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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Weather and Climate Change Impacts on Human Mortality in Bangladesh

Weather and climate profoundly affect human health. Several studies have demonstrated a U-, V-, or J-shaped temperature-mortality relationship with increasing death rates at the lower and particularly upper end of the temperature distribution. The objectives of this study were (1) to analyze the relationship between temperature and mortality in Bangladesh for different subpopulations and (2) to project future heat-related mortality under climate change scenarios. We used (non-)parametric Generalized Additive Models adjusted for trend, season and day of the month to analyze the effect of temperature on daily mortality. We found a decrease in mortality with increasing temperature over a wide range of values; between the 90th and 95th percentile an abrupt increase in mortality was observed which was particularly pronounced for the elderly above the age of 65 years, for males, as well as in urban areas and in areas with a high socio-economic status. Daily historical and future temperature values were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset. This dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5). The derived dose-response functions were used to estimate the number of heat-related deaths occurring during the 1990s (1980-2005), the 2020s (2011-2040) and the 2050s (2041-2070). We estimated that excess deaths due to heat will triple from the 1990s to the 2050s, with an annual number of 0.5 million excess deaths in 1990 to and expected number of 1.5 millions in 2050.

mortality↗
DOE OSTI2020

Evaluating cross-sectoral impacts of climate change and adaptations on the energy-water nexus: a framework and California case study

Abstract Electricity and water systems are inextricably linked through water demands for energy generation, and through energy demands for using, moving, and treating water and wastewater. Climate change may stress these interdependencies, together referred to as the energy-water nexus, by reducing water availability for hydropower generation and by increasing irrigation and electricity demand for groundwater pumping, among other feedbacks. Further, many climate adaptation measures to augment water supplies—such as water recycling and desalination—are energy-intensive. However, water and electricity system climate vulnerabilities and adaptations are often studied in isolation, without considering how multiple interactive risks may compound. This paper reviews the fragmented literature and develops a generalized framework for understanding these implications of climate change on the energy-water nexus. We apply this framework in a case study to quantify end-century direct climate impacts on California’s water and electricity resources and estimate the magnitude of the indirect cross-sectoral feedback of electricity demand from various water adaptation strategies. Our results show that increased space cooling demand and decreased hydropower generation are the most significant direct climate change impacts on California’s electricity sector by end-century. In California’s water sector, climate change impacts directly on surface water availability exceed demand changes, but have considerable uncertainty, both in direction and magnitude. Additionally, we find that the energy demands of water sector climate adaptations could significantly affect California’s future electricity system needs. If the worst-case water shortage occurs under climate change, water-conserving adaptation measures can provide large energy savings co-benefits, but other energy-intensive water adaptations may double the direct impacts of climate change on the state’s electricity resource requirement. These results highlight the value of coordinated adaptation planning between the energy and water sectors to achieve mutually beneficial solutions for climate resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mid-century climate change impacts on tornado-producing tropical cyclones

Tornadoes are a co-occurring extreme that can be produced by landfalling tropical cyclones (TCs). These tornadoes can exacerbate the loss of life and property damage caused by the TC from which they were spawned. It is uncertain how the severe weather environments of landfalling TCs may change in a future climate and how this could impact tornado activity from TCs. In this study, we investigated four TCs that made landfall in the U.S. and produced large tornado outbreaks. We performed four-member ensembles of convective-allowing (4-km resolution) regional climate model simulations representing each TC in the historical climate and a mid-twenty-first century future climate. To identify potentially tornadic storms, or TC-tornado (TCT) surrogates, we used thresholds for three-hourly maximum updraft helicity and radar reflectivity, as tornadoes are not resolved in the model. We found that the ensemble-mean number of TCT-surrogates increased substantially (56–299%) in the future, supported by increases in most-unstable convective available potential energy, surface-to-700-hPa bulk wind shear, and 0–1-km storm-relative helicity in the tornado-producing region of the TCs. On the other hand, future changes in most-unstable convective inhibition had minimal influence on future TCT-surrogates. This provides robust evidence that tornado activity from TCs may increase in the future. Furthermore, TCT-surrogate frequency between 00Z and 09Z increased for three of the four cases, suggesting enhanced tornado activity at night, when people are asleep and more likely to miss warnings. All of these factors indicate that TC-tornadoes may become more frequent and a greater hazard in the future, compounding impacts from future increases in TC winds and precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1∕8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

