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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Exploring the Climatic Impact of Bi-Modal Dust Particle Size Distributions During the MY34/2018 Global Dust Storm with the NASA Ames Mars Global Climate Model.

We have implemented a bi-modal dust lifting scheme in the NASA Ames Mars Global Climate Model (GCM) and investigated the climatic impact on the MY34/2018 Global Dust Storm (GDS). We found that the climate is measurably responsive to the inclusion of a second, smaller dust mode. Dust tends to be lifted through a deeper column in the atmosphere, which is reflected in the climate as changes to atmospheric temperature, tide amplitudes, and surface temperatures. Adding a modest fraction of a smaller dust mode improves simulations during the GDS compared to Curiosity semi-diurnal tide observations as well as Mars Climate Sounder (MCS) T15 brightness temperatures

R A Urata↗
DOE OSTI2016

Drivers of Change in Managed Water Resources: Modeling the Impacts of Climate and Socioeconomic Changes Using the US Midwest as a Case Study

A global integrated assessment model including a water-demand model driven by socio-economics, is coupled in a one-way fashion with a land surface hydrology – routing – water resources management model. The integrated modeling framework is applied to the U.S. Upper Midwest (Missouri, Upper Mississippi, and Ohio) to advance understanding of the regional impacts of climate and socio-economic changes on integrated water resources. Implications for future flow regulation, water supply, and supply deficit are investigated using climate change projections with the B1 and A2 emission scenarios, which affect both natural flow and water demand. Changes in water demand are driven by socio-economic factors, energy and food demands, global markets and prices. The framework identifies the multiple spatial scales of interactions between the drivers of changes (natural flow and water demand) and the managed water resources (regulated flow, supply and supply deficit). The contribution of the different drivers of change are quantified regionally, and also evaluated locally, using covariances. The integrated framework shows that water supply deficit is more predictable over the Missouri than the other regions in the Midwest. The predictability of the supply deficit mostly comes from long term changes in water demand although changes in runoff has a greater contribution, comparable to the contribution of changes in demand, over shorter time periods. The integrated framework also shows that spatially, water demand drives local supply deficit. Using elasticity, the sensitivity of supply deficit to drivers of change is established. The supply deficit is found to be more sensitive to changes in runoff than to changes in demand regionally. It contrasts with the covariance analysis that shows that water demand is the dominant driver of supply deficit over the analysed periods. The elasticity indicates the level of mitigation needed to control the demand in order to reduce the vulnerability of the integrated system in future periods. The elasticity analyses also emphasize the need to address uncertainty with respect to changes in natural flow in integrated assessment.

climate change, water resources management, socio-↗
DOE OSTI2019

Evaluating the Relationship between Interannual Variations in the Antarctic Ozone Hole and Southern Hemisphere Surface Climate in Chemistry–Climate Models

Studies have recently reported statistically significant relationships between observed year-to-year spring Antarctic ozone variability and the Southern Hemisphere annular mode and surface temperatures in spring–summer. This study reported herein investigates whether current chemistry–climate models (CCMs) can capture these relationships, in particular, the connection between November total column ozone (TCO) and Australian summer surface temperatures, where years with anomalously high TCO over the Antarctic polar cap tend to be followed by warmer summers. The interannual ozone–temperature teleconnection is examined over the historical period in the observations and simulations from the Whole Atmosphere Community Climate Model (WACCM) and nine other models participating in the Chemistry–Climate Model Initiative (CCMI). There is a systematic difference between the WACCM experiments forced with prescribed observed sea surface temperatures (SSTs) and those with an interactive ocean. Strong correlations between TCO and Australian temperatures are only obtained for the uncoupled experiment, suggesting that the SSTs could be important for driving both variations in Australian temperatures and the ozone hole, with no causal link between the two. Other CCMI models also tend to capture this relationship with more fidelity when driven by observed SSTs, although additional research and targeted modeling experiments are required to determine causality and further explore the role of model biases and observational uncertainty. The results indicate that CCMs can reproduce the relationship between spring ozone and summer Australian climate reported in observational studies, suggesting that incorporating ozone variability could improve seasonal predictions; however, more work is required to understand the difference between the coupled and uncoupled simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Climate Control Load Reduction Strategies for Electric Drive Vehicles in Cold Weather

