Science and Collaborative Processes in Building Regional Climate Resiliency in Southeast Florida

NASA Astrophysics Data System (ADS)

Jurado, J.

2016-12-01

Southeast Florida is widely recognized as one of the most vulnerable regions in the United States to the impacts of climate change, especially sea level rise. Dense urban populations, low land elevations, flat topography, complex shorelines and a porous geology all contribute to the region's challenges. Regional and local governments have been working collaboratively to address shared climate mitigation and adaptation concerns as part of the four-county Southeast Florida Regional Climate Change Compact (Compact). This partnership has emphasized, in part, the use of climate data and the development of advanced technical tools and visualizations to help inform decision-making, improve communications, and guide investments. Prominent work products have included regional vulnerability maps and assessments, a unified sea level rise projection for southeast Florida, the development and application of hydrologic models in scenario planning, interdisciplinary resilient redesign planning workshops, and the development of regional climate indicators. Key to the Compact's efforts has been the engagement and expertise of academic and agency partners, including a formal collaboration between the Florida Climate Institute and the Compact to improve research and project collaborations focused on southeast Florida. This presentation will focus on the collaborative processes and work products that have served to accelerate resiliency planning and investments in southeast Florida, with specific examples of how local governments are using these work products to modernize agency processes, and build support among residents and business leaders.

A conceptual model of oceanic heat transport in the Snowball Earth scenario

NASA Astrophysics Data System (ADS)

Comeau, Darin; Kurtze, Douglas A.; Restrepo, Juan M.

2016-12-01

Geologic evidence suggests that the Earth may have been completely covered in ice in the distant past, a state known as Snowball Earth. This is still the subject of controversy, and has been the focus of modeling work from low-dimensional models up to state-of-the-art general circulation models. In our present global climate, the ocean plays a large role in redistributing heat from the equatorial regions to high latitudes, and as an important part of the global heat budget, its role in the initiation a Snowball Earth, and the subsequent climate, is of great interest. To better understand the role of oceanic heat transport in the initiation of Snowball Earth, and the resulting global ice covered climate state, the goal of this inquiry is twofold: we wish to propose the least complex model that can capture the Snowball Earth scenario as well as the present-day climate with partial ice cover, and we want to determine the relative importance of oceanic heat transport. To do this, we develop a simple model, incorporating thermohaline dynamics from traditional box ocean models, a radiative balance from energy balance models, and the more contemporary "sea glacier" model to account for viscous flow effects of extremely thick sea ice. The resulting model, consisting of dynamic ocean and ice components, is able to reproduce both Snowball Earth and present-day conditions through reasonable changes in forcing parameters. We find that including or neglecting oceanic heat transport may lead to vastly different global climate states, and also that the parameterization of under-ice heat transfer in the ice-ocean coupling plays a key role in the resulting global climate state, demonstrating the regulatory effect of dynamic ocean heat transport.

Revisiting historical climatic signals to better explore the future: prospects of water cycle changes in Central Sahel

NASA Astrophysics Data System (ADS)

Leauthaud, C.; Demarty, J.; Cappelaere, B.; Grippa, M.; Kergoat, L.; Velluet, C.; Guichard, F.; Mougin, E.; Chelbi, S.; Sultan, B.

2015-06-01

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.

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Projected asymmetric response of Adélie penguins to Antarctic climate change

NASA Astrophysics Data System (ADS)

Cimino, Megan A.; Lynch, Heather J.; Saba, Vincent S.; Oliver, Matthew J.

2016-06-01

The contribution of climate change to shifts in a species’ geographic distribution is a critical and often unresolved ecological question. Climate change in Antarctica is asymmetric, with cooling in parts of the continent and warming along the West Antarctic Peninsula (WAP). The Adélie penguin (Pygoscelis adeliae) is a circumpolar meso-predator exposed to the full range of Antarctic climate and is undergoing dramatic population shifts coincident with climate change. We used true presence-absence data on Adélie penguin breeding colonies to estimate past and future changes in habitat suitability during the chick-rearing period based on historic satellite observations and future climate model projections. During the contemporary period, declining Adélie penguin populations experienced more years with warm sea surface temperature compared to populations that are increasing. Based on this relationship, we project that one-third of current Adélie penguin colonies, representing ~20% of their current population, may be in decline by 2060. However, climate model projections suggest refugia may exist in continental Antarctica beyond 2099, buffering species-wide declines. Climate change impacts on penguins in the Antarctic will likely be highly site specific based on regional climate trends, and a southward contraction in the range of Adélie penguins is likely over the next century.

Multidisciplinary research in the space sciences

NASA Technical Reports Server (NTRS)

Broecker, W. S.; Flynn, G. W.

1983-01-01

Research activities were carried out in the following areas during this reporting period: (1) astrophysics; (2) climate and atmospheric modeling; and (3) climate applications of earth observations & geological studies. An ultra-low-noise 115 GHz receiver based upon a superconducting tunnel diode mixer has been designed and constructed. The first laboratory tests have yielded spectacular results: a single-sideband noise temperature of 75 K considerably more sensitive than any other receiver at this frequency. The receiver will replace that currently in use on the Columbia-GISS CO Sky Survey telescope. The 1.2 meter millimeter-wave telescope at Columbia University has been used to complete two large-scale surveys of molecular matter in the part of the inner galaxy which is visible from the Northern hemisphere (the first galactic quadrant); one of the distant galaxy and one of the solar neighborhood. The research conducted during the past year in the climate and atmospheric modeling programs has been focused on the development of appropriate atmospheric and upper ocean models, and preliminary applications of these models. Principal models are a one-dimensional radiative-convective model, a three-dimensional global climate model, and an upper ocean model. During the past year this project has focused on development of 2-channel satellite analysis methods and radiative transfer studies in support of multichannel analysis techniques.

Stratigraphic evidence of desertification in the west-central Great Plains within the past 1000 yr

USGS Publications Warehouse

Madole, R.F.

1994-01-01

Stratigraphic and geomorphic relations, archaeological data, and eight radiocarbon ages at five widely scattered localities in northeastern Colorado indicate that eolian sand was mobilized over broad areas within the past 1000 yr. The mobilization began after 1 ka, was episodic, and ended at some as yet undetermined time prior to the latter part of the 19th century. Given that climate-model simulations suggest only slight variation in average surface temperature and annual precipitation in this region during the past 1000 yr, this part of the Great Plains evidently is near the threshold of widespread eolian sand transport under the present climate. -Author

Advancing land surface model development with satellite-based Earth observations

NASA Astrophysics Data System (ADS)

Orth, Rene; Dutra, Emanuel; Trigo, Isabel F.; Balsamo, Gianpaolo

2017-04-01

The land surface forms an essential part of the climate system. It interacts with the atmosphere through the exchange of water and energy and hence influences weather and climate, as well as their predictability. Correspondingly, the land surface model (LSM) is an essential part of any weather forecasting system. LSMs rely on partly poorly constrained parameters, due to sparse land surface observations. With the use of newly available land surface temperature observations, we show in this study that novel satellite-derived datasets help to improve LSM configuration, and hence can contribute to improved weather predictability. We use the Hydrology Tiled ECMWF Scheme of Surface Exchanges over Land (HTESSEL) and validate it comprehensively against an array of Earth observation reference datasets, including the new land surface temperature product. This reveals satisfactory model performance in terms of hydrology, but poor performance in terms of land surface temperature. This is due to inconsistencies of process representations in the model as identified from an analysis of perturbed parameter simulations. We show that HTESSEL can be more robustly calibrated with multiple instead of single reference datasets as this mitigates the impact of the structural inconsistencies. Finally, performing coupled global weather forecasts we find that a more robust calibration of HTESSEL also contributes to improved weather forecast skills. In summary, new satellite-based Earth observations are shown to enhance the multi-dataset calibration of LSMs, thereby improving the representation of insufficiently captured processes, advancing weather predictability and understanding of climate system feedbacks. Orth, R., E. Dutra, I. F. Trigo, and G. Balsamo (2016): Advancing land surface model development with satellite-based Earth observations. Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-628

How uncertain are climate model projections of water availability indicators across the Middle East?

PubMed

Hemming, Debbie; Buontempo, Carlo; Burke, Eleanor; Collins, Mat; Kaye, Neil

2010-11-28

The projection of robust regional climate changes over the next 50 years presents a considerable challenge for the current generation of climate models. Water cycle changes are particularly difficult to model in this area because major uncertainties exist in the representation of processes such as large-scale and convective rainfall and their feedback with surface conditions. We present climate model projections and uncertainties in water availability indicators (precipitation, run-off and drought index) for the 1961-1990 and 2021-2050 periods. Ensembles from two global climate models (GCMs) and one regional climate model (RCM) are used to examine different elements of uncertainty. Although all three ensembles capture the general distribution of observed annual precipitation across the Middle East, the RCM is consistently wetter than observations, especially over the mountainous areas. All future projections show decreasing precipitation (ensemble median between -5 and -25%) in coastal Turkey and parts of Lebanon, Syria and Israel and consistent run-off and drought index changes. The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) GCM ensemble exhibits drying across the north of the region, whereas the Met Office Hadley Centre work Quantifying Uncertainties in Model ProjectionsAtmospheric (QUMP-A) GCM and RCM ensembles show slight drying in the north and significant wetting in the south. RCM projections also show greater sensitivity (both wetter and drier) and a wider uncertainty range than QUMP-A. The nature of these uncertainties suggests that both large-scale circulation patterns, which influence region-wide drying/wetting patterns, and regional-scale processes, which affect localized water availability, are important sources of uncertainty in these projections. To reduce large uncertainties in water availability projections, it is suggested that efforts would be well placed to focus on the understanding and modelling of both large-scale processes and their teleconnections with Middle East climate and localized processes involved in orographic precipitation.

A zonally symmetric model for the monsoon-Hadley circulation with stochastic convective forcing

NASA Astrophysics Data System (ADS)

De La Chevrotière, Michèle; Khouider, Boualem

2017-02-01

Idealized models of reduced complexity are important tools to understand key processes underlying a complex system. In climate science in particular, they are important for helping the community improve our ability to predict the effect of climate change on the earth system. Climate models are large computer codes based on the discretization of the fluid dynamics equations on grids of horizontal resolution in the order of 100 km, whereas unresolved processes are handled by subgrid models. For instance, simple models are routinely used to help understand the interactions between small-scale processes due to atmospheric moist convection and large-scale circulation patterns. Here, a zonally symmetric model for the monsoon circulation is presented and solved numerically. The model is based on the Galerkin projection of the primitive equations of atmospheric synoptic dynamics onto the first modes of vertical structure to represent free tropospheric circulation and is coupled to a bulk atmospheric boundary layer (ABL) model. The model carries bulk equations for water vapor in both the free troposphere and the ABL, while the processes of convection and precipitation are represented through a stochastic model for clouds. The model equations are coupled through advective nonlinearities, and the resulting system is not conservative and not necessarily hyperbolic. This makes the design of a numerical method for the solution of this system particularly difficult. Here, we develop a numerical scheme based on the operator time-splitting strategy, which decomposes the system into three pieces: a conservative part and two purely advective parts, each of which is solved iteratively using an appropriate method. The conservative system is solved via a central scheme, which does not require hyperbolicity since it avoids the Riemann problem by design. One of the advective parts is a hyperbolic diagonal matrix, which is easily handled by classical methods for hyperbolic equations, while the other advective part is a nilpotent matrix, which is solved via the method of lines. Validation tests using a synthetic exact solution are presented, and formal second-order convergence under grid refinement is demonstrated. Moreover, the model is tested under realistic monsoon conditions, and the ability of the model to simulate key features of the monsoon circulation is illustrated in two distinct parameter regimes.

The Paleoclimate Uncertainty Cascade: Tracking Proxy Errors Via Proxy System Models.

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Dee, S. G.; Evans, M. N.; Adkins, J. F.

2014-12-01

Paleoclimatic observations are, by nature, imperfect recorders of climate variables. Empirical approaches to their calibration are challenged by the presence of multiple sources of uncertainty, which may confound the interpretation of signals and the identifiability of the noise. In this talk, I will demonstrate the utility of proxy system models (PSMs, Evans et al, 2013, 10.1016/j.quascirev.2013.05.024) to quantify the impact of all known sources of uncertainty. PSMs explicitly encode the mechanistic knowledge of the physical, chemical, biological and geological processes from which paleoclimatic observations arise. PSMs may be divided into sensor, archive and observation components, all of which may conspire to obscure climate signals in actual paleo-observations. As an example, we couple a PSM for the δ18O of speleothem calcite to an isotope-enabled climate model (Dee et al, submitted) to analyze the potential of this measurement as a proxy for precipitation amount. A simple soil/karst model (Partin et al, 2013, 10.1130/G34718.1) is used as sensor model, while a hiatus-permitting chronological model (Haslett & Parnell, 2008, 10.1111/j.1467-9876.2008.00623.x) is used as part of the observation model. This subdivision allows us to explicitly model the transformation from precipitation amount to speleothem calcite δ18O as a multi-stage process via a physical and chemical sensor model, and a stochastic archive model. By illustrating the PSM's behavior within the context of the climate simulations, we show how estimates of climate variability may be affected by each submodel's transformation of the signal. By specifying idealized climate signals(periodic vs. episodic, slow vs. fast) to the PSM, we investigate how frequency and amplitude patterns are modulated by sensor and archive submodels. To the extent that the PSM and the climate models are representative of real world processes, then the results may help us more accurately interpret existing paleodata, characterize their uncertainties, and design sampling strategies that exploit their strengths while mitigating their weaknesses.

