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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Atmospheric River Detection Under Changing Seasonality and Mean-State Climate: ARTMIP Tier 2 Paleoclimate Experiments

Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single-forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO2 levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean-state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.

Atmospheric river, paleoclimate↗

NASA NTRS2011

Modeling of Firn Compaction for Estimating Ice-Sheet Mass Change from Observed Ice-Sheet Elevation Change

Changes in ice-sheet surface elevation are caused by a combination of ice-dynamic imbalance, ablation, temporal variations in accumulation rate, firn compaction and underlying bedrock motion. Thus, deriving the rate of ice-sheet mass change from measured surface elevation change requires information on the rate of firn compaction and bedrock motion, which do not involve changes in mass, and requires an appropriate firn density to associate with elevation changes induced by recent accumulation rate variability. We use a 25 year record of surface temperature and a parameterization for accumulation change as a function of temperature to drive a firn compaction model. We apply this formulation to ICESat measurements of surface elevation change at three locations on the Greenland ice sheet in order to separate the accumulation-driven changes from the ice-dynamic/ablation-driven changes, and thus to derive the corresponding mass change. Our calculated densities for the accumulation-driven changes range from 410 to 610 kg/cu m, which along with 900 kg/cu m for the dynamic/ablation-driven changes gives average densities ranging from 680 to 790 kg/cu m. We show that using an average (or "effective") density to convert elevation change to mass change is not valid where the accumulation and the dynamic elevation changes are of opposite sign.

Li, Jun↗

DOE OSTI2021

Microbial community response to a decade of simulated global changes depends on the plant community

Global changes such as increased drought and atmospheric nitrogen deposition perturb both the microbial and plant communities that mediate terrestrial ecosystem functioning. However, few studies consider how microbial responses to global changes may be influenced by interactions with plant communities. To begin to address the role of microbial–plant interactions, we tested the hypothesis that the response of microbial communities to global change depends on the plant community. We characterized bacterial and fungal communities from 395 plant litter samples taken from the Loma Ridge Global Change Experiment, a decade-long global change experiment in Southern California that manipulates rainfall and nitrogen levels across two adjacent ecosystems, a grassland and a coastal sage scrubland. The differences in bacterial and fungal composition between ecosystems paralleled distinctions in plant community composition. In addition to the direct main effects, the global change treatments altered microbial composition in an ecosystem-dependent manner, in support of our hypothesis. The interaction between the drought treatment and ecosystem explained nearly 5% of the variation in bacterial community composition, similar to the variation explained by the ecosystem-independent effects of drought. Unexpectedly, we found that the main effect of drought was approximately four times as strong on bacterial composition as that of nitrogen addition, which did not alter fungal or plant composition. Overall, the findings underscore the importance of considering plant–microbe interactions when considering the transferability of the results of global change experiments across ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Global Market and Economic Welfare Implications of Changes in Agricultural Yields Due to Climate Change

The economic welfare effects of climate change on global agriculture will be mediated by several complex biophysical and economic processes. For a given emissions scenario, these include: (1) the response of the climate system to anthropogenic forcing, (2) the response of crop yields to climate system and carbon dioxide changes, given baseline improvements in crop yields, (3) the response of agricultural markets to crop yield changes, and (4) the economic welfare implications of such market responses. In this paper, we use information about the first two processes from available climate-crop model comparison studies to analyze implications for the third and fourth processes. Applying the range of crop yield changes in a Global Integrated Assessment Model (GCAM) highlights several important economic relationships. First, we find a consistent relationship between global cropland area and yield change that is approximately orthogonal to the relationship between regional cropland area and yield change. Second, we find that the change in economic welfare, expressed as total surplus change per unit economic output, peaks during the 21st century. Third, we find that, at the global level, changes in yield affect both producer surplus and consumer surplus. Specifically, surplus changes to producers and consumers are always opposite in sign, although which economic actors gain or lose varies with the sign of yield change for any given commodity. Taken together, these results contribute to a growing body of research on climate-induced changes on agriculture by highlighting several economic relationships that are robust to differences in the underlying biophysical responses.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Methodology to Assess the Changing Risk of Yield Failure Due to Heat and Drought Stress Under Climate Change