extreme climate index↗
NASA NTRS2011

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗
NASA NTRS2011

Remote Sensing of Urban Land Cover/Land Use Change, Surface Thermal Responses, and Potential Meteorological and Climate Change Impacts

City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will potentially affect land cover LSTs across the Center. Moreover, the weather stations will also provide baseline data for developing a better understanding of how localized weather factors, such as extreme rainfall and heat events, affect micrometeorology. These data can also be used to model the interrelationships between LSTs and meteorology on a longer term basis to help evaluate how changes in these parameters can be quantified from satellite data collected in the future. In turn, the overall integration of multi-temporal meteorological information with LULCC, and LST data for MSFC proper and the surrounding Huntsville urbanized area can provide a perspective on how urban land surface types affect the meteorology in the boundary layer and ultimately, the UHI. Additionally, data such as this can be used as a foundation for modeling how climate change will potentially impact local and regional meteorology and conversely, how urban LULCC can or will influence changes on climate over the north Alabama area.

Quattrochi, Dale A.↗
NASA NTRS2021

Indicators of Climate Change Impacts on the Water Cycle and Water Management

Managing water is a top social and economic responsibility and is expected to become even more critical as climate change, in addition to other human activities, alters water availability and quality. Robust indicators reflecting the effects of climate change on the U.S. and global water cycles are needed in order to appropriately manage water resources. Here, we describe a suite of seventeen water cycle and management indicators, which are based on synthesis of available datasets. These indicators include: average and heavy precipitation, standardized precipitation index, annual, 7-day low and 3-day high streamflow volume, streamflow timing, snow cover, snow water equivalent, groundwater level, lake water temperature, stream water temperature, dissolved oxygen, salinity, Palmer Drought Severity Index, water withdrawals and water use. We also identify three indicators that could be included in the suite of water cycle and management indicators with some additional, directed work: snowfall, evapotranspiration and soil moisture. Our conceptual framework focuses on known water cycle changes in addition to potential effects on management, and addresses water quantity and quality, as well as water use and related interactions with freshwater ecosystems, societal impacts, and management. Water cycle indicators are organized into three categories: (1) hydrologic processes, (2) water quality processes, and (3) water quality and quantity impacts. Indicators described here are recommended to serve as critical references for periodic climate assessments. As such, these indicators support analyses of the effects of global change on the natural environment, agriculture, energy, and water resources, among other sectors. Additionally, we identify research gaps and needs that can be addressed to advance the development of future indicators.

Christa D Peters-Lidard↗
NASA NTRS2017

Synthetic Scenarios from CMIP5 Model Simulations for Climate Change Impact Assessments in Managed Ecosystems and Water Resources: Case Study in South Asian Countries

Increasing population, urbanization, and associated demand for food production compounded by climate change and variability have important implications for the managed ecosystems and water resources of a region. This is particularly true for south Asia, which supports one quarter of the global population, half of whom live below the poverty line. This region is largely dependent on monsoon precipitation for water. Given the limited resources of the developing countries in this region, the objective of our study was to empirically explore climate change in south Asia up to the year 2099 using monthly simulations from 35 global climate models (GCMs) participating in the fifth phase of the Climate Model Inter-comparison Project (CMIP5) for two future emission scenarios (representative concentration pathways RCP4.5 and RCP8.5) and provide a wide range of potential climate change outcomes. This was carried out using a three-step procedure: calculating the mean annual, monsoon, and non-monsoon precipitation and temperatures; estimating the percent change from historical conditions; and developing scenario funnels and synthetic scenarios. This methodology was applied for the entire south Asia region; however, the percent change information generated at 1.5deg grid scale can be used to generate scenarios at finer spatial scales. Our results showed a high variability in the future change in precipitation (-23% to 52%, maximum in the non-monsoon season) and temperature (0.8% to 2.1%) in the region. Temperatures in the region consistently increased, especially in the Himalayan region, which could have impacts including a faster retreat of glaciers and increased floods. It could also change rivers from perennial to seasonal, leading to significant challenges in water management. Increasing temperatures could further stress groundwater reservoirs, leading to withdrawal rates that become even more unsustainable. The high precipitation variability (with higher propensity for localized intense rainfall events) observed in the region can be a key factor for managed ecosystems and water management and could also lead to more incidence of severe urban flooding. The results could be used to assess both mitigation and adaptation alternatives to reduce vulnerabilities in managed ecosystems (agricultural and urban) and water resources.