European climate reconstructed for the past 500 years based on documentary and instrumental evidence

NASA Astrophysics Data System (ADS)

Wheeler, Dennis; Brazdil, Rudolf; Pfister, Christian

2010-05-01

European climate reconstructed for the past 500 years based on documentary and instrumental evidence Dennis Wheeler, Rudolf Brázdil, Christian Pfister and the Millennium project SG1 team The paper summarises the results of historical-climatological research conducted as part of the EU-funded 6th FP project MILLENNIUM the principal focus of which was the investigation of European climate during the past one thousand years (http://www.millenniumproject.net/). This project represents a major advance in bringing together, for the first time on such a scale, historical climatologists with other palaeoclimatological communities and climate modellers from many European countries. As part of MILLENNIUM, a sub-group (SG1) of historical climatologists from ten countries had the responsibility of collating and comprehensively analysing evidence from instrumental and documentary archives. This paper presents the main results of this undertaking but confines its attention to the study of the climate of the past 500 years and represents a summary of 10 themed papers submitted for a special issue of Climatic Change. They range across a variety of topics including newly-studied documentary data sources (e.g. early instrumental records, opening of the Stockholm harbour, ship log book data), temperature reconstructions for Central Europe, the Stockholm area and Mediterranean based on different types of documentary evidence, the application of standard paleoclimatological approaches to reconstructions based on index series derived from the documentary data, the influence of circulation dynamics on January-April climate , a comparison of reconstructions based on documentary data with the model runs (ECHO-G), a study of the quality of instrumental data in climate reconstructions, a 500-year flood chronology in Europe, and selected disastrous European windstorms and their reflection in documentary evidence and human memory. Finally, perspectives of historical-climatological research and future challenges and directions in this rapidly-developing and important field are presented together with an overview of the potential of documentary sources for climatic reconstructions.

On the identification of a Pliocene time slice for data–model comparison

USGS Publications Warehouse

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception.

On the identification of a Pliocene time slice for data–model comparison

PubMed Central

Haywood, Alan M.; Dolan, Aisling M.; Pickering, Steven J.; Dowsett, Harry J.; McClymont, Erin L.; Prescott, Caroline L.; Salzmann, Ulrich; Hill, Daniel J.; Hunter, Stephen J.; Lunt, Daniel J.; Pope, James O.; Valdes, Paul J.

2013-01-01

The characteristics of the mid-Pliocene warm period (mPWP: 3.264–3.025 Ma BP) have been examined using geological proxies and climate models. While there is agreement between models and data, details of regional climate differ. Uncertainties in prescribed forcings and in proxy data limit the utility of the interval to understand the dynamics of a warmer than present climate or evaluate models. This uncertainty comes, in part, from the reconstruction of a time slab rather than a time slice, where forcings required by climate models can be more adequately constrained. Here, we describe the rationale and approach for identifying a time slice(s) for Pliocene environmental reconstruction. A time slice centred on 3.205 Ma BP (3.204–3.207 Ma BP) has been identified as a priority for investigation. It is a warm interval characterized by a negative benthic oxygen isotope excursion (0.21–0.23‰) centred on marine isotope stage KM5c (KM5.3). It occurred during a period of orbital forcing that was very similar to present day. Climate model simulations indicate that proxy temperature estimates are unlikely to be significantly affected by orbital forcing for at least a precession cycle centred on the time slice, with the North Atlantic potentially being an important exception. PMID:24043865

Impact of climate change on runoff in Lake Urmia basin, Iran

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Amirataee, Babak

2018-04-01

Investigation of the impact of climate change on water resources is very necessary in dry and arid regions. In the first part of this paper, the climate model Long Ashton Research Station Weather Generator (LARS-WG) was used for downscaling climate data including rainfall, solar radiation, and minimum and maximum temperatures. Two different case studies including Aji-Chay and Mahabad-Chay River basins as sub-basins of Lake Urmia in the northwest part of Iran were considered. The results indicated that the LARS-WG successfully downscaled the climatic variables. By application of different emission scenarios (i.e., A1B, A2, and B1), an increasing trend in rainfall and a decreasing trend in temperature were predicted for both the basins over future time periods. In the second part of this paper, gene expression programming (GEP) was applied for simulating runoff of the basins in the future time periods including 2020, 2055, and 2090. The input combination including rainfall, solar radiation, and minimum and maximum temperatures in current and prior time was selected as the best input combination with highest predictive power for runoff prediction. The results showed that the peak discharge will decrease by 50 and 55.9% in 2090 comparing with the baseline period for the Aji-Chay and Mahabad-Chay basins, respectively. The results indicated that the sustainable adaptation strategies are necessary for these basins for protection of water resources in future.

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

DOE PAGES

Collins, William J.; Lamarque, Jean -François; Schulz, Michael; ...

2017-02-09

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

2011 Souris River flood—Will it happen again?

USGS Publications Warehouse

Nustad, Rochelle A.; Kolars, Kelsey A.; Vecchia, Aldo V.; Ryberg, Karen R.

2016-09-29

The Souris River Basin is a 61,000 square kilometer basin in the provinces of Saskatchewan and Manitoba and the state of North Dakota. Record setting rains in May and June of 2011 led to record flooding with peak annual streamflow values (762 cubic meters per second [m3/s]) more than twice that of any previously recorded peak streamflow and more than five times the estimated 100 year postregulation streamflow (142 m3/s) at the U.S. Geological Survey (USGS) streamflow-gaging station above Minot, North Dakota. Upstream from Minot, N. Dak., the Souris River is regulated by three reservoirs in Saskatchewan (Rafferty, Boundary, and Alameda) and Lake Darling in North Dakota. During the 2011 flood, the city of Minot, N. Dak., experienced devastating damages with more than 4,000 homes flooded and 11,000 evacuated. As a result, the Souris River Basin Task Force recommended the U.S. Geological Survey (in cooperation with the North Dakota State Water Commission) develop a model for estimating the probabilities of future flooding and drought. The model that was developed took on four parts: (1) looking at past climate, (2) predicting future climate, (3) developing a streamflow model in response to certain climatic variables, and (4) combining future climate estimates with the streamflow model to predict future streamflow events. By taking into consideration historical climate record and trends in basin response to various climatic conditions, it was determined flood risk will remain high in the Souris River Basin until the wet climate state ends.

AerChemMIP: Quantifying the effects of chemistry and aerosols in CMIP6

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

Collins, William J.; Lamarque, Jean -François; Schulz, Michael

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions. 1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period? 2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and theirmore » climate impacts? 3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates? 4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects? These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. As a result, specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.« less

The WASCAL high-resolution climate projection ensemble for West Africa

NASA Astrophysics Data System (ADS)

Kunstmann, Harald; Heinzeller, Dominikus; Dieng, Diarra; Smiatek, Gerhard; Bliefernicht, Jan; Hamann, Ilse; Salack, Seyni

2017-04-01

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.

MODELING THE EFFECTS OF CLIMATE AND LAND USE CHANGE ON CARBON AND TRACE GAS BUDGETS OVER THE AMAZON REGION USING NASA SATELLITE PRODUCTS

EPA Science Inventory

As part of the LBA-ECO Phase III synthesis efforts for remote sensing and predictive modeling of Amazon carbon, water, and trace gas fluxes, we are evaluating results from the regional ecosystem model called NASA-CASA (Carnegie-Ames Stanford Approach). The NASA-CASA model has bee...

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Climate change effects on Chikungunya transmission in Europe: geospatial analysis of vector's climatic suitability and virus' temperature requirements.

PubMed

Fischer, Dominik; Thomas, Stephanie M; Suk, Jonathan E; Sudre, Bertrand; Hess, Andrea; Tjaden, Nils B; Beierkuhnlein, Carl; Semenza, Jan C

2013-11-12

Chikungunya was, from the European perspective, considered to be a travel-related tropical mosquito-borne disease prior to the first European outbreak in Northern Italy in 2007. This was followed by cases of autochthonous transmission reported in South-eastern France in 2010. Both events occurred after the introduction, establishment and expansion of the Chikungunya-competent and highly invasive disease vector Aedes albopictus (Asian tiger mosquito) in Europe. In order to assess whether these outbreaks are indicative of the beginning of a trend or one-off events, there is a need to further examine the factors driving the potential transmission of Chikungunya in Europe. The climatic suitability, both now and in the future, is an essential starting point for such an analysis. The climatic suitability for Chikungunya outbreaks was determined by using bioclimatic factors that influence, both vector and, pathogen. Climatic suitability for the European distribution of the vector Aedes albopictus was based upon previous correlative environmental niche models. Climatic risk classes were derived by combining climatic suitability for the vector with known temperature requirements for pathogen transmission, obtained from outbreak regions. In addition, the longest potential intra-annual season for Chikungunya transmission was estimated for regions with expected vector occurrences.In order to analyse spatio-temporal trends for risk exposure and season of transmission in Europe, climate change impacts are projected for three time-frames (2011-2040, 2041-2070 and 2071-2100) and two climate scenarios (A1B and B1) from the Intergovernmental Panel on Climate Change (IPCC). These climatic projections are based on regional climate model COSMO-CLM, which builds on the global model ECHAM5. European areas with current and future climatic suitability of Chikungunya transmission are identified. An increase in risk is projected for Western Europe (e.g. France and Benelux-States) in the first half of the 21st century and from mid-century onwards for central parts of Europe (e.g. Germany). Interestingly, the southernmost parts of Europe do not generally provide suitable conditions in these projections. Nevertheless, many Mediterranean regions will persist to be climatically suitable for transmission. Overall, the highest risk of transmission by the end of the 21st century was projected for France, Northern Italy and the Pannonian Basin (East-Central Europe). This general tendency is depicted in both, the A1B and B1 climate change scenarios. In order to guide preparedness for further outbreaks, it is crucial to anticipate risk as to identify areas where specific public health measures, such as surveillance and vector control, can be implemented. However, public health practitioners need to be aware that climate is only one factor driving the transmission of vector-borne disease.

Atmospheric Aerosol Properties and Climate Impacts

NASA Technical Reports Server (NTRS)

Chin, Mian; Kahn, Ralph A.; Remer, Lorraine A.; Yu, Hongbin; Rind, David; Feingold, Graham; Quinn, Patricia K.; Schwartz, Stephen E.; Streets, David G.; DeCola, Phillip;

Future climate and surface mass balance of Svalbard glaciers in an RCP8.5 climate scenario: a study with the regional climate model MAR forced by MIROC5

NASA Astrophysics Data System (ADS)

Lang, C.; Fettweis, X.; Erpicum, M.

2015-05-01

We have performed a future projection of the climate and surface mass balance (SMB) of Svalbard with the MAR (Modèle Atmosphérique Régional) regional climate model forced by MIROC5 (Model for Interdisciplinary Research on Climate), following the RCP8.5 scenario at a spatial resolution of 10 km. MAR predicts a similar evolution of increasing surface melt everywhere in Svalbard followed by a sudden acceleration of melt around 2050, with a larger melt increase in the south compared to the north of the archipelago. This melt acceleration around 2050 is mainly driven by the albedo-melt feedback associated with the expansion of the ablation/bare ice zone. This effect is dampened in part as the solar radiation itself is projected to decrease due to a cloudiness increase. The near-surface temperature is projected to increase more in winter than in summer as the temperature is already close to 0 °C in summer. The model also projects a stronger winter west-to-east temperature gradient, related to the large decrease of sea ice cover around Svalbard. By 2085, SMB is projected to become negative over all of Svalbard's glaciated regions, leading to the rapid degradation of the firn layer.

Modelling uncertainties and possible future trends of precipitation and temperature for 10 sub-basins in Columbia River Basin (CRB)

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Rana, A.; Qin, Y.; Moradkhani, H.

2014-12-01

Trends and changes in future climatic parameters, such as, precipitation and temperature have been a central part of climate change studies. In the present work, we have analyzed the seasonal and yearly trends and uncertainties of prediction in all the 10 sub-basins of Columbia River Basin (CRB) for future time period of 2010-2099. The work is carried out using 2 different sets of statistically downscaled Global Climate Model (GCMs) projection datasets i.e. Bias correction and statistical downscaling (BCSD) generated at Portland State University and The Multivariate Adaptive Constructed Analogs (MACA) generated at University of Idaho. The analysis is done for with 10 GCM downscaled products each from CMIP5 daily dataset totaling to 40 different downscaled products for robust analysis. Summer, winter and yearly trend analysis is performed for all the 10 sub-basins using linear regression (significance tested by student t test) and Mann Kendall test (0.05 percent significance level), for precipitation (P), temperature maximum (Tmax) and temperature minimum (Tmin). Thereafter, all the parameters are modelled for uncertainty, across all models, in all the 10 sub-basins and across the CRB for future scenario periods. Results have indicated in varied degree of trends for all the sub-basins, mostly pointing towards a significant increase in all three climatic parameters, for all the seasons and yearly considerations. Uncertainty analysis have reveled very high change in all the parameters across models and sub-basins under consideration. Basin wide uncertainty analysis is performed to corroborate results from smaller, sub-basin scale. Similar trends and uncertainties are reported on the larger scale as well. Interestingly, both trends and uncertainties are higher during winter period than during summer, contributing to large part of the yearly change.

Reconstructing the climate states of the Late Pleistocene with the MIROC climate model

NASA Astrophysics Data System (ADS)

Chan, Wing-Le; Abe-Ouchi, Ayako; O'ishi, Ryouta; Takahashi, Kunio

2014-05-01

The Late Pleistocene was a period which lasted from the Eemian interglacial period to the start of the warm Holocene and was characterized mostly by widespread glacial ice. It was also a period which saw modern humans spread throughout the world and other species of the same genus, like the Neanderthals, become extinct. Various hypotheses have been put forward to explain the extinction of Neanderthals, about 30,000 years ago. Among these is one which involves changes in past climate and the inability of Neanderthals to adapt to such changes. The last traces of Neanderthals coincide with the end of Marine Isotope Stage 3 (MIS3) which was marked by large fluctuations in temperature and so-called Heinrich events, as suggested by geochemical records from ice cores. It is thought that melting sea ice or icebergs originating from the Laurentide ice sheet led to a large discharge of freshwater into the North Atlantic Ocean during the Heinrich events and severely weakened the Atlantic meridional overturning circulation, with important environmental ramifications across parts of Europe such as sharp decreases in temperature and reduction in forest cover. In order to assess the effects of past climate change on past hominin migration and on the extinction of certain species, it is first important to have a good understanding of the past climate itself. In this study, we have used three variants of MIROC (The Model for Interdisciplinary Research on Climate), a global climate model, for a time slice experiment within the Late Pleistocene: two mid-resolution models (an atmosphere model and a coupled atmosphere-ocean model) and a high-resolution atmosphere model. To obtain a fuller picture, we also look at a cool stadial state as obtained from a 'freshwater hosing' coupled-model experiment, designed to mimic the effects of freshwater discharge in the North Atlantic. We next use the sea surface temperature response from this experiment to drive the atmosphere models. We discuss the general features of the model-simulated climates and how model resolution can affect these results. We also compare our results with some available proxy data to elucidate where model simulations show good agreement.