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

Climate risk assessment↗

NASA NTRS2012

Seismic Rate Changes Associated with Seasonal, Annual, and Decadal Changes in the Cryosphere

Near the Bering Glacier Global Fiducial site in southern Alaska large cryospheric fluctuations occur in a region of upper crustal faulting and folding associated with collision and accretion of the Yakutat terrane. In this study we report constraints on seasonal, annual and decadal cryospheric changes estimated over the last decade from field, aircraft and satellite measurements, and we evaluate the influence of cryospheric changes on the background seismic rate. Multi-year images from the Bering Glacier global fiducial site are available since mid-2003 to constrain changes in extent of the Bering Glacier and to discern feature changes in the glacial surface. Starting around the same time, satellite gravimetric measurements from the Gravity Recovery and Climate experiment (GRACE) commenced. Large spatial-scale mass change calculated from the GRACE 1deg x 1deg mascon solution of Luthcke et al. [2012] indicate a general trend of annual ice mass loss for southern Alaska but with large, variable seasonal mass fluctuations. Since 2007, the station position of a continuous GPS site near Cape Yakataga (Alaska EarthScope PBO site, AB35) has been available as well. In addition to changes in the geodetic position due to tectonic motion, this GPS station shows large seasonal excursions in the detrended vertical and horizontal position components consistent with snow loading in the fall and winter and melt onset/mass decrease in the spring/summer. To better understand the timing of processes responsible for the onset of cryospheric mass loss documented in the GRACE data, we examined changes in the snow cover extent and the onset of melt in the spring. We calculated the surface displacements of the solid Earth and theoretical earthquake failure criteria associated with these annual and seasonal ice and snow changes using layered elastic half-space. Additionally, we compared the seismic rate (M>1.8) from a reference background time period against other time periods with variable ice or tectonic change characteristics to test the significance of seismic rate changes. Our earlier results suggest statistically significant changes in the background seismic rate associated with large seasonal mass changes. INDEX

Sauber-Rosenberg, Jeanne↗

NASA NTRSDate not supplied

Relating Changing Aerosols to Changing Clouds: Two Decades of Terra and Aqua Observations

The global aerosol system of today is not the same as it was two decades ago when Terra and Aqua were launched. As a result of a changing climate (natural and anthropogenic) convolved with changes in human activity (deliberate and accidental), some regions have experienced significant changes to their total aerosol burden (increases or decreases of total loading) or their aerosol composition (as defined by relative size or source type). Other regions have had less or no significant changes. At the same time, changes in aerosol amount and composition affect clouds through direct and indirect microphysical and radiative processes. We can theoretically predict what might happen to clouds when you add aerosol to an otherwise pristine environment. Conversely, there is the situation of removing aerosol from a polluted environment. Over the past two decades, sensors on both Earth Observing Satellites (Terra and Aqua) have observed the radiative signatures of aerosols and clouds, as well as their changes. Via massive efforts by their respective characterization teams, the resulting data records appear to have a minimum of artificial drifts. Therefore, we are trying to assess, region by region, our 20-year records of aerosols and clouds, along with meteorological variables. Where have been the most significant changes of aerosols and/or clouds? Where do the changes in clouds conform with expectations based on changes of aerosols and meteorology and where do they not? In addition to separate ‘aerosol’ and ‘cloud’ retrievals from the Moderate Resolution Imaging Spectrometer (MODIS), there is a ‘twilight zone’ that is not accounted for in either product. What are these regions, and have they changed over the past two decades? We will present our early efforts at characterizing the MODIS view of aerosol and cloud changes, while also relating to changes in radiative fluxes at the top-of-atmosphere (TOA) from corresponding observations by the Clouds and the Earth's Radiant Energy System (CERES).