agriculture↗
NASA NTRS2021

Climate Change Impacts and Adaptation for Dryland Farming Systems in Zimbabwe: A Stakeholder-Driven Integrated Multi-Model Assessment

Decision makers need accurate information to address climate variability and change and accelerate transformation to sustainability. A stakeholder-driven, science-based multi-model approach has been developed and used by the Agricultural Model Intercomparison and Improvement Project (AgMIP) to generate actionable information for adaptation planning processes. For a range of mid-century climate projections—likely to be hotter, drier, and more variable—contrasting future socio-economic scenarios (Representative Agricultural Pathways, RAPs) were co-developed with stakeholders to portray a sustainable development scenario and a rapid economic growth pathway. The unique characteristic of this application is the integration of a multi-modeling approach with stakeholder engagement to co-develop scenarios and adaptation strategies. Distribution of outcomes were simulated with climate, crop, livestock, and economic impact assessment models for smallholder crop livestock farmers in a typical dryland agro-ecological zone in Zimbabwe, characterized by low and erratic rainfall and nutrient depleted soils. Results showed that in Nkayi District, Western Zimbabwe, climate change would threaten most of the farms, and, in particular, those with large cattle herds due to feed shortages. Adaptation strategies that showed the most promise included diversification using legume production, soil fertility improvement, and investment in conducive market environments. The switch to more legumes in the farming systems reduced the vulnerability of the very poor as well as the more resourced farmers. Overall, the sustainable development scenario consistently addressed institutional failures and motivated productivity-enhancing, environmentally sound technologies and inclusive development approaches. This yielded more favorable outcomes than investment in quick economic wins from commercializing agriculture.

Climate change adaptation↗
DOE OSTI2021

Assessing climate change impacts on live fuel moisture and wildfire risk using a hydrodynamic vegetation model

Abstract. Live fuel moisture content (LFMC) plays a critical role in wildfire dynamics, but little is known about responses of LFMC to multivariate climate change, e.g., warming temperature, CO2 fertilization, and altered precipitation patterns, leading to a limited prediction ability of future wildfire risks. Here, we use a hydrodynamic demographic vegetation model to estimate LFMC dynamics of chaparral shrubs, a dominant vegetation type in fire-prone southern California. We parameterize the model based on observed shrub allometry and hydraulic traits and evaluate the model's accuracy through comparisons between observed and simulated LFMC of three plant functional types (PFTs) under current climate conditions. Moreover, we estimate the number of days per year of LFMC below 79 % (which is a critical threshold for wildfire danger rating of southern California chaparral shrubs) from 1960 to 2099 for each PFT and compare the number of days below the threshold for medium and high greenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climate change could lead to more days per year (5.2 %–14.8 % increase) with LFMC below 79 % between the historical (1960–1999) and future (2080–2099) periods, implying an increase in wildfire danger for chaparral shrubs in southern California. Under the high greenhouse gas emission scenario during the dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1 %–18.6 % reduction in LFMC. Lower precipitation in the spring leads to a 6.3 %–8.1 % reduction in LFMC. The combined impacts of warming and precipitation change on fire season length are equal to the additive impacts of warming and precipitation change individually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5 %–4.8 % increase in LFMC. Our results suggest that multivariate climate change could cause a significant net reduction in LFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Climate Change on Energy Systems in Global and Regional Scenarios