School environments and obesity: The mediating role of personal stress.

PubMed

Milam, Adam J; Jones, Chandria D; Debnam, Katrina J; Bradshaw, Catherine P

2017-01-01

Youth spend a large amount of time in the school environment. Given the multiple influences of teachers, peers, and food and physical activity options, youth are likely to experience stressors that can influence their weight. This study examines the association between school climate and weight status. Students ( n = 28,582; 58 schools) completed an online, anonymous school climate survey as part of the Maryland Safe and Supportive Schools Project. Multilevel structural equation modeling was used to explore the association between school climate, personal stress, and obesity. Analyses were stratified by gender. At the individual level, poor school climate (bullying, physical safety, and lack of whole-school connectedness) was associated with an increased likelihood of being overweight among females ( β =.115, p = .019) but not males ( β = .138; p =.244), after controlling for age, race, and physical activity. There was no association between school climate at the school level and being overweight among males or females. A second model included stress as a potential mediator; stress attenuated the relationship between poor school-related climate and being overweight ( β = .039; p = .048) among females. Findings suggest that stress related to school climate can play a role in the health and weight status of youth.

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2010-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance.

Increased nitrogen export from eastern North America to the Atlantic Ocean due to climatic and anthropogenic changes during 1901-2008

NASA Astrophysics Data System (ADS)

Yang, Qichun; Tian, Hanqin; Friedrichs, Marjorie A. M.; Hopkinson, Charles S.; Lu, Chaoqun; Najjar, Raymond G.

2015-06-01

We used a process-based land model, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH4+), nitrate (NO3-), dissolved organic nitrogen (DON), and particulate organic nitrogen (PON) from eastern North America, especially the drainage areas of the Gulf of Maine (GOM), Mid-Atlantic Bight (MAB), and South Atlantic Bight (SAB) during 1901-2008. Model simulations indicated that annual fluxes of NH4+, NO3-, DON, and PON from the study area during 1980-2008 were 0.019 ± 0.003 (mean ± 1 standard deviation) Tg N yr-1, 0.18 ± 0.035 Tg N yr-1, 0.10 ± 0.016 Tg N yr-1, and 0.043 ± 0.008 Tg N yr-1, respectively. NH4+, NO3-, and DON exports increased while PON export decreased from 1901 to 2008. Nitrogen export demonstrated substantial spatial variability across the study area. Increased NH4+ export mainly occurred around major cities in the MAB. NO3- export increased in most parts of the MAB but decreased in parts of the GOM. Enhanced DON export was mainly distributed in the GOM and the SAB. PON export increased in coastal areas of the SAB and northern parts of the GOM but decreased in the Piedmont areas and the eastern parts of the MAB. Climate was the primary reason for interannual variability in nitrogen export; fertilizer use and nitrogen deposition tended to enhance the export of all nitrogen species; livestock farming and sewage discharge were also responsible for the increases in NH4+ and NO3- fluxes; and land cover change (especially reforestation of former agricultural land) reduced the export of the four nitrogen species.

Transient climate simulations of the deglaciation 21-9 thousand years before present (version 1) - PMIP4 Core experiment design and boundary conditions

NASA Astrophysics Data System (ADS)

Ivanovic, Ruza F.; Gregoire, Lauren J.; Kageyama, Masa; Roche, Didier M.; Valdes, Paul J.; Burke, Andrea; Drummond, Rosemarie; Peltier, W. Richard; Tarasov, Lev

2016-07-01

The last deglaciation, which marked the transition between the last glacial and present interglacial periods, was punctuated by a series of rapid (centennial and decadal) climate changes. Numerical climate models are useful for investigating mechanisms that underpin the climate change events, especially now that some of the complex models can be run for multiple millennia. We have set up a Paleoclimate Modelling Intercomparison Project (PMIP) working group to coordinate efforts to run transient simulations of the last deglaciation, and to facilitate the dissemination of expertise between modellers and those engaged with reconstructing the climate of the last 21 000 years. Here, we present the design of a coordinated Core experiment over the period 21-9 thousand years before present (ka) with time-varying orbital forcing, greenhouse gases, ice sheets and other geographical changes. A choice of two ice sheet reconstructions is given, and we make recommendations for prescribing ice meltwater (or not) in the Core experiment. Additional focussed simulations will also be coordinated on an ad hoc basis by the working group, for example to investigate more thoroughly the effect of ice meltwater on climate system evolution, and to examine the uncertainty in other forcings. Some of these focussed simulations will target shorter durations around specific events in order to understand them in more detail and allow for the more computationally expensive models to take part.

Performance evaluation of a non-hydrostatic regional climate model over the Mediterranean/Black Sea area and climate projections for the XXI century

NASA Astrophysics Data System (ADS)

Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia

2013-04-01

In the framework of the Work Package 4 (Developing integrated tools for environmental assessment) of PERSEUS Project, high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes the Mediterranean and Black Seas, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Assessment of temperature and precipitation over Mediterranean Area and Black Sea with non hydrostatic high resolution regional climate model

NASA Astrophysics Data System (ADS)

Mercogliano, P.; Montesarchio, M.; Zollo, A.; Bucchignani, E.

2012-12-01

In the framework of the Italian GEMINA Project (program of expansion and development of the Euro-Mediterranean Center for Climate Change (CMCC), high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes all the Mediterranean Sea, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate patterns but also extremes of the present and future climate, in terms of temperature, precipitation and wind.

Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems

NASA Astrophysics Data System (ADS)

Wild, Martin; Folini, Doris; Henschel, Florian; Müller, Björn

2015-04-01

Traditionally, for the planning and assessment of solar energy systems, the amount of solar radiation (sunlight) incident on the Earth's surface is assumed to be constant over the years. However, with changing climate and air pollution levels, solar resources may no longer be stable over time and undergo substantial decadal changes. Observational records covering the past decades confirm long-term changes in this quantity. Here we examine, how the latest generation of climate models used for the 5th IPCC report projects potential changes in surface solar radiation over the coming decades, and how this may affect, in combination with the expected greenhouse warming, solar power output from photovoltaic (PV) systems. For this purpose, projections up to the mid 21th century from 39 state of the art climate models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are analysed globally and for selected key regions with major solar power production capacity. The large model ensemble allows to assess the degree of consistency of their projections. Models are largely consistent in the sign of the projected changes in solar radiation under cloud-free conditions as well as in surface temperatures over most of the globe, while still reasonably consistent over a considerable part of the globe in the sign of changes in cloudiness and associated changes in solar radiation. A first order estimate of the impact of solar radiation and temperature changes on energy yields of PV systems under the RPC8.5 scenario indicates statistically significant decreases in PV outputs in large parts of the world, but notable exceptions with positive trends in parts of Europe and the South-East of China. Projected changes between 2006 and 2049 under the RCP8.5 scenario overall are on the order of 1 % per decade for horizontal planes, but may be larger for tilted or tracked planes as well as on shorter (decadal) timescales. Related References: Wild, M., Folini, D., Henschel, F., and Müller, B. 2015: Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems, submitted. Muller, B., Wild, M., Driesse, A., and Behrens, K., 2014: Rethinking solar resource assessments in the context of global dimming and brightening, Solar Energy, 99, 272-282. Wild, M. 2012: Enlightening Global Dimming and Brightening. Bull. Amer. Meteor. Soc., 93, 27-37, doi:10.1175/BAMS-D-11-00074.1

Life history trade-off moderates model predictions of diversity loss from climate change

PubMed Central

2017-01-01

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. PMID:28520770

Can decadal climate predictions be improved by ocean ensemble dispersion filtering?

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kröner, I.; Ulbrich, U.; Cubasch, U.

2017-12-01

Decadal predictions by Earth system models aim to capture the state and phase of the climate several years inadvance. Atmosphere-ocean interaction plays an important role for such climate forecasts. While short-termweather forecasts represent an initial value problem and long-term climate projections represent a boundarycondition problem, the decadal climate prediction falls in-between these two time scales. The ocean memorydue to its heat capacity holds big potential skill on the decadal scale. In recent years, more precise initializationtechniques of coupled Earth system models (incl. atmosphere and ocean) have improved decadal predictions.Ensembles are another important aspect. Applying slightly perturbed predictions results in an ensemble. Insteadof using and evaluating one prediction, but the whole ensemble or its ensemble average, improves a predictionsystem. However, climate models in general start losing the initialized signal and its predictive skill from oneforecast year to the next. Here we show that the climate prediction skill of an Earth system model can be improvedby a shift of the ocean state toward the ensemble mean of its individual members at seasonal intervals. Wefound that this procedure, called ensemble dispersion filter, results in more accurate results than the standarddecadal prediction. Global mean and regional temperature, precipitation, and winter cyclone predictions showan increased skill up to 5 years ahead. Furthermore, the novel technique outperforms predictions with largerensembles and higher resolution. Our results demonstrate how decadal climate predictions benefit from oceanensemble dispersion filtering toward the ensemble mean. This study is part of MiKlip (fona-miklip.de) - a major project on decadal climate prediction in Germany.We focus on the Max-Planck-Institute Earth System Model using the low-resolution version (MPI-ESM-LR) andMiKlip's basic initialization strategy as in 2017 published decadal climate forecast: http://www.fona-miklip.de/decadal-forecast-2017-2026/decadal-forecast-for-2017-2026/ More informations about this study in JAMES:DOI: 10.1002/2016MS000787

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.

Global Pyrogeography: the Current and Future Distribution of Wildfire

PubMed Central

Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine

2009-01-01

Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494

Assessing climate change impacts on water resources in remote mountain regions

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; De Bièvre, Bert

2013-04-01

From a water resources perspective, remote mountain regions are often considered as a basket case. They are often regions where poverty is often interlocked with multiple threats to water supply, data scarcity, and high uncertainties. In these environments, it is paramount to generate locally relevant knowledge about water resources and how they impact local livelihoods. This is often problematic. Existing environmental data collection tends to be geographically biased towards more densely populated regions, and prioritized towards strategic economic activities. Data may also be locked behind institutional and technological barriers. These issues create a "knowledge trap" for data-poor regions, which is especially acute in remote and hard-to-reach mountain regions. We present lessons learned from a decade of water resources research in remote mountain regions of the Andes, Africa and South Asia. We review the entire tool chain of assessing climate change impacts on water resources, including the interrogation and downscaling of global circulation models, translating climate variables in water availability and access, and assessing local vulnerability. In global circulation models, mountain regions often stand out as regions of high uncertainties and lack of agreement of future trends. This is partly a technical artifact because of the different resolution and representation of mountain topography, but it also highlights fundamental uncertainties in climate impacts on mountain climate. This problem also affects downscaling efforts, because regional climate models should be run in very high spatial resolution to resolve local gradients, which is computationally very expensive. At the same time statistical downscaling methods may fail to find significant relations between local climate properties and synoptic processes. Further uncertainties are introduced when downscaled climate variables such as precipitation and temperature are to be translated in hydrologically relevant variables such as streamflow and groundwater recharge. Fundamental limitations in both the understanding of hydrological processes in mountain regions (e.g., glacier melt, wetland attenuation, groundwater flows) and in data availability introduce large uncertainties. Lastly, assessing access to water resources is a major challenge. Topographical gradients and barriers, as well as strong spatiotemporal variations in hydrological processes, makes it particularly difficult to assess which parts of the mountain population is most vulnerable to future perturbations of the water cycle.

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

PubMed Central

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change. PMID:24823495

Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity.

PubMed

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species' occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species' occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

Modeling the Climatic Consequences of Geoengineering

NASA Astrophysics Data System (ADS)

Somerville, R. C.

2005-12-01

The last half-century has seen the development of physically comprehensive computer models of the climate system. These models are the primary tool for making predictions of climate change due to human activities, such as emitting greenhouse gases into the atmosphere. Because scientific understanding of the climate system is incomplete, however, any climate model will necessarily have imperfections. The inevitable uncertainties associated with these models have sometimes been cited as reasons for not taking action to reduce such emissions. Climate models could certainly be employed to predict the results of various attempts at geoengineering, but many questions would arise. For example, in considering proposals to increase the planetary reflectivity by brightening parts of the land surface or by orbiting mirrors, can models be used to bound the results and to warm of unintended consequences? How could confidence limits be placed on such model results? How can climate changes due to proposed geoengineering be distinguished from natural variability? There are historical parallels on smaller scales, in which models have been employed to predict the results of attempts to alter the weather, such as the use of cloud seeding for precipitation enhancement, hail suppression and hurricane modification. However, there are also many lessons to be learned from the recent record of using models to simulate the effects of the great unintended geoengineering experiment involving greenhouse gases, now in progress. In this major research effort, the same types of questions have been studied at length. The best modern models have demonstrated an impressive ability to predict some aspects of climate change. A large body of evidence has already accumulated through comparing model predictions to many observed aspects of recent climate change, ranging from increases in ocean heat content to changes in atmospheric water vapor to reductions in glacier extent. The preponderance of expert opinion is that this evidence is now sufficient to establish the human cause of much recent climate change. Nevertheless, no model can provide detailed and fully trustworthy answers to every possible question of interest. As an example, how will the climatology of Atlantic hurricanes change as the greenhouse effect becomes stronger? Can models reliably forecast changes in the length of the hurricane season or changes in the geographical regions affected by hurricanes? The answer is no, or at least, not yet. Additionally, climate models are not based entirely on first principles, such as Newtonian physics. Instead, they have been developed primarily to simulate the present climate and relatively small departures from it. To achieve this goal, a certain amount of empiricism has been built into the models. The result has sometimes been to increase the apparent realism of models at the cost of limiting their generality. Thus, the available climate models may well be less capable of simulating a geoengineering experiment that might lead to a radically different climate. New model development may be required for this new application. The challenge is to distinguish between what models can and cannot do well. It would be irresponsible and unethical, either to undertake geoengineering projects without modeling their consequences, or to place blind faith in the models. To decide how best to model a proposed geoengineering technique requires a deep understanding of the strengths and weaknesses of climate models. The history of modeling successes and failures is a valuable guide to the wise interpretation of model results.