When operated, the climate control system is the largest auxiliary load on a vehicle. This load has significant impact on fuel economy for conventional and hybrid vehicles, and it drastically reduces the driving range of all electric vehicles (EVs). Heating is even more detrimental to EV range than cooling because no engine waste heat is available. Reducing the thermal loads on the heating, ventilating, and air conditioning system will extend driving range and increase the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have evaluated strategies for vehicle climate control load reduction with special attention toward grid connected electric vehicles. Outdoor vehicle thermal testing and computational modeling were used to assess potential strategies for improved thermal management and to evaluate the effectiveness of thermal load reduction technologies. A human physiology model was also used to evaluate the impact on occupant thermal comfort. Experimental evaluations of zonal heating strategies demonstrated a 5.5% to 28.5% reduction in cabin heating energy over a 20-minute warm-up. Vehicle simulations over various drive cycles show a 6.9% to 18.7% improvement in EV range over baseline heating using the most promising zonal heating strategy investigated. A national-level analysis was conducted to determine the overall national impact. If all vehicles used the best zonal strategy, the range would be improved by 7.1% over the baseline heating range. This is a 33% reduction in the range penalty for heating.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Climate warming causes photobiont degradation and carbon starvation in a boreal climate sentinel lichen

The long-term potential for acclimation by lichens to changing climates is poorly known, despite their prominent roles in forested ecosystems. Although often considered “extremophiles,” lichens may not readily acclimate to novel climates well beyond historical norms. In a previous study, Evernia mesomorpha transplants in a whole-ecosystem climate change experiment showed drastic mass loss after 1 yr of warming and drying; however, the causes of this mass loss were not addressed. We examined the causes of this warming-induced mass loss by measuring physiological, functional, and reproductive attributes of lichen transplants. Severe loss of mass and physiological function occurred above +2°C of experimental warming. Loss of algal symbionts (“bleaching”) and turnover in algal community compositions increased with temperature and were the clearest impacts of experimental warming. Enhanced CO 2 had no significant physiological or symbiont composition effects. The functional loss of algal photobionts led to significant loss of mass and specific thallus mass (STM), which in turn reduced water-holding capacity (WHC). Although algal genotypes remained detectable in thalli exposed to higher stress, within-thallus photobiont communities shifted in composition toward greater diversity. The strong negative impacts of warming and/or lower humidity on Evernia mesomorpha were driven by a loss of photobiont activity. Analogous to the effects of climate change on corals, the balance of symbiont carbon metabolism in lichens is central to their resilience to changing conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Response of the Quasi–Biennial Oscillation to a warming climate in global climate models

We compare the response of the Quasi–Biennial Oscillation (QBO) to a warming climate in eleven atmosphere general circulation models that performed time–slice simulations for present–day, doubled, and quadrupled CO 2 climates. No consistency was found among the models for the QBO period response, with the period decreasing by 8 months in some models and lengthening by up to 13 months in others in the doubled CO 2 simulations. In the quadrupled CO 2 simulations, a reduction in QBO period of 14 months was found in some models, whereas in several others the tropical oscillation no longer resembled the present–day QBO, although it could still be identified in the deseasonalized zonal mean zonal wind timeseries. In contrast, all the models projected a decrease in the QBO amplitude in a warmer climate with the largest relative decrease near 60 hPa. In simulations with doubled and quadrupled CO 2 , the multi–model mean QBO amplitudes decreased by 36 and 51%, respectively. Across the models the differences in the QBO period response were most strongly related to how the gravity wave momentum flux entering the stratosphere and tropical vertical residual velocity responded to the increases in CO 2 amounts. Likewise it was found that the robust decrease in QBO amplitudes was correlated across the models to changes in vertical residual velocity, parametrized gravity wave momentum fluxes, and to some degree the resolved upward wave flux. Here, we argue that uncertainty in the representation of the parameterized gravity waves is the most likely cause of the spread among the eleven models in the QBO's response to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

DISCOVR strain pipeline screening – Part II: Winter and summer season areal productivities and biomass compositional shifts in climate-simulation photobioreactor cultures