A growing number of studies report the impact of climate change on the supply, demand, transport, and cost of energy. However, there is lack of comprehensive overview and understanding of climate change impacts on energy across technologies and scales. Here, we conduct a systematic assessment of results from 186 papers on potential impacts of climate change on energy. Results show that increased cooling demand and decreased heating demand is anticipated globally. Similarly, increases in bio-energy and hydro power and a possible decrease in thermal electricity supply is projected. Overall changes in heating and cooling demand, increased thermal cooling, and reduced hydropower supply in Europe, India and Latin America are projected 35 at the regional scale. Furthermore, our review revealed that studies use a wide range of inconsistent methods and data sources. To move forward, the study proposes a consistent multi-model assessment framework for a comprehensive understanding of climate impacts on energy.

Yalew, Seleshi G.↗
NASA NTRS2013

Ocean Biological Pump Sensitivities and Implications for Climate Change Impacts

The ocean is one of the principal reservoirs of CO2, a greenhouse gas, and therefore plays a crucial role in regulating Earth's climate. Currently, the ocean sequesters about a third of anthropogenic CO2 emissions, mitigating the human impact on climate. At the same time, the deeper ocean represents the largest carbon pool in the Earth System and processes that describe the transfer of carbon from the surface of the ocean to depth are intimately linked to the effectiveness of carbon sequestration.The ocean biological pump (OBP), which involves several biogeochemical processes, is a major pathway for transfer of carbon from the surface mixed layer into the ocean interior. About 75 of the carbon vertical gradient is due to the carbon pump with only 25 attributed to the solubility pump. However, the relative importance and role of the two pumps is poorly constrained. OBP is further divided to the organic carbon pump (soft tissue pump) and the carbonate pump, with the former exporting about 10 times more carbon than the latter through processes like remineralization.Major uncertainties about OBP, and hence in the carbon uptake and sequestration, stem from uncertainties in processes involved in OBP such as particulate organicinorganic carbon sinkingsettling, remineralization, microbial degradation of DOC and uptakegrowth rate changes of the ocean biology. The deep ocean is a major sink of atmospheric CO2 in scales of hundreds to thousands of years, but how the export efficiency (i.e. the fraction of total carbon fixation at the surface that is transported at depth) is affected by climate change remains largely undetermined. These processes affect the ocean chemistry (alkalinity, pH, DIC, particulate and dissolved organic carbon) as well as the ecology (biodiversity, functional groups and their interactions) in the ocean. It is important to have a rigorous, quantitative understanding of the uncertainties involved in the observational measurements, the models and the projections of future changes.

particulates↗
DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Compounding climate change impacts during high stress periods for a high wind and solar power system in Texas

Power system planning aims at ensuring that sufficient supply- and demand-side assets exist to meet electricity demand at all times. For a Texas electric power system with high wind and solar penetrations, we quantify how climate change will affect supply and demand during three types of high stress periods for the power grid: high demand hours, high net demand hours, and high system ramp hours. We specifically quantify effects on demand, reductions in available thermal capacity (i.e. thermal deratings), wind and solar generation, and net demand. We estimate each using meteorological variables from five climate change projections (2041-2050) assuming Representative Concentration Pathway 8.5 and from a reference period (1996-2005). All five projections indicate that climate change will increase demand by up to 2 GWh during high demand hours (4% of demand in the reference period) and increase net demand by up to 3 GWh during high net demand periods (6% of net demand in the reference period). All five projections also indicate thermal deratings will increase during high demand and net demand periods by up to 2 GWh and high net demand ramps will increase by up to 2 GW. Overall, our results indicate compounding effects of climate change in Texas will necessitate greater investment in peak and flexible capacity.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

Integrated Assessment of Climate Change Impacts on Maize Farms and Farm Household Incomes in South India: A Case Study from Tamil Nadu: Chapter - 9