Climate change impact assessment on Veneto and Friuli Plain groundwater. Part I: an integrated modeling approach for hazard scenario construction.

PubMed

Baruffi, F; Cisotto, A; Cimolino, A; Ferri, M; Monego, M; Norbiato, D; Cappelletto, M; Bisaglia, M; Pretner, A; Galli, A; Scarinci, A; Marsala, V; Panelli, C; Gualdi, S; Bucchignani, E; Torresan, S; Pasini, S; Critto, A; Marcomini, A

2012-12-01

Climate change impacts on water resources, particularly groundwater, is a highly debated topic worldwide, triggering international attention and interest from both researchers and policy makers due to its relevant link with European water policy directives (e.g. 2000/60/EC and 2007/118/EC) and related environmental objectives. The understanding of long-term impacts of climate variability and change is therefore a key challenge in order to address effective protection measures and to implement sustainable management of water resources. This paper presents the modeling approach adopted within the Life+ project TRUST (Tool for Regional-scale assessment of groUndwater Storage improvement in adaptation to climaTe change) in order to provide climate change hazard scenarios for the shallow groundwater of high Veneto and Friuli Plain, Northern Italy. Given the aim to evaluate potential impacts on water quantity and quality (e.g. groundwater level variation, decrease of water availability for irrigation, variations of nitrate infiltration processes), the modeling approach integrated an ensemble of climate, hydrologic and hydrogeologic models running from the global to the regional scale. Global and regional climate models and downscaling techniques were used to make climate simulations for the reference period 1961-1990 and the projection period 2010-2100. The simulation of the recent climate was performed using observed radiative forcings, whereas the projections have been done prescribing the radiative forcings according to the IPCC A1B emission scenario. The climate simulations and the downscaling, then, provided the precipitation, temperatures and evapo-transpiration fields used for the impact analysis. Based on downscaled climate projections, 3 reference scenarios for the period 2071-2100 (i.e. the driest, the wettest and the mild year) were selected and used to run a regional geomorphoclimatic and hydrogeological model. The final output of the model ensemble produced information about the potential variations of the water balance components (e.g. river discharge, groundwater level and volume) due to climate change. Such projections were used to develop potential hazard scenarios for the case study area, to be further applied within climate change risk assessment studies for groundwater resources and associated ecosystems. This paper describes the models' chain and the methodological approach adopted in the TRUST project and analyzes the hazard scenarios produced in order to investigate climate change risks for the case study area. Copyright © 2012 Elsevier B.V. All rights reserved.

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Assessing Portuguese Guadiana Basin water management impacts under climate change and paleoclimate variability

NASA Astrophysics Data System (ADS)

Maia, Rodrigo; Oliveira, Bruno; Ramos, Vanessa; Brekke, Levi

2014-05-01

The water balance in each reservoir and the subsequent, related, water resource management decisions are, presently, highly information dependent and are therefore often limited to a reactive response (even if aimed towards preventing future issues regarding the water system). Taking advantage of the availability of scenarios for climate projections, it is now possible to estimate the likely future evolution of climate which represents an important stepping stone towards proactive, adaptative, water resource management. The purpose of the present study was to assess the potential effects of climate change in terms of temperature, precipitation, runoff and water availability/scarcity for application in water resource management decisions. The analysis here presented was applied to the Portuguese portion of the Guadiana River Basin, using a combination of observed climate and runoff data and the results of the Global Climate Models. The Guadiana River Basin was represented by its reservoirs on the Portuguese portion of the basin and, for the future period, an estimated value of the inflows originating in the Spanish part of the Basin. The change in climate was determined in terms of relative and absolute variations of climate (precipitation and temperature) and hydrology (runoff and water balance related information). Apart from the previously referred data, an hydrological model and a water management model were applied so as to obtain an extended range of data regarding runoff generation (calibrated to observed data) and water balance in the reservoirs (considering the climate change impacts in the inflows, outflows and water consumption). The water management model was defined in order to represent the reservoirs interaction including upstream to downstream discharges and water transfers. Under the present climate change context, decision-makers and stakeholders are ever more vulnerable to the uncertainties of climate. Projected climate in the Guadiana basin indicates an increase in temperatures and a reduction of the precipitation values which go well beyond the observed values and, therefore, must be forcefully included in any realistic proactive water resource management decision. Using the results of this study it is possible to estimate future water availability and consumption satisfaction allowing for the elaboration of informed management decisions. In this study, the CMIP 3 Global Climate Models were considered for the definition of the effects of climate change, using the median and extreme tendencies based on the range of variation of the multiple climate projection scenarios. The observed climate variability, along with these model-derived tendencies, were used to inform the hydrology and water management models for the historical and future periods, respectively. Additionally, for a more comprehensive analysis on climate variability, a stochastic model was implemented based on the paleoclimate variability obtained from tree-ring records.

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

NASA Astrophysics Data System (ADS)

Irby, Isaac David

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the pollution diet in light of future projections for air temperature, sea level, and precipitation was examined. While a changing climate will reduce the ability of the nutrient reduction to improve oxygen concentrations, that effect is trumped by the improvements in dissolved oxygen stemming from the pollution diet itself. However, climate change still has the potential to cause the current level of nutrient reduction to be inadequate. This is primarily due to the fact that low-oxygen conditions are predicted to start one week earlier, on average, in the future, with the primary changes resulting from the increase in temperature. Overall, this research lends an increased degree of confidence in the water quality modeling of the potential impact of the Chesapeake Bay pollution diet. This research also establishes the efficacy of utilizing a multiple model approach to examining projected changes in water quality while establishing that the pollution diet trumps the impact from climate change. This work will lead directly to advances in scientific understanding of the response of water quality, ecosystem health, and ecological resilience to the impacts of nutrient reduction and climate change.

A Statistical Bias Correction Tool for Generating Climate Change Scenarios in Indonesia based on CMIP5 Datasets

NASA Astrophysics Data System (ADS)

Faqih, A.

2017-03-01

Providing information regarding future climate scenarios is very important in climate change study. The climate scenario can be used as basic information to support adaptation and mitigation studies. In order to deliver future climate scenarios over specific region, baseline and projection data from the outputs of global climate models (GCM) is needed. However, due to its coarse resolution, the data have to be downscaled and bias corrected in order to get scenario data with better spatial resolution that match the characteristics of the observed data. Generating this downscaled data is mostly difficult for scientist who do not have specific background, experience and skill in dealing with the complex data from the GCM outputs. In this regards, it is necessary to develop a tool that can be used to simplify the downscaling processes in order to help scientist, especially in Indonesia, for generating future climate scenario data that can be used for their climate change-related studies. In this paper, we introduce a tool called as “Statistical Bias Correction for Climate Scenarios (SiBiaS)”. The tool is specially designed to facilitate the use of CMIP5 GCM data outputs and process their statistical bias corrections relative to the reference data from observations. It is prepared for supporting capacity building in climate modeling in Indonesia as part of the Indonesia 3rd National Communication (TNC) project activities.

Carbon Management In the Post-Cap-and-Trade Carbon Economy-Part II

NASA Astrophysics Data System (ADS)

DeGroff, F. A.

2014-12-01

This is the second installment in our search for a comprehensive economic model to mitigate climate change due to anthropogenic activity. Last year we presented how the unique features of our economic model measure changes in carbon flux due to anthropogenic activity, referred to as carbon quality or CQ, and how the model is used to value such changes in the climate system. This year, our paper focuses on how carbon quality can be implemented to capture the effect of economic activity and international trade on the climate system, thus allowing us to calculate a Return on Climate System (RoCS) for all economic assets and activity. The result is that the RoCS for each public and private economic activity and entity can be calculated by summing up the RoCS for each individual economic asset and activity in which an entity is engaged. Such a macro-level scale is used to rank public and private entities including corporations, governments, and even entire nations, as well as human adaptation and carbon storage activities, providing status and trending insights to evaluate policies on both a micro- and macro-economic level. With international trade, RoCS measures the embodied effects on climate change that will be needed to assess border fees to insure carbon parity on all imports and exports. At the core of our vision is a comprehensive, 'open-source' construct of which our carbon quality metric is the first element. One goal is to recognize each country's endemic resources and infrastructure that affect their ability to manage carbon, while preventing spatial and temporal shifting of carbon emissions that reduce or reverse efforts to mitigate climate change. The standards for calculating the RoCS can be promulgated as part of the Generally Accepted Accounted Principles (GAAP) and the International Financial Reporting Standards (IFRS) to ensure standard and consistent reporting. The value of such insights on the climate system at all levels will be crucial to managing anthropogenic activity in order to minimize the effect on the climate system. Without the insights provided by a comprehensive, standardized and verifiable RoCS, managing anthropogenic activity will be elusive and difficult to achieve, at best. Such a model may also be useful to manage the effect of anthropogenic activity on the nitrogen and phosphorous cycles.

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

NASA Astrophysics Data System (ADS)

Hasan, M. Alfi; Islam, A. K. M. Saiful; Akanda, Ali Shafqat

2017-11-01

In the era of global warning, the insight of future climate and their changing extremes is critical for climate-vulnerable regions of the world. In this study, we have conducted a robust assessment of Regional Climate Model (RCM) results in a monsoon-dominated region within the new Coupled Model Intercomparison Project Phase 5 (CMIP5) and the latest Representative Concentration Pathways (RCP) scenarios. We have applied an advanced bias correction approach to five RCM simulations in order to project future climate and associated extremes over Bangladesh, a critically climate-vulnerable country with a complex monsoon system. We have also generated a new gridded product that performed better in capturing observed climatic extremes than existing products. The bias-correction approach provided a notable improvement in capturing the precipitation extremes as well as mean climate. The majority of projected multi-model RCMs indicate an increase of rainfall, where one model shows contrary results during the 2080s (2071-2100) era. The multi-model mean shows that nighttime temperatures will increase much faster than daytime temperatures and the average annual temperatures are projected to be as hot as present-day summer temperatures. The expected increase of precipitation and temperature over the hilly areas are higher compared to other parts of the country. Overall, the projected extremities of future rainfall are more variable than temperature. According to the majority of the models, the number of the heavy rainy days will increase in future years. The severity of summer-day temperatures will be alarming, especially over hilly regions, where winters are relatively warm. The projected rise of both precipitation and temperature extremes over the intense rainfall-prone northeastern region of the country creates a possibility of devastating flash floods with harmful impacts on agriculture. Moreover, the effect of bias-correction, as presented in probable changes of both bias-corrected and uncorrected extremes, can be considered in future policy making.

Downscaling Pest Risk Analyses: Identifying Current and Future Potentially Suitable Habitats for Parthenium hysterophorus with Particular Reference to Europe and North Africa

PubMed Central

Kriticos, Darren J.; Brunel, Sarah; Ota, Noboru; Fried, Guillaume; Oude Lansink, Alfons G. J. M.; Panetta, F. Dane; Prasad, T. V. Ramachandra; Shabbir, Asad; Yaacoby, Tuvia

2015-01-01

Pest Risk Assessments (PRAs) routinely employ climatic niche models to identify endangered areas. Typically, these models consider only climatic factors, ignoring the ‘Swiss Cheese’ nature of species ranges due to the interplay of climatic and habitat factors. As part of a PRA conducted for the European and Mediterranean Plant Protection Organization, we developed a climatic niche model for Parthenium hysterophorus, explicitly including the effects of irrigation where it was known to be practiced. We then downscaled the climatic risk model using two different methods to identify the suitable habitat types: expert opinion (following the EPPO PRA guidelines) and inferred from the global spatial distribution. The PRA revealed a substantial risk to the EPPO region and Central and Western Africa, highlighting the desirability of avoiding an invasion by P. hysterophorus. We also consider the effects of climate change on the modelled risks. The climate change scenario indicated the risk of substantial further spread of P. hysterophorus in temperate northern hemisphere regions (North America, Europe and the northern Middle East), and also high elevation equatorial regions (Western Brazil, Central Africa, and South East Asia) if minimum temperatures increase substantially. Downscaling the climate model using habitat factors resulted in substantial (approximately 22–53%) reductions in the areas estimated to be endangered. Applying expert assessments as to suitable habitat classes resulted in the greatest reduction in the estimated endangered area, whereas inferring suitable habitats factors from distribution data identified more land use classes and a larger endangered area. Despite some scaling issues with using a globally conformal Land Use Systems dataset, the inferential downscaling method shows promise as a routine addition to the PRA toolkit, as either a direct model component, or simply as a means of better informing an expert assessment of the suitable habitat types. PMID:26325680

Paleodynamics of large closed lakes as a standard for climate modeling data verification

NASA Astrophysics Data System (ADS)

Kislov, Alexander

2015-04-01

Observed and reconstructed variations of large lakes can serve as a standard for assessing the quality of the model run off simulated by climate models. It provides the opportunity to assess whether models designed for future scenarios are skillful in 'out-of sample' climate change experiments. Based on general ideas about the laws of temporal dynamics relating to massive inertial objects, slow changes of the lake level under the semi-steady climate state can be represented as resulting from the accumulation of small anomalies in the water regime; it appears like a kind of "self-developing" system. To test this hypothesis, the water balance model of the Caspian Sea (CS) was used. Time scale for the CS is estimated as ~20 years. Model is interpreted as stochastic, and from this perspective, it is a Langevin equation that incorporates the action of precipitation and evaporation like random white noise, so that the whole can be thought of as an analogue of Brownian motion. Under these conditions, the CS palaeostages during the Holocene is represented by a system undergoing random walk. It should be emphasized that modeling results are interpreted from the probabilistic point of view, despite the fact that the model is deterministically based on the physical law of conservation of water mass. Despite the CS, another candidate to be as a potential evaluation tool for climate model simulations is the Black Sea (BS) until its merger with the Mediterranean. Therefore, although the image of the CS, BS and other lakes within the climate models is very simplified (or absent), changes in the levels could be used to assess the ability of climate models to reproduce the water budget over the catchment areas. For the CS or the BS, they are the large parts of the East European Plane and can be as indicators of climate model quality. However, the use of reconstructed data of other closed lakes is problematic. It is due to its water budget components cannot be simulated with needed accuracy because they are either too small (the size of the largest closed Siberian lake (the Chany) is less than the typical grid box of climate model) or they are located in mountain region (like the Issyk-Kul Lake, located in the northern Tian Shan mountains) where the lake variability is determined by badly reproduced glacier melting.