Assessing the seasonal biomass productivity and compositional shift dynamics under simulated outdoor culture conditions of the top 22 algae strains selected during Tier I flask screening is an important step in the further prioritization of strains with regard to outdoor pond cultivation. These top 22 strains were subjected to Tier II testing in the PNNL Laboratory Environmental Algae Pond Simulator (LEAPS) photobioreactors, simulating light and temperature conditions of 20 cm deep outdoor ponds during the Arizona winter and summer season. All strains were grown in two consecutive nutrient-replete batch culture experiments at their particular optimal medium salinity to quantify their respective seasonal linear-phase areal biomass productivities. To determine biomass compositional shifts in response to nutrient-depletion, the LEAPS cultures were allowed to enter a 9-day nutrient depletion phase at the end of the second batch run. The following strains were evaluated in winter-season climate-simulated cultures and are listed in the order from highest (7.9 g m -2 day -1 ) to lowest (2.3 g m -2 day -1 ) areal N-replete biomass productivity: Monoraphidium minutum 26B-AM, Tetraselmis striata LANL1001, Chlorella vulgaris LRB AZ-1201, Micractinium reisseri NREL14-F2, Monoraphidium sp. MONOR1, Chlorella vulgaris NREL4-C12, Scenedesmus obliquus UTEX393, Scenedesmus acutus LRB-AP-0401, Nannochloropsis oceanica CCAP849/10, and Stichococcus minutus CCALA727. The following strains were evaluated in summer-season climate-simulated cultures and are listed in the order from highest (31.8 g m -2 day -1 ) to lowest (14.2 g m -2 day -1 ) areal N-replete biomass productivity: Picochlorum renovo NREL39-A8, Scenedesmus obliquus UTEX393, Porphyridium cruentum CCMP675, Picochlorum celeri TG2-WT-CSM/EMRE, Chlorella sorokiniana DOE1116, Stichococcus minor CCMP819, Picochlorum oklahomensis CCMP2329, Chlorella sorokiniana DOE1412 (UTEXB3016), Scenedesmus rubescens NREL46B-D3, Picochlorum soloecismus DOE101, Tetraselmis striata LANL1001, Scenedesmus obliquus DOE 0152.z, and Agmenellum quadruplicatum UTEX2268. All LEAPS cultures experienced a significant reduction in areal biomass productivity in response to nutrient-depletion, from 7-16% in the winter season simulation and up to 1-60% in the summer season simulation. Finally, for 10 of the strains tested, the carbohydrate content more than doubled upon nutrient depletion, and for 9 strains, the lipid content increased by over 50% of the initial content.

09 BIOMASS FUELS↗
DOE OSTI2018

Impacts of Climate Change, Policy and Water-Energy-Food Nexus on Hydropower Development

Hydropower plays an important role as the global energy system moves towards a less carbon-intensive and sustainable future as promoted under the Sustainable Development Goals (SDGs). This article provides a systematic review of the impacts from policy, climate change and Water-Energy-Food (W-E-F) nexus on hydropower development at global scale. Asia, Africa and Latin America are hotspots promoting hydropower development with capacity expansion, while Europe and North America focus on performance improvement and environment impacts mitigation. Climate change is projected to improve gross hydropower potential at high latitude of North Hemisphere and tropical Africa and decrease that in the US, South Africa and south and central Europe. Analysis from W-E-F nexus highlights the importance of integrated approaches as well as cross-sectoral coordination so as to improve resources use efficiency and achieve sustainable hydropower development. These three factors together shape the future of hydropower and need to be considered for planning and operation purpose.

Zhang, Xiao↗
DOE OSTI2015

CO₂ emission mitigation and fossil fuel markets: Dynamic and international aspects of climate policies

This paper explores a multi-model scenario ensemble to assess the impacts of idealized and non-idealized climate change stabilization policies on fossil fuel markets. Under idealized conditions climate policies significantly reduce coal use in the short- and long-term. Reductions in oil and gas use are much smaller, particularly until 2030, but revenues decrease much more because oil and gas prices are higher than coal prices. A first deviation from optimal transition pathways is delayed action that relaxes global emission targets until 2030 in accordance with the Copenhagen pledges. Fossil fuel markets revert back to the no-policy case: though coal use increases strongest, revenue gains are higher for oil and gas. To balance the carbon budget over the 21st century, the long-term reallocation of fossil fuels is significantly larger—twice and more—than the short-term distortion. This amplifying effect results from coal lock-in and inter-fuel substitution effects to balance the full-century carbon budget. The second deviation from the optimal transition pathway relaxes the global participation assumption. The result here is less clear-cut across models, as we find carbon leakage effects ranging from positive to negative because trade and substitution patterns of coal, oil, and gas differ across models. In summary, distortions of fossil fuel markets resulting from relaxed short-term global emission targets are more important and less uncertain than the issue of carbon leakage from early mover action.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

The Importance of Weather and Climate to Energy Systems: A Workshop on Next Generation Challenges in Energy–Climate Modeling

More than 80 international participants, representing weather, climate, and energy systems research, joined two 4-hour remote sessions to highlight and prioritize ongoing and future challenges in energy-climate modelling. The workshop had two primary goals: to build a deeper engagement across the “energy” and “climate” research communities, and to identify and begin to address the scientific challenges associated with modelling climate risk in energy systems.