South India is characterized by a wide variety of landscapes, soils and climatic zones. It is comprised of tropical, semi-arid, humid-moist, and high-altitude environments, which support a diversity of agricultural systems. Our study focused on the state of Tamil Nadu, which is characterized by a generally tropical climate, and receive rainfall during both the southwest monsoon season (SWM, June to September) and the northeast monsoon (NEM, September to December). Agriculture continues to be an important sector in the state economy, as more than 56 of the people depend on agriculture and allied sectors for their livelihood. Analysis of land-use patterns in Tamil Nadu reveals that in the past decade there has been a reduction in net sown area and current fallow, while the share of cultivable wastelands has increased. The area under cereals, pulses, and oilseeds had marginally declined, although area under commercial crops like turmeric, sugar-cane, banana, fruits, and vegetables has shown an increasing trend. The production performance of major crops like cereals, pulses, and oilseeds has not shown any significant increase. Demand and supply gap of important crops in Tamil Nadu for the year 2010 indicates that the state is lagging far behind in the production of various crops.

agriculture↗
DOE OSTI2023

Predicting climate change impacts on poikilotherms using physiologically guided species abundance models

Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climate change impacts on wind power generation

Wind energy is a virtually carbon-free and pollution-free electricity source, with global wind resources greatly exceeding electricity demand. Accordingly, the installed capacity of wind turbines grew at an annualized rate of >20% from 2000 to 2019 and is projected to increase by a further 50% by the end of 2023. Here, in this Review, we describe the factors that dictate the wind resource magnitude and variability and illustrate the tools and techniques that are being used to make projections of wind resources and wind turbine operating conditions. Natural variability due to the action of internal climate modes appears to dominate over global-warming-induced non-stationarity over most areas with large wind energy installations or potential. However, there is evidence for increased wind energy resources by the end of the current century in northern Europe and the US Southern Great Plains. New technology trends are changing the sensitivity of wind energy to global climate non-stationarity and, thus, present new challenges and opportunities for innovative research. The evolution of climate modelling to increasingly address mesoscale processes is providing improved projections of both wind resources and wind turbine operating conditions, and will contribute to continued reductions in the levelized cost of energy from wind power generation.

17 WIND ENERGY↗
NASA NTRS2015

Representative Agricultural Pathways and Scenarios for Regional Integrated Assessment of Climate Change Impacts, Vulnerability, and Adaptation: Chapter - 5

The global change research community has recognized that new pathway and scenario concepts are needed to implement impact and vulnerability assessment where precise prediction is not possible, and also that these scenarios need to be logically consistent across local, regional, and global scales. For global climate models, representative concentration pathways (RCPs) have been developed that provide a range of time-series of atmospheric greenhouse-gas concentrations into the future. For impact and vulnerability assessment, new socio-economic pathway and scenario concepts have also been developed, with leadership from the Integrated Assessment Modeling Consortium (IAMC).This chapter presents concepts and methods for development of regional representative agricultural pathways (RAOs) and scenarios that can be used for agricultural model intercomparison, improvement, and impact assessment in a manner consistent with the new global pathways and scenarios. The development of agriculture-specific pathways and scenarios is motivated by the need for a protocol-based approach to climate impact, vulnerability, and adaptation assessment. Until now, the various global and regional models used for agricultural-impact assessment have been implemented with individualized scenarios using various data and model structures, often without transparent documentation, public availability, and consistency across disciplines. These practices have reduced the credibility of assessments, and also hampered the advancement of the science through model intercomparison, improvement, and synthesis of model results across studies. The recognition of the need for better coordination among the agricultural modeling community, including the development of standard reference scenarios with adequate agriculture-specific detail led to the creation of the Agricultural Model Intercomparison and Improvement Project (AgMIP) in 2010. The development of RAPs is one of the cross-cutting themes in AgMIP's work plan, and has been the subject of ongoing work by AgMIP since its creation.

agriculture↗