High Resolution Simulations of Future Climate in West Africa Using a Variable-Resolution Atmospheric Model

NASA Astrophysics Data System (ADS)

Adegoke, J. O.; Engelbrecht, F.; Vezhapparambu, S.

2013-12-01

In previous work demonstrated the application of a var¬iable-resolution global atmospheric model, the conformal-cubic atmospheric model (CCAM), across a wide range of spatial and time scales to investigate the ability of the model to provide realistic simulations of present-day climate and plausible projections of future climate change over sub-Saharan Africa. By applying the model in stretched-grid mode the versatility of the model dynamics, numerical formulation and physical parameterizations to function across a range of length scales over the region of interest, was also explored. We primarily used CCAM to illustrate the capability of the model to function as a flexible downscaling tool at the climate-change time scale. Here we report on additional long term climate projection studies performed by downscaling at much higher resolutions (8 Km) over an area that stretches from just south of Sahara desert to the southern coast of the Niger Delta and into the Gulf of Guinea. To perform these simulations, CCAM was provided with synoptic-scale forcing of atmospheric circulation from 2.5 deg resolution NCEP reanalysis at 6-hourly interval and SSTs from NCEP reanalysis data uses as lower boundary forcing. CCAM 60 Km resolution downscaled to 8 Km (Schmidt factor 24.75) then 8 Km resolution simulation downscaled to 1 Km (Schmidt factor 200) over an area approximately 50 Km x 50 Km in the southern Lake Chad Basin (LCB). Our intent in conducting these high resolution model runs was to obtain a deeper understanding of linkages between the projected future climate and the hydrological processes that control the surface water regime in this part of sub-Saharan Africa.

Revealing, Reducing, and Representing Uncertainties in New Hydrologic Projections for Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, Jeffrey; Clark, Martyn; Gutmann, Ethan; Wood, Andy; Nijssen, Bart; Rasmussen, Roy

2016-04-01

The United States Army Corps of Engineers (USACE) has had primary responsibility for multi-purpose water resource operations on most of the major river systems in the U.S. for more than 200 years. In that time, the USACE projects and programs making up those operations have proved mostly robust against the range of natural climate variability encountered over their operating life spans. However, in some watersheds and for some variables, climate change now is known to be shifting the hydroclimatic baseline around which that natural variability occurs and changing the range of that variability as well. This makes historical stationarity an inappropriate basis for assessing continued project operations under climate-changed futures. That means new hydroclimatic projections are required at multiple scales to inform decisions about specific threats and impacts, and for possible adaptation responses to limit water-resource vulnerabilities and enhance operational resilience. However, projections of possible future hydroclimatologies have myriad complex uncertainties that require explicit guidance for interpreting and using them to inform those decisions about climate vulnerabilities and resilience. Moreover, many of these uncertainties overlap and interact. Recent work, for example, has shown the importance of assessing the uncertainties from multiple sources including: global model structure [Meehl et al., 2005; Knutti and Sedlacek, 2013]; internal climate variability [Deser et al., 2012; Kay et al., 2014]; climate downscaling methods [Gutmann et al., 2012; Mearns et al., 2013]; and hydrologic models [Addor et al., 2014; Vano et al., 2014; Mendoza et al., 2015]. Revealing, reducing, and representing these uncertainties is essential for defining the plausible quantitative climate change narratives required to inform water-resource decision-making. And to be useful, such quantitative narratives, or storylines, of climate change threats and hydrologic impacts must sample from the full range of uncertainties associated with all parts of the simulation chain, from global climate models with simulations of natural climate variability, through regional climate downscaling, and on to modeling of affected hydrologic processes and downstream water resources impacts. This talk will present part of the work underway now both to reveal and reduce some important uncertainties and to develop explicit guidance for future generation of quantitative hydroclimatic storylines. Topics will include: 1- model structural and parameter-set limitations of some methods widely used to quantify climate impacts to hydrologic processes [Gutmann et al., 2014; Newman et al., 2015]; 2- development and evaluation of new, spatially consistent, U.S. national-scale climate downscaling and hydrologic simulation capabilities directly relevant at the multiple scales of water-resource decision-making [Newman et al., 2015; Mizukami et al., 2015; Gutmann et al., 2016]; and 3- development and evaluation of advanced streamflow forecasting methods to reduce and represent integrated uncertainties in a tractable way [Wood et al., 2014; Wood et al., 2015]. A key focus will be areas where climatologic and hydrologic science is currently under-developed to inform decisions - or is perhaps wrongly scaled or misapplied in practice - indicating the need for additional fundamental science and interpretation.

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) project: a summary

NASA Astrophysics Data System (ADS)

Hawkins, Ed; Day, Jonny; Tietsche, Steffen

2016-04-01

Recent years have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. We describe a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual TimEscales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we provide a summary and update of the project's results which include: (1) quantifying the predictability of Arctic climate, especially sea ice; (2) the state-dependence of this predictability, finding that extreme years are potentially more predictable than neutral years; (3) analysing a spring 'predictability barrier' to skillful forecasts; (4) initial sea ice thickness information provides much of the skill for summer forecasts; (5) quantifying the sources of error growth and uncertainty in Arctic predictions. The dataset is now publicly available.

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

Hinzman, Larry D.; Bolton, William Robert; Young-Robertson, Jessica

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

Guess-Work and Reasonings on Centennial Evolution of Surface Air Temperature in Russia. Part IV: Towards Economic Estimations of Climate-Related Damages from the Bifurcation Analysis Viewpoint

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

The paper completes the cycle of the research devoted to the development of the experimental bifurcation analysis (not computer simulations) in order to answer the following questions: whether qualitative changes occur in the dynamics of local climate systems in a centennial timescale?; how to analyze such qualitative changes with daily resolution for local and regional space-scales?; how to establish one-to-one daily correspondence between the dynamics evolution and economic consequences for productions? To answer the questions, the unconventional conceptual model to describe the local climate dynamics was proposed and verified in the previous parts. That model (HDS-model) originates from the hysteresis regulator with double synchronization and has a variable structure due to competition between the amplitude quantization and the time quantization. The main advantage of the HDS-model is connected with the possibility to describe “internally” (on the basis of the self-regulation) the specific causal effects observed in the dynamics of local climate systems instead of “external” description of three states of the hysteresis behavior of climate systems (upper, lower and transient states). As a result, the evolution of the local climate dynamics is based on the bifurcation diagrams built by processing the data of meteorological observations, where the strange effects of the essential interannual daily variability of annual temperature variation are taken into account and explained. It opens the novel possibilities to analyze the local climate dynamics taking into account the observed resultant of all internal and external influences on each local climate system. In particular, the paper presents the viewpoint on how to estimate economic damages caused by climate-related hazards through the bifurcation analysis. That viewpoint includes the following ideas: practically each local climate system is characterized by its own time pattern of the natural qualitative changes in temperature dynamics over a century, so, any unified time window to determine the local climatic norms seems to be questionable; the temperature limits determined for climate-related technological hazards should be reasoned by the conditions of artificial human activity, but not by the climatic norms; the damages caused by such hazards can be approximately estimated in relation to the average annual profit of each production. Now, it becomes possible to estimate the minimal and maximal numbers of the specified hazards per year in order, first of all, to avoid unforeseen latent damages. Also, it becomes possible to make some useful relative estimation concerning damage and profit. We believe that the results presented in the cycle illustrate great practical competence of the current advances in the experimental bifurcation analysis. In particular, the developed QHS-analysis provides the novel prospects towards both how to adapt production to climatic changes and how to compensate negative technological impacts on environment.

Quantitative assessment of Vulnerability of Forest ecosystem to Climate Change in Korea

NASA Astrophysics Data System (ADS)

Byun, J.; Lee, W.; Choi, S.; Oh, S.; Climate Change Model Team

2011-12-01

The purpose of this study was to assess the vulnerability of forest ecosystem to climate change in Korea using outputs of vegetation models(HyTAG and MC1) and socio-ecological indicators. Also it suggested adaptation strategies in forest management through analysis of three vulnerability components: exposure, sensitivity and adaptive capacity. For the model simulation of past years(1971-2000), the climatic data was prepared by the Korea Meteorological Administration(KMA). In addition, for the future simulation, the Fifth-Generation NCAR/Penn State Mesoscale Model(MM5) coupling with atmosphere-ocean circulation model(ECHO-G) provide the future climatic data under the A1B scenarios. HyTAG (Hydrological and Thermal Analogy Groups), korean model of forest distribution on a regional-scale, could show extent of sensitivity and adaptive capacity in connection with changing frequency and changing direction of vegetation. MC1 model could provide variation and direction of NPP(Net Primary Production) and SCS(Soil Carbon Storage). In addition, the sensitivity and adaptation capacity were evaluated for each. Besides indicators from models, many other indicators such as financial affairs and number of officers were included in the vulnerability components. As a result of the vulnerability assessment, south western part and Je-ju island of Korea had relatively high vulnerability. This finding is considered to come from a distinctively adaptative capacity. Using these results, we could propose actions against climate change and develop decision making systems on forest management.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Climate Hazard Assessment for Stakeholder Adaptation Planning in New York City

NASA Technical Reports Server (NTRS)

Horton, Radley M.; Gornitz, Vivien; Bader, Daniel A.; Ruane, Alex C.; Goldberg, Richard; Rosenzweig, Cynthia

2011-01-01

This paper describes a time-sensitive approach to climate change projections, developed as part of New York City's climate change adaptation process, that has provided decision support to stakeholders from 40 agencies, regional planning associations, and private companies. The approach optimizes production of projections given constraints faced by decision makers as they incorporate climate change into long-term planning and policy. New York City stakeholders, who are well-versed in risk management, helped pre-select the climate variables most likely to impact urban infrastructure, and requested a projection range rather than a single 'most likely' outcome. The climate projections approach is transferable to other regions and consistent with broader efforts to provide climate services, including impact, vulnerability, and adaptation information. The approach uses 16 Global Climate Models (GCMs) and three emissions scenarios to calculate monthly change factors based on 30-year average future time slices relative to a 30- year model baseline. Projecting these model mean changes onto observed station data for New York City yields dramatic changes in the frequency of extreme events such as coastal flooding and dangerous heat events. Based on these methods, the current 1-in-10 year coastal flood is projected to occur more than once every 3 years by the end of the century, and heat events are projected to approximately triple in frequency. These frequency changes are of sufficient magnitude to merit consideration in long-term adaptation planning, even though the precise changes in extreme event frequency are highly uncertain

Village-level supply reliability of surface water irrigation in rural China: effects of climate change

NASA Astrophysics Data System (ADS)

Li, Yanrong; Wang, Jinxia

2018-06-01

Surface water, as the largest part of water resources, plays an important role on China's agricultural production and food security. And surface water is vulnerable to climate change. This paper aims to examine the status of the supply reliability of surface water irrigation, and discusses how it is affected by climate change in rural China. The field data we used in this study was collected from a nine-province field survey during 2012 and 2013. Climate data are offered by China's National Meteorological Information Center which contains temperature and precipitation in the past 30 years. A Tobit model (or censored regression model) was used to estimate the influence of climate change on supply reliability of surface water irrigation. Descriptive results showed that, surface water supply reliability was 74 % in the past 3 years. Econometric results revealed that climate variables significantly influenced the supply reliability of surface water irrigation. Specifically, temperature is negatively related with the supply reliability of surface water irrigation; but precipitation positively influences the supply reliability of surface water irrigation. Besides, climate influence differs by seasons. In a word, this paper improves our understanding of the impact of climate change on agriculture irrigation and water supply reliability in the micro scale, and provides a scientific basis for relevant policy making.

Climate matching as a tool for predicting potential North American spread of Brown Treesnakes

USGS Publications Warehouse

Rodda, Gordon H.; Reed, Robert N.; Jarnevich, Catherine S.; Witmer, G.W.; Pitt, W. C.; Fagerstone, K.A.

2007-01-01

Climate matching identifies extralimital destinations that could be colonized by a potential invasive species on the basis of similarity to climates found in the species’ native range. Climate is a proxy for the factors that determine whether a population will reproduce enough to offset mortality. Previous climate matching models (e.g., Genetic Algorithm for Rule-set Prediction [GARP]) for brown treesnakes (Boiga irregularis) were unsatisfactory, perhaps because the models failed to allow different combinations of climate attributes to influence a species’ range limits in different parts of the range. Therefore, we explored the climate space described by bivariate parameters of native range temperature and rainfall, allowing up to two months of aestivation in the warmer portions of the range, or four months of hibernation in temperate climes. We found colonization area to be minimally sensitive to assumptions regarding hibernation temperature thresholds. Although brown treesnakes appear to be limited by dry weather in the interior of Australia, aridity rarely limits potential distribution in most of the world. Potential colonization area in North America is limited primarily by cold. Climatically suitable portions of the United States (US) mainland include the Central Valley of California, mesic patches in the Southwest, and the southeastern coastal plain from Texas to Virginia.