17 WIND ENERGY↗
DOE OSTI2020

Impacts of Wildfire Aerosols on Global Energy Budget and Climate: The Role of Climate Feedbacks

Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be -0.78 ± 0.29 W m -2 , which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; -0.70 ± 0.20 W m -2 ). The associated global annual-mean surface air temperature (SAT) change ΔT is -0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ΔT) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ΔT) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Impact of Tropical Cyclone Wind Forcing on the Global Climate in a Fully Coupled Climate Model

Tropical cyclones (TCs) alter upper-ocean temperature and influence ocean heat content via enhanced turbulent mixing. A better understanding of the role of TCs within the climate system requires a fully coupled modeling framework, where TC-induced ocean responses feed back to the atmosphere and subsequently to the climate mean state and variability. Here, we investigate the impacts of TC wind forcing on the global ocean and the associated feedbacks within the climate system using the fully coupled Community Earth System Model version 1.3 (CESM1.3). Using the low-resolution version of CESM1.3 (1° atmosphere and ocean grid spacing) with no intrinsic TCs, we conduct a suite of sensitivity experiments by inserting TC winds extracted from a high-resolution (0.25° atmosphere grid spacing) TC-permitting simulation into the low-resolution model. Results from the low-resolution TC experiment are compared to a low-resolution control simulation to diagnose TCs’ impact. We found that the added TC winds can increase ocean heat content by affecting ocean vertical mixing, air–sea enthalpy fluxes, and cloud amount. Here, the added TCs can influence mean SST, precipitation, ocean subsurface temperature, and ocean mixed layer depth. We found a strengthening of the wind-driven subtropical cells and a weakening of the Atlantic meridional overturning circulation due to the changes of surface buoyancy fluxes. TCs in the model cause anomalous equatorward ocean heat convergence in the deep tropics and an increase of poleward ocean heat transport out of the subtropics. Our modeling results provide new insights into the multiscale interactions between TCs and the coupled climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at the surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2 , SO 2 , PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Downscaling a Global Climate Model to Simulate Climate Change Impacts on U.S. Regional and Urban Air Quality

Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with WRF to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the continental United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF RCM to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12km by 12km resolution, as well as the effect of evolving climate conditions on the air quality at major U.S. cities. The high resolution simulations produce somewhat different results than the coarse resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the U.S. during fall (Western U.S., Texas, Northeastern, and Southeastern U.S), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). We also find that daily peak temperatures tend to increase in most major cities in the U.S. which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

meteorological parameters↗
NASA NTRS2015

Climate Data Initiative: A Geocuration Effort to Support Climate Resilience

Curation is traditionally defined as the process of collecting and organizing information around a common subject matter or a topic of interest and typically occurs in museums, art galleries, and libraries. The task of organizing data around specific topics or themes is a vibrant and growing effort in the biological sciences but to date this effort has not been actively pursued in the Earth sciences. In this paper, we introduce the concept of geocuration and define it as the act of searching, selecting, and synthesizing Earth science data/metadata and information from across disciplines and repositories into a single, cohesive, and useful compendium We present the Climate Data Initiative (CDI) project as an exemplar example. The CDI project is a systematic effort to manually curate and share openly available climate data from various federal agencies. CDI is a broad multi-agency effort of the U.S. government and seeks to leverage the extensive existing federal climate-relevant data to stimulate innovation and private-sector entrepreneurship to support national climate-change preparedness. We describe the geocuration process used in CDI project, lessons learned, and suggestions to improve similar geocuration efforts in the future.

virtual collections↗
NASA NTRS2020

Using Climate Models to Learn: Investigating the Phenomenon of Increasing Surface Air Temperatures Using a Global Climate Modeling Approach

Since 1880, Earth’s average global temperature has increased by approximately 1.4 °F (0.8 °C). Approximately two-thirds of the warming has occurred since 1975 (Wuebbles, Easterling, Hayhoe, et al. 2017). Despite consensus about global climate change (GCC) within the scientific community, students struggle to comprehend - why temperatures are increasing globally - at what rate this change is occurring, and - how climate scientists predict Earth’s future climate. These challenges are due, in part, to the abstraction inherent to understanding GCC, a phenomenon that occurs over long periods of time (past and future), and over large regions (regional and global). With the adoption of the Next Generation Science Standards (NGSS Lead States 2013), GCC is emphasized at the secondary school level, with a focus on analyzing and understanding the evidence for GCC (HS-ESS3-1), climate modeling (HS-ESS2-6, HS-ESS3-5), and the impact of humans on the environment (HS-LS2-7, HS-ESS3-6).

climate models↗
DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗
NASA NTRS2017

Selection of a Representative Subset of Global Climate Models that Captures the Profile of Regional Changes for Integrated Climate Impacts Assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Climate Change; GCMs; Climate Model Subset; Repres↗