Streamflow Bias Correction for Climate Change Impact Studies: Harmless Correction or Wrecking Ball?

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chegwidden, O.

2017-12-01

Projections of the hydrologic impacts of climate change rely on a modeling chain that includes estimates of future greenhouse gas emissions, global climate models, and hydrologic models. The resulting streamflow time series are used in turn as input to impact studies. While these flows can sometimes be used directly in these impact studies, many applications require additional post-processing to remove model errors. Water resources models and regulation studies are a prime example of this type of application. These models rely on specific flows and reservoir levels to trigger reservoir releases and diversions and do not function well if the unregulated streamflow inputs are significantly biased in time and/or amount. This post-processing step is typically referred to as bias-correction, even though this step corrects not just the mean but the entire distribution of flows. Various quantile-mapping approaches have been developed that adjust the modeled flows to match a reference distribution for some historic period. Simulations of future flows are then post-processed using this same mapping to remove hydrologic model errors. These streamflow bias-correction methods have received far less scrutiny than the downscaling and bias-correction methods that are used for climate model output, mostly because they are less widely used. However, some of these methods introduce large artifacts in the resulting flow series, in some cases severely distorting the climate change signal that is present in future flows. In this presentation, we discuss our experience with streamflow bias-correction methods as part of a climate change impact study in the Columbia River basin in the Pacific Northwest region of the United States. To support this discussion, we present a novel way to assess whether a streamflow bias-correction method is merely a harmless correction or is more akin to taking a wrecking ball to the climate change signal.

Chapter 1. Impacts of the oceans on climate change.

PubMed

Reid, Philip C; Fischer, Astrid C; Lewis-Brown, Emily; Meredith, Michael P; Sparrow, Mike; Andersson, Andreas J; Antia, Avan; Bates, Nicholas R; Bathmann, Ulrich; Beaugrand, Gregory; Brix, Holger; Dye, Stephen; Edwards, Martin; Furevik, Tore; Gangstø, Reidun; Hátún, Hjálmar; Hopcroft, Russell R; Kendall, Mike; Kasten, Sabine; Keeling, Ralph; Le Quéré, Corinne; Mackenzie, Fred T; Malin, Gill; Mauritzen, Cecilie; Olafsson, Jón; Paull, Charlie; Rignot, Eric; Shimada, Koji; Vogt, Meike; Wallace, Craig; Wang, Zhaomin; Washington, Richard

2009-01-01

The oceans play a key role in climate regulation especially in part buffering (neutralising) the effects of increasing levels of greenhouse gases in the atmosphere and rising global temperatures. This chapter examines how the regulatory processes performed by the oceans alter as a response to climate change and assesses the extent to which positive feedbacks from the ocean may exacerbate climate change. There is clear evidence for rapid change in the oceans. As the main heat store for the world there has been an accelerating change in sea temperatures over the last few decades, which has contributed to rising sea-level. The oceans are also the main store of carbon dioxide (CO2), and are estimated to have taken up approximately 40% of anthropogenic-sourced CO2 from the atmosphere since the beginning of the industrial revolution. A proportion of the carbon uptake is exported via the four ocean 'carbon pumps' (Solubility, Biological, Continental Shelf and Carbonate Counter) to the deep ocean reservoir. Increases in sea temperature and changing planktonic systems and ocean currents may lead to a reduction in the uptake of CO2 by the ocean; some evidence suggests a suppression of parts of the marine carbon sink is already underway. While the oceans have buffered climate change through the uptake of CO2 produced by fossil fuel burning this has already had an impact on ocean chemistry through ocean acidification and will continue to do so. Feedbacks to climate change from acidification may result from expected impacts on marine organisms (especially corals and calcareous plankton), ecosystems and biogeochemical cycles. The polar regions of the world are showing the most rapid responses to climate change. As a result of a strong ice-ocean influence, small changes in temperature, salinity and ice cover may trigger large and sudden changes in regional climate with potential downstream feedbacks to the climate of the rest of the world. A warming Arctic Ocean may lead to further releases of the potent greenhouse gas methane from hydrates and permafrost. The Southern Ocean plays a critical role in driving, modifying and regulating global climate change via the carbon cycle and through its impact on adjacent Antarctica. The Antarctic Peninsula has shown some of the most rapid rises in atmospheric and oceanic temperature in the world, with an associated retreat of the majority of glaciers. Parts of the West Antarctic ice sheet are deflating rapidly, very likely due to a change in the flux of oceanic heat to the undersides of the floating ice shelves. The final section on modelling feedbacks from the ocean to climate change identifies limitations and priorities for model development and associated observations. Considering the importance of the oceans to climate change and our limited understanding of climate-related ocean processes, our ability to measure the changes that are taking place are conspicuously inadequate. The chapter highlights the need for a comprehensive, adequately funded and globally extensive ocean observing system to be implemented and sustained as a high priority. Unless feedbacks from the oceans to climate change are adequately included in climate change models, it is possible that the mitigation actions needed to stabilise CO2 and limit temperature rise over the next century will be underestimated.

Extreme environments select for reproductive assurance: evidence from evening primroses (Oenothera).

PubMed

Evans, Margaret E K; Hearn, David J; Theiss, Kathryn E; Cranston, Karen; Holsinger, Kent E; Donoghue, Michael J

2011-07-01

Competing evolutionary forces shape plant breeding systems (e.g. inbreeding depression, reproductive assurance). Which of these forces prevails in a given population or species is predicted to depend upon such factors as life history, ecological conditions, and geographical context. Here, we examined two such predictions: that self-compatibility should be associated with the annual life history or extreme climatic conditions. We analyzed data from a clade of plants remarkable for variation in breeding system, life history and climatic conditions (Oenothera, sections Anogra and Kleinia, Onagraceae). We used a phylogenetic comparative approach and Bayesian or hybrid Bayesian tests to account for phylogenetic uncertainty. Geographic information system (GIS)-based climate data and ecological niche modeling allowed us to quantify climatic conditions. Breeding system and reproductive life span are not correlated in Anogra and Kleinia. Instead, self-compatibility is associated with the extremes of temperature in the coldest part of the year and precipitation in the driest part of the year. In the 60 yr since this pattern was anticipated, this is the first demonstration of a relationship between the evolution of self-compatibility and climatic extremes. We discuss possible explanations for this pattern and possible implications with respect to anthropogenic climate change. © 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

A variant of the anomaly initialisation approach for global climate forecast models

NASA Astrophysics Data System (ADS)

Volpi, Danila; Guemas, Virginie; Doblas-Reyes, Francisco; Hawkins, Ed; Nichols, Nancy; Carrassi, Alberto

2014-05-01

This work presents a refined method of anomaly initialisation (AI) applied to the ocean and sea ice components of the global climate forecast model EC-Earth, with the following particularities: - the use of a weight to the anomalies, in order to avoid the risk of introducing too big anomalies recorded in the observed state, whose amplitude does not fit the range of the internal variability generated by the model. - the AI of the temperature and density ocean state variables instead of the temperature and salinity. Results show that the use of such refinements improve the skill over the Arctic region, part of the North and South Atlantic, part of the North and South Pacific and the Mediterranean Sea. In the Tropical Pacific the full field initialised experiment performs better. This is probably due to a displacement of the observed anomalies caused by the use of the AI technique. Furthermore, preliminary results of an anomaly nudging experiment are discussed.

A Bayesian model for quantifying the change in mortality associated with future ozone exposures under climate change.

PubMed

Alexeeff, Stacey E; Pfister, Gabriele G; Nychka, Doug

2016-03-01

Climate change is expected to have many impacts on the environment, including changes in ozone concentrations at the surface level. A key public health concern is the potential increase in ozone-related summertime mortality if surface ozone concentrations rise in response to climate change. Although ozone formation depends partly on summertime weather, which exhibits considerable inter-annual variability, previous health impact studies have not incorporated the variability of ozone into their prediction models. A major source of uncertainty in the health impacts is the variability of the modeled ozone concentrations. We propose a Bayesian model and Monte Carlo estimation method for quantifying health effects of future ozone. An advantage of this approach is that we include the uncertainty in both the health effect association and the modeled ozone concentrations. Using our proposed approach, we quantify the expected change in ozone-related summertime mortality in the contiguous United States between 2000 and 2050 under a changing climate. The mortality estimates show regional patterns in the expected degree of impact. We also illustrate the results when using a common technique in previous work that averages ozone to reduce the size of the data, and contrast these findings with our own. Our analysis yields more realistic inferences, providing clearer interpretation for decision making regarding the impacts of climate change. © 2015, The International Biometric Society.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

AGCM Biases in Evaporation Regime: Impacts on Soil Moisture Memory and Land-Atmosphere Feedback

NASA Technical Reports Server (NTRS)

Mahanama, Sarith P. P.; Koster, Randal D.

2005-01-01

Because precipitation and net radiation in an atmospheric general circulation model (AGCM) are typically biased relative to observations, the simulated evaporative regime of a region may be biased, with consequent negative effects on the AGCM s ability to translate an initialized soil moisture anomaly into an improved seasonal prediction. These potential problems are investigated through extensive offline analyses with the Mosaic land surface model (LSM). We first forced the LSM globally with a 15-year observations-based dataset. We then repeated the simulation after imposing a representative set of GCM climate biases onto the forcings - the observational forcings were scaled so that their mean seasonal cycles matched those simulated by the NSIPP-1 (NASA Global Modeling and Assimilation Office) AGCM over the same period-The AGCM s climate biases do indeed lead to significant biases in evaporative regime in certain regions, with the expected impacts on soil moisture memory timescales. Furthermore, the offline simulations suggest that the biased forcing in the AGCM should contribute to overestimated feedback in certain parts of North America - parts already identified in previous studies as having excessive feedback. The present study thus supports the notion that the reduction of climate biases in the AGCM will lead to more appropriate translations of soil moisture initialization into seasonal prediction skill.

Climate change likely to favor shift toward warmer climate states of the Pliocene and Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.

2017-12-01

As the world warms due to rising greenhouse gas concentrations, the climate system is moving toward a state without precedent in the historical record. Various past climate states have been proposed as potential analogues or model systems for the coming decades, including the early to middle Holocene, the last interglacial, the middle Pliocene, and the early Eocene. However, until now, such comparisons have been qualitative. To compare these time periods to the projected climate states for the 21st and 22nd centuries, we conduct a climate similarity analysis using the standardized Euclidean distance metric (SED) and seasonal means of surface air temperature and precipitation. We make this future-to-past comparison using 30-year mean climatologies, for every decade between 2020 and 2280 AD (27 total comparisons). The list of past earth system states includes the historical period (1940-1970 AD), a pre-industrial control (ca. 1850), the middle Holocene (ca. 6 ka), the last glacial maximum (ca. 21 ka), the last interglacial (ca. 125 ka), the middle Pliocene (ca. 3 Ma), and the early Eocene (ca. 50-55 Ma). To reduce uncertainties resulting from choice of earth system model, analyses are based on simulations from three earth system models (HadCM, CCSM, NASA/GISS Model-E), using in part experiments from PMIP2, PMIP3/CMIP5, EoMIP, and PlioMIP. Results are presented for two representative concentration pathways (RCP's 4.5, 8.5). By 2050 AD, the most common past climate analogue is sourced from the Pliocene for RCP 8.5, while by 2190 AD, the Eocene becomes the source of the most common past climate analogue. For RCP 4.5, in which radiative forcings stabilize this century, the Pliocene becomes the most important past climate analogue by 2100 AD. Low latitude climates are the first to most closely resemble these past earth warm periods. The mid-latitudes then follow this pattern by the end of the 22nd century. Although no past state of the earth system is a perfect analogue for the Anthropocene, these analyses clarify the similarities between the expected climates of the future and the geological climates of the past.

The impact of climate change on photovoltaic power generation in Europe

PubMed Central

Jerez, Sonia; Tobin, Isabelle; Vautard, Robert; Montávez, Juan Pedro; López-Romero, Jose María; Thais, Françoise; Bartok, Blanka; Christensen, Ole Bøssing; Colette, Augustin; Déqué, Michel; Nikulin, Grigory; Kotlarski, Sven; van Meijgaard, Erik; Teichmann, Claas; Wild, Martin

2015-01-01

Ambitious climate change mitigation plans call for a significant increase in the use of renewables, which could, however, make the supply system more vulnerable to climate variability and changes. Here we evaluate climate change impacts on solar photovoltaic (PV) power in Europe using the recent EURO-CORDEX ensemble of high-resolution climate projections together with a PV power production model and assuming a well-developed European PV power fleet. Results indicate that the alteration of solar PV supply by the end of this century compared with the estimations made under current climate conditions should be in the range (−14%;+2%), with the largest decreases in Northern countries. Temporal stability of power generation does not appear as strongly affected in future climate scenarios either, even showing a slight positive trend in Southern countries. Therefore, despite small decreases in production expected in some parts of Europe, climate change is unlikely to threaten the European PV sector. PMID:26658608

Responses of runoff to historical and future climate variability over China

NASA Astrophysics Data System (ADS)

Wu, Chuanhao; Hu, Bill X.; Huang, Guoru; Wang, Peng; Xu, Kai

2018-03-01

China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960-2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from -2.2 to -0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960-2008, the climate contribution to R ranges from -2.4 to 3.6 % yr-1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071-2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071-2100, respectively (relative to the baseline 1971-2000).

Exploring the Causes of Mid-Holocene Drought in the Rocky Mountains Using Hydrologic Forward Models

NASA Astrophysics Data System (ADS)

Meador, E.; Morrill, C.

2017-12-01

We present a quantitative model-data comparison for mid-Holocene (6 ka) lake levels in the Rocky Mountains, with the goals of assessing the skill coupled climate models and hydrologic forward models in simulating climate change and improving our understanding of the factors causing past changes in water resources. The mid-Holocene climate in this area may in some ways be similar to expected future climate, thus improved understanding of the factors causing past changes in water resources have the potential to aid in the process of water allocation for large areas that share a relatively small water source. This project focuses on Little Windy Hill Pond in the Medicine Bow Forest in the Rocky Mountains in southern Wyoming. We first calibrated the Variable Infiltration Capacity (VIC) catchment hydrologic model and the one-dimensional Hostetler Bartlein lake energy-balance model to modern observations, using U.S. Geological Survey stream discharge data and Snow Telemetry (SNOTEL) data to ensure appropriate selection of model parameters. Once the models were calibrated to modern conditions, we forced them with output from eight mid-Holocene coupled climate model simulations completed as part of the Coupled Model Intercomparison Project, Phase 5. Forcing from nearly all of the CMIP5 models generates intense, short-lived droughts for the mid-Holocene that are more severe than any we modeled for the past six decades. The severity of the mid-Holocene droughts could be sufficient, depending on sediment processes in the lake, to account for low lake levels recorded by loss-on-ignition in sediment cores. Our preliminary analysis of model output indicates that the combined effects of decreased snowmelt runoff and increased summer lake evaporation cause low mid-Holocene lake levels. These factors are also expected to be important in the future under anthropogenic climate change.

Providing a Scientific Foundation in Climate Studies for Non-Science Majors

NASA Astrophysics Data System (ADS)

Brey, J. A.; Geer, I. W.; Moran, J. M.; Weinbeck, R. S.; Mills, E. W.; Lambert, J.; Blair, B. A.; Hopkins, E. J.; O'Neill, K. L.; Hyre, H. R.; Nugnes, K. A.; Moses, M. N.

2010-12-01

Climate change has become a politically charged topic, creating the necessity for a scientifically literate population. Therefore, the American Meteorological Society (AMS), in partnership with NASA, has produced an introductory level, climate science course that engages students, allows for course flexibility, and boosts scientific knowledge about climate. This course shares NASA’s goal of observing, understanding, and modeling the Earth system, to discover how it is changing, to better predict change, and to understand the consequences for life. In Spring 2010, AMS Climate Studies was piloted to determine the most effective method to foster an understanding of some of the more difficult concepts of climate science. This study was offered as part of the NASA grant. This presentation will report the results of that study. Faculty and students from fourteen colleges and universities throughout the country evaluated the course using pre- and post-test questions, which included multiple choice and short answer questions, weekly course content evaluations, and an extensive post-course evaluation. The large majority of participating teachers rated the overall course, scientific content, internet delivery, and study materials as ‘good’, the most positive response available. Feedback from faculty members as well as suggestions from NASA reviewers were used to enhance the final version of the textbook and Investigations Manual for the Fall 2010 academic semester. Following the proven course work of AMS Weather and AMS Ocean Studies, AMS Climate Studies is a turnkey package utilizing both printed and online materials. It covers topics such as the water in Earth’s climate system, paleoclimates, along with climate change and public policy. The Investigations include 30 complimentary lab-style activities including the Conceptual Energy Model, which explores the flow of energy from space to Earth. Additionally, the course website features Current Climate Studies where students use real-world data and up-to-the-minute information regarding recent climate events. AMS Climate Studies can be presented in traditional, online, or blended environments, as best suites the instructor, student, and institution. By exploring the Earth’s climate as part of a larger Earth system, AMS Climate Studies will serve as a great primer in preparing students to become responsible, scientifically-literate participants in discussions of climate science and climate change. It maintains a strong focus on the fundamental science while still addressing many of the societal impacts that draw the attention of today’s students. AMS Climate Studies is available for full implementation at institutions nationwide.

Effect of Temperature on Acoustic Evaluation of Standing trees and logs: Part 1-Laboratory investigation

Treesearch

Shan Gao; Xiping Wang; Lihai Wang; R. Bruce. Allison

2012-01-01

The goals of this study were to investigate the effect of environment temperature on acoustic velocity of standing trees and green logs and to develop workable models for compensating temperature differences as acoustic measurements are performed in different climates and seasons. The objective of Part 1 was to investigate interactive effects of temperature and...

Predicting Factors of Perceived Organizational Support by Full-Time and Part-Time Community College Faculty as Relates to Student Retention Rates

ERIC Educational Resources Information Center

Nichols, Sarah K.

2012-01-01

Student retention is socially, politically, and financially important to educational institutions. This quantitative study explored the gap in research regarding the relationship between employment of part-time in lieu of full-time faculty and student retention. The campus climate exchange model (CCEM), served as the conceptual framework in this…

Research in Satellite-Fiber Network Interoperability

NASA Technical Reports Server (NTRS)

Edelson, Burt

1997-01-01

This four part report evaluated the performance of high data rate transmission links using the ACTS satellite, and to provide a preparatory test framework for two of the space science applications that have been approved for tests and demonstrations as part of the overall ACTS program. The test plan will provide guidance and information necessary to find the optimal values of the transmission parameters and then apply these parameters to specific applications. The first part will focus on the satellite-to-earth link. The second part is a set of tests to study the performance of ATM on the ACTS channel. The third and fourth parts of the test plan will cover the space science applications, Global Climate Modeling and Keck Telescope Acquisition Modeling and Control.

[Climatic suitability of citrus in subtropical China].

PubMed

Duan, Hai-Lai; Qian, Huai-Sui; Li, Ming-Xia; Du, Yao-Dong

2010-08-01

By applying the theories of ecological suitability and the methods of fuzzy mathematics, this paper established a climatic suitability model for citrus, calculated and evaluated the climatic suitability and its spatiotemporal differences for citrus production in subtropical China, and analyzed the climatic suitability of citrus at its different growth stages and the mean climatic suitability of citrus in different regions of subtropical China. The results showed that the citrus in subtropical China had a lower climatic suitability and a higher risk at its flower bud differentiation stage, budding stage, and fruit maturity stage, but a higher climatic suitability and a lower risk at other growth stages. Cold damage and summer drought were the key issues affecting the citrus production in subtropical China. The citrus temperature suitability represented a latitudinal zonal pattern, i. e., decreased with increasing latitude; its precipitation suitability was high in the line of "Sheyang-Napo", medium in the southeast of the line, low in the northwest of the line, and non in high mountainous area; while the sunlight suitability was in line with the actual duration of sunshine, namely, higher in high-latitude areas than in low-latitude areas, and higher in high-altitude areas than in plain areas. Limited by temperature factor, the climatic suitability was in accordance with temperature suitability, i. e., south parts had a higher suitability than north parts, basically representing latitudinal zonal pattern. From the analysis of the inter-annual changes of citrus climatic suitability, it could be seen that the citrus climatic suitability in subtropical China was decreasing, and had obvious regional differences, suggesting that climate change could bring about the changes in the regions suitable for citrus production and in the key stages of citrus growth.

Satellite-based climate data records of surface solar radiation from the CM SAF

NASA Astrophysics Data System (ADS)

Trentmann, Jörg; Cremer, Roswitha; Kothe, Steffen; Müller, Richard; Pfeifroth, Uwe

2017-04-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth's energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF is freely available via www.cmsaf.eu. Here we present the regional and the global climate data records of surface solar radiation from the CM SAF. The regional climate data record SARAH (Surface Solar Radiation Dataset - Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002) is based on observations from the series of Meteosat satellites. SARAH provides 30-min, daily- and monthly-averaged data of the effective cloud albedo, the solar irradiance (incl. spectral information), the direct solar radiation (horizontal and normal), and the sunshine duration from 1983 to 2015 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05° allowing for detailed regional studies. The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002) is based on observations from the series of AVHRR satellite instruments. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from 1982 to 2015 with a spatial resolution of 0.25°. In addition to the solar surface radiation also the longwave surface radiation as well as surface albedo and numerous cloud properties are provided in CLARA. Here we provide an overview of the climate data records of the surface solar radiation and present the results of the quality assessment of both climate data records against available surface reference observations, e.g., from the BSRN and the GEBA data archive.

Belowground Carbon Cycling Processes at the Molecular Scale: An EMSL Science Theme Advisory Panel Workshop

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

Hess, Nancy J.; Brown, Gordon E.; Plata, Charity

2014-02-21

As part of the Belowground Carbon Cycling Processes at the Molecular Scale workshop, an EMSL Science Theme Advisory Panel meeting held in February 2013, attendees discussed critical biogeochemical processes that regulate carbon cycling in soil. The meeting attendees determined that as a national scientific user facility, EMSL can provide the tools and expertise needed to elucidate the molecular foundation that underlies mechanistic descriptions of biogeochemical processes that control carbon allocation and fluxes at the terrestrial/atmospheric interface in landscape and regional climate models. Consequently, the workshop's goal was to identify the science gaps that hinder either development of mechanistic description ofmore » critical processes or their accurate representation in climate models. In part, this report offers recommendations for future EMSL activities in this research area. The workshop was co-chaired by Dr. Nancy Hess (EMSL) and Dr. Gordon Brown (Stanford University).« less

OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Griffies, Stephen M.; Danabasoglu, Gokhan; Durack, Paul J.; Adcroft, Alistair J.; Balaji, V.; Böning, Claus W.; Chassignet, Eric P.; Curchitser, Enrique; Deshayes, Julie; Drange, Helge; Fox-Kemper, Baylor; Gleckler, Peter J.; Gregory, Jonathan M.; Haak, Helmuth; Hallberg, Robert W.; Heimbach, Patrick; Hewitt, Helene T.; Holland, David M.; Ilyina, Tatiana; Jungclaus, Johann H.; Komuro, Yoshiki; Krasting, John P.; Large, William G.; Marsland, Simon J.; Masina, Simona; McDougall, Trevor J.; Nurser, A. J. George; Orr, James C.; Pirani, Anna; Qiao, Fangli; Stouffer, Ronald J.; Taylor, Karl E.; Treguier, Anne Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valdivieso, Maria; Wang, Qiang; Winton, Michael; Yeager, Stephen G.

2016-09-01

The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

Simulated hydrologic response to projected changes in precipitation and temperature in the Congo River basin

NASA Astrophysics Data System (ADS)

Aloysius, Noel; Saiers, James

2017-08-01

Despite their global significance, the impacts of climate change on water resources and associated ecosystem services in the Congo River basin (CRB) have been understudied. Of particular need for decision makers is the availability of spatial and temporal variability of runoff projections. Here, with the aid of a spatially explicit hydrological model forced with precipitation and temperature projections from 25 global climate models (GCMs) under two greenhouse gas emission scenarios, we explore the variability in modeled runoff in the near future (2016-2035) and mid-century (2046-2065). We find that total runoff from the CRB is projected to increase by 5 % [-9 %; 20 %] (mean - min and max - across model ensembles) over the next two decades and by 7 % [-12 %; 24 %] by mid-century. Projected changes in runoff from subwatersheds distributed within the CRB vary in magnitude and sign. Over the equatorial region and in parts of northern and southwestern CRB, most models project an overall increase in precipitation and, subsequently, runoff. A simulated decrease in precipitation leads to a decline in runoff from headwater regions located in the northeastern and southeastern CRB. Climate model selection plays an important role in future projections for both magnitude and direction of change. The multimodel ensemble approach reveals that precipitation and runoff changes under business-as-usual and avoided greenhouse gas emission scenarios (RCP8.5 vs. RCP4.5) are relatively similar in the near term but deviate in the midterm, which underscores the need for rapid action on climate change adaptation. Our assessment demonstrates the need to include uncertainties in climate model and emission scenario selection during decision-making processes related to climate change mitigation and adaptation.

Understanding the tropical warm temperature bias simulated by climate models

NASA Astrophysics Data System (ADS)

Brient, Florent; Schneider, Tapio

2017-04-01

The state-of-the-art coupled general circulation models have difficulties in representing the observed spatial pattern of surface tempertaure. A majority of them suffers a warm bias in the tropical subsiding regions located over the eastern parts of oceans. These regions are usually covered by low-level clouds scattered from stratus along the coasts to more vertically developed shallow cumulus farther from them. Models usually fail to represent accurately this transition. Here we investigate physical drivers of this warm bias in CMIP5 models through a near-surface energy budget perspective. We show that overestimated solar insolation due to a lack of stratocumulus mostly explains the warm bias. This bias also arises partly from inter-model differences in surface fluxes that could be traced to differences in near-surface relative humidity and air-sea temperature gradient. We investigate the role of the atmosphere in driving surface biases by comparing historical and atmopsheric (AMIP) experiments. We show that some differences in boundary-layer characteristics, mostly those related to cloud fraction and relative humidity, are already present in AMIP experiments and may be the drivers of coupled biases. This gives insights in how models can be improved for better simulations of the tropical climate.

Water-Energy Nexus Challenges & Opportunities in the Arabian Peninsula under Climate Change

NASA Astrophysics Data System (ADS)

Flores-Lopez, F.; Yates, D. N.; Galaitsi, S.; Binnington, T.; Dougherty, W.; Vinnaccia, M.; Glavan, J. C.

2016-12-01

Demand for water in the GCC countries relies mainly on fossil groundwater resources and desalination. Satisfying water demand requires a great deal of energy as it treats and moves water along the supply chain from sources, through treatment processes, and ultimately to the consumer. Hence, there is an inherent connection between water and energy and with climate change, the links between water and energy are expected to become even stronger. As part of AGEDI's Local, National, and Regional Climate Change Programme, a study of the water-energy nexus of the countries in the Arabian Peninsula was implemented. For water, WEAP models both water demand - and its main drivers - and water supply, simulating policies, priorities and preferences. For energy, LEAP models both energy supply and demand, and is able to capture the impacts of low carbon development strategies. A coupled WEAP-LEAP model was then used to evaluate the future performance of the energy-water system under climate change and policy scenarios. The coupled models required detailed data, which were obtained through literature reviews and consultations with key stakeholders in the region. As part of this process, the outputs of both models were validated for historic periods using existing data The models examined 5 policy scenarios of different futures of resource management to the year 2060. A future under current management practices with current climate and a climate projection based on the RCP8.5; a High Efficiency scenario where each country gradually implements policies to reduce the consumption of water and electricity; a Natural Resource Protection scenario with resource efficiency and phasing out of groundwater extraction and drastic reduction of fossil fuel usage in favor of solar; and an Integrated Policy scenario that integrates the prior two policy scenarios Water demands can mostly be met in any scenario through supply combinations of groundwater, desalination and wastewater reuse, with some regional fossil groundwater basins draw to extinction by 2060. While the analysis includes both demand and supply oriented scenarios, the results of the analysis strongly suggest that the region will need to simultaneously purse demand and supply side policies to achieve more sustainable uses of water and energy into the second half of the 21st century.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2013-01-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model.

PubMed

King, David A; Bachelet, Dominique M; Symstad, Amy J

2013-12-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine-prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Climate change and fire effects on a prairie–woodland ecotone: projecting species range shifts with a dynamic global vegetation model

PubMed Central

King, David A; Bachelet, Dominique M; Symstad, Amy J

2013-01-01

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects. PMID:24455138

A unified approach for process-based hydrologic modeling: Part 2. Model implementation and case studies

USDA-ARS?s Scientific Manuscript database

Understanding and prediction of snowmelt-generated streamflow at sub-daily time scales is important for reservoir scheduling and climate change characterization. This is particularly important in the Western U.S. where over 50% of water supply is provided by snowmelt during the melting period. Previ...

Integrated Models of School-Based Prevention: Logic and Theory

ERIC Educational Resources Information Center

Domitrovich, Celene E.; Bradshaw, Catherine P.; Greenberg, Mark T.; Embry, Dennis; Poduska, Jeanne M.; Ialongo, Nicholas S.

2010-01-01

School-based prevention programs can positively impact a range of social, emotional, and behavioral outcomes. Yet the current climate of accountability pressures schools to restrict activities that are not perceived as part of the core curriculum. Building on models from public health and prevention science, we describe an integrated approach to…

Signs of the Land: Reaching Arctic Communities Facing Climate Change

NASA Astrophysics Data System (ADS)

Sparrow, E. B.; Chase, M. J.; Demientieff, S.; Pfirman, S. L.; Brunacini, J.

2014-12-01

In July 2014, a diverse and intergenerational group of Alaskan Natives came together on Howard Luke's Galee'ya Camp by the Tanana River in Fairbanks, Alaska to talk about climate change and it's impacts on local communities. Over a period of four days, the Signs of the Land Climate Change Camp wove together traditional knowledge, local observations, Native language, and climate science through a mix of storytelling, presentations, dialogue, and hands-on, community-building activities. This camp adapted the model developed several years ago under the Association for Interior Native Educators (AINE)'s Elder Academy. Part of the Polar Learning and Responding Climate Change Education Partnership, the Signs of the Land Climate Change Camp was developed and conducted collaboratively with multiple partners to test a model for engaging indigenous communities in the co-production of climate change knowledge, communication tools, and solutions-building. Native Alaskans have strong subsistence and cultural connections to the land and its resources, and, in addition to being keen observers of their environment, have a long history of adapting to changing conditions. Participants in the camp included Elders, classroom teachers, local resource managers and planners, community members, and climate scientists. Based on their experiences during the camp, participants designed individualized outreach plans for bringing culturally-responsive climate learning to their communities and classrooms throughout the upcoming year. Plans included small group discussions, student projects, teacher training, and conference presentations.

Stochastic integrated assessment of climate tipping points indicates the need for strict climate policy

NASA Astrophysics Data System (ADS)

Lontzek, Thomas S.; Cai, Yongyang; Judd, Kenneth L.; Lenton, Timothy M.

2015-05-01

Perhaps the most `dangerous’ aspect of future climate change is the possibility that human activities will push parts of the climate system past tipping points, leading to irreversible impacts. The likelihood of such large-scale singular events is expected to increase with global warming, but is fundamentally uncertain. A key question is how should the uncertainty surrounding tipping events affect climate policy? We address this using a stochastic integrated assessment model, based on the widely used deterministic DICE model. The temperature-dependent likelihood of tipping is calibrated using expert opinions, which we find to be internally consistent. The irreversible impacts of tipping events are assumed to accumulate steadily over time (rather than instantaneously), consistent with scientific understanding. Even with conservative assumptions about the rate and impacts of a stochastic tipping event, today’s optimal carbon tax is increased by ~50%. For a plausibly rapid, high-impact tipping event, today’s optimal carbon tax is increased by >200%. The additional carbon tax to delay climate tipping grows at only about half the rate of the baseline carbon tax. This implies that the effective discount rate for the costs of stochastic climate tipping is much lower than the discount rate for deterministic climate damages. Our results support recent suggestions that the costs of carbon emission used to inform policy are being underestimated, and that uncertain future climate damages should be discounted at a low rate.

Using prior information to separate the temperature response to greenhouse gas forcing from that of aerosols - Estimating the transient climate response

NASA Astrophysics Data System (ADS)

Schurer, Andrew; Hegerl, Gabriele

2016-04-01

The evaluation of the transient climate response (TCR) is of critical importance to policy makers as it can be used to calculate a simple estimate of the expected warming given predicted greenhouse gas emissions. Previous studies using optimal detection techniques have been able to estimate a TCR value from the historic record using simulations from some of the models which took part in the Coupled Model Intercomparison Project Phase 5 (CMIP5) but have found that others give unconstrained results. At least partly this is due to degeneracy between the greenhouse gas and aerosol signals which makes separation of the temperature response to these forcings problematic. Here we re-visit this important topic by using an adapted optimal detection analysis within a Bayesian framework. We account for observational uncertainty by the use of an ensemble of instrumental observations, and model uncertainty by combining the results from several different models. This framework allows the use of prior information which is found to help separate the response to the different forcings leading to a more constrained estimate of TCR.

A Brazilian Vulnerability Index Towards Natural Disasters and Climatic Change - Flashfloods and Landslides.

NASA Astrophysics Data System (ADS)

Debortoli, N. S.; Camarinha, P. I., Sr.; Marengo, J. A.; Rodrigues, R.

2015-12-01

There are some evidences that hydrological climate extremes events have become more frequent an intense in the last decades due to climatic change. In Brazil, flashfloods and landslides were responsible for 74% of the deaths related to natural disasters in 1991-2010 period. In this sense, climate change could be considered a threat which can further increase these numbers, if actions of adaptation and reducing vulnerability are not taken. To evaluate Brazil's vulnerability hotspots to these disasters, two vulnerability indexes were developed using three sets of variables: (1) climate, with IPCC climate extreme indexes; (2) environmental, including land use, drainage systems, relief map, slope, road density and hydrography variables; (3) socioeconomic, including Gini coefficient, HDI (Human Development Index), housing conditions and poverty-related index. The variables were normalized on a scale between 0 to 1 and related using Map Algebra technique (ArcGIS). As part of the effort to contribute to the elaboration of the Third National Communication to the United Nations Framework Convention on Climate Change (UNFCCC), and to contribute to the assessment of impacts on strategic country's issues, simulations at higher resolution were carried out using Eta-20km RCM (Regional Climate Model) nested with two global climate models: HadGEM ES and MIROC 5 (INPE Brazilian National Institute for Space Research). For the baseline period of 1961-1990, the vulnerability indexes were adjusted by an iterative process, which was validated by comparing it to the Brazilian National Disasters Data. The same indexes found at baseline were used to estimate the vulnerability until the end of the XXI century, using the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. The results indicate a large increase in Brazil's vulnerability to landslides mainly in coastal zone, southern states, high lands of southeast states, and along the Amazon River due to climatic aspects only, not considering other factors such as increase in population size, etc. Flashfloods vulnerability, on the other hand, increases mostly in the south/southeast regions, the northeast coastal zone and parts of the Amazon basin. Funded by: Ministry of Science and Technology of Brazil and the United Nations Development Program in Brazil.

Projected changes in the future distribution and production of sessile oak forests near the xeric limit

NASA Astrophysics Data System (ADS)

Gulyás, Krisztina; Berki, Imre; Veperdi, Gábor

2017-04-01

As a result of regional climate change, most European countries are experiencing an increase in mean annual temperature and CO2 concentration and a decrease in mean annual precipitation. In low-elevation areas in Southeast Europe, where precipitation is a limiting factor, the projected climate change threatens the health, production, and potential distribution of forest ecosystems. The intensive summer droughts and commonly occurring extreme weather events create negative influences that cause health declines, changes in yield potential, and tree mortality. Due to the observed damages, attention has been focused on these problems. The impacts of climatic extremes cause difficulties in forest management; these difficulties occur more frequently in Hungary, which is a region that is the most sensitive to climatic extremes. Regional climate model simulations project that the frequency of extremely high temperatures and long-term dry periods will increase; both of these factors have negative effects on future tree species distribution and production. Thus, the aim of our study is to utilize the sessile oak (Quercus petraea) as a climate indicator tree species to investigate potential future distribution and estimate changes in growth trends. For future spatial distribution, we used the Fuzzy membership distribution model in a new Decision Support System (DSS) which was developed for the Hungarian forestry and agricultural sectors. Through study techniques we can employ DSS, which contains various environmental layers (topography, vegetation, past and projected future climate, soils, and hydrology), to create probability distribution maps. The results, based on 12 regional climate model simulations (www.ensembles-eu.org), show that the area of sessile oak forests is shrinking continuously and will continue to do so to the end of the 21st century. For future production estimations, we analysed intensive long-term growth monitoring network plots that were established in 1993. We calculated production capacity on the basis of age and height; we then compared these to past climate conditions to discover connections between climate, site conditions, and production. We estimated future growth tendencies for three different time periods (2011-2040; 2041-2070; 2071-2100). Results show that the most vulnerable region is the south-western part of Hungary where the projected production capacity may decrease by 26% for the time period 2071-2100. The impacts of climate change may be milder in the north-eastern part of Hungary where a 19% decrease in the production capacity of sessile oak forests is estimated. These investigations and results are important for sustainable forest management and help define climate change adaptation strategies in forestry. Keywords: climate change impacts, distribution modelling, production capacity Acknowledgements: Research is supported by the ÚNKP-16-3-3 New National Excellence Program of the Ministry of Human Capacities and the "Agroclimate.2" (VKSZ_12-1-2013-0034) EU-national joint funded research project.

The Role of Social Influences on Pro-Environment Behaviors in the San Diego Region.

PubMed

Estrada, Mica; Schultz, P Wesley; Silva-Send, Nilmini; Boudrias, Michel A

2017-04-01

From a social psychological perspective, addressing the threats of climate change involves not only education, which imparts objective facts upon a passive individual, but also a socializing process. The Tripartite Integration Model of Social Influence (TIMSI) provides a theoretical framework that connects acquiring climate change knowledge with integration into a community, which results in greater engagement in climate friendly behaviors. Survey data were collected from 1000 residents in San Diego County. Measures included (a) knowledge about climate change; (b) self-efficacy, what pro-environmental actions they felt they could do; (c) identity, to what extent they identified as part of a community that is concerned about climate change; (d) values, endorsement of values of the community that is concerned about climate change; and (e) pro-environmental behavior, engagement in conservation behaviors. Results indicated that self-efficacy and values mediated the relationship between knowledge and pro-environmental behavior.

Paleoclimatology Supports Physics: Our Energy Choices Will Have Large and Long-Lasting Consequences for Climate and Ecosystems

NASA Astrophysics Data System (ADS)

Harland, B.; Bradley, R. S.; Schlosser, P.; Rignot, E. J.; Dickens, G. R.; Boslough, M.; Alley, R. B.

2016-12-01

Interpretations of the paleoclimatic record show with increasing clarity and confidence that CO2 has been the most important of the many controls on Earth's climate history, providing a slow stabilizer but fast destabilizer through both forcing and feedbacks. From the Faint Young Sun through Snowball Earth, the warmth of the Cretaceous, the PETM, ice-age cycling, and many events between, our best understanding shows that CO2 has been an essential player. Many climate reconstructions are based on the biological record; we know what CO2 did to the climate in part from the ways that living things responded. If our climate models have a shortcoming, the full climate response to CO2 is larger than simulated for shorter times. Surprisingly large response may prove to be especially important for ice sheets and sea level.

Role of internal variability in recent decadal to multidecadal tropical Pacific climate changes

NASA Astrophysics Data System (ADS)

Bordbar, Mohammad Hadi; Martin, Thomas; Latif, Mojib; Park, Wonsun

2017-05-01

While the Earth's surface has considerably warmed over the past two decades, the tropical Pacific has featured a cooling of sea surface temperatures in its eastern and central parts, which went along with an unprecedented strengthening of the equatorial trade winds, the surface component of the Pacific Walker Circulation (PWC). Previous studies show that this decadal trend in the trade winds is generally beyond the range of decadal trends simulated by climate models when forced by historical radiative forcing. There is still a debate on the origin of and the potential role that internal variability may have played in the recent decadal surface wind trend. Using a number of long control (unforced) integrations of global climate models and several observational data sets, we address the question as to whether the recent decadal to multidecadal trends are robustly classified as an unusual event or the persistent response to external forcing. The observed trends in the tropical Pacific surface climate are still within the range of the long-term internal variability spanned by the models but represent an extreme realization of this variability. Thus, the recent observed decadal trends in the tropical Pacific, though highly unusual, could be of natural origin. We note that the long-term trends in the selected PWC indices exhibit a large observational uncertainty, even hindering definitive statements about the sign of the trends.