aerosols↗

DOE OSTI2020

Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2

Anthropogenic land-use and land-cover change activities play a critical role in Earth system dynamics through significant alterations to biogeophysical and biogeochemical properties at local to global scales. To quantify the magnitude of these impacts, climate models need consistent land-cover change time series at a global scale, based on land-use information from observations or dedicated land-use change models. However, a specific land-use change cannot be unambiguously mapped to a specific land-cover change. Here, nine translation rules are evaluated based on assumptions about the way land-use change could potentially impact land cover. Utilizing the Global Land-use Model 2 (GLM2), the model underlying the latest Land-Use Harmonization dataset (LUH2), the land-cover dynamics resulting from land-use change were simulated based on multiple alternative translation rules from 850 to 2015 globally. For each rule, the resulting forest cover, carbon density and carbon emissions were compared with independent estimates from remote sensing observations, U.N. Food and Agricultural Organization reports, and other studies. The translation rule previously suggested by the authors of the HYDE 3.2 dataset, that underlies LUH2, is consistent with the results of our examinations at global, country and grid scales. This rule recommends that for CMIP6 simulations, models should (1) completely clear vegetation in land-use changes from primary and secondary land (including both forested and non-forested) to cropland, urban land and managed pasture; (2) completely clear vegetation in land-use changes from primary forest and/or secondary forest to rangeland; (3) keep vegetation inland-use changes from primary non-forest and/or secondary non-forest to rangeland. Our analysis shows that this rule is one of three (out of nine)rules that produce comparable estimates of forest cover, vegetation carbon and emissions to independent estimates and also mitigate the anomalously high carbon emissions from land-use change observed in previous studies in the 1950s. According to the three translation rules, contemporary global forest area is estimated to be 37.42×106 km2, within the range derived from remote sensing products. Likewise, the estimated carbon stock is in close agreement with reference biomass datasets, particularly over regions with more than 50 % forest cover

58 GEOSCIENCES↗

NASA NTRS2005

AO/NAO Response to Climate Change: Respective Influences of Stratospheric and Tropospheric Climate Changes - 1

We utilize the GISS Global Climate Middle Atmosphere Model and 8 different climate change experiments, many of them focused on stratospheric climate forcings, to assess the relative influence of tropospheric and stratospheric climate change on the extratropical circulation indices (Arctic Oscillation, AO; North Atlantic Oscillation, NAO). The experiments are run in two different ways: with variable sea surface temperatures (SSTs) to allow for a full tropospheric climate response, and with specified SSTs to minimize the tropospheric change. The results show that tropospheric warming (cooling) experiments and stratospheric cooling (warming) experiments produce more positive (negative) AO/NAO indices. For the typical magnitudes of tropospheric and stratospheric climate changes, the tropospheric response dominates; results are strongest when the tropospheric and stratospheric influences are producing similar phase changes. Both regions produce their effect primarily by altering wave propagation and angular momentum transports, but planetary wave energy changes accompanying tropospheric climate change are also important. Stratospheric forcing has a larger impact on the NAO than on the AO, and the angular momentum transport changes associated with it peak in the upper troposphere, affecting all wavenumbers. Tropospheric climate changes influence both the A0 and NAO with effects that extend throughout the troposphere. For both forcings there is often vertical consistency in the sign of the momentum transport changes, obscuring the difference between direct and indirect mechanisms for influencing the surface circulation.

Rind, D.↗

NASA NTRS2005

AO/NAO Response to Climate Change: Relative Importance of Low- and High-Latitude Temperature Changes - 2

Using a variety of GCM experiments with various versions of the GISS model, we investigate how different aspects of tropospheric climate changes affect the extratropical Arctic Oscillation (AO)/North Atlantic Oscillation (NAO) circulation indices. The results show that low altitude changes in the extratropical latitudinal temperature gradient can have a strong impact on eddy forcing of the extratropical zonal wind, in the sense that when this latitudinal temperature gradient increases, it helps force a more negative AO/NAO phase. In addition, local conditions at high latitudes can stabilize/destabilize the atmosphere, inducing negative/positive phase changes. To the extent that there is not a large temperature change in the tropical upper troposphere (either through reduced tropical sensitivity at the surface, or limited transport of this change to high levels), the changes in the low level temperature gradient can provide the dominate influence on the extratropical circulation, so that planetary wave meridional refraction and eddy angular momentum transport changes become uncorrelated with potential vorticity transports. In particular, the climate change that produces the most positive NAO phase change would have substantial warming in the tropical upper troposphere over the Pacific Ocean, with high latitude warming in the North Atlantic. An increase in positive phase of these circulation indices is still more likely than not, but it will depend on the degree of tropical and high latitude temperature response and the transport of low level warming into the upper troposphere. These are aspects that currently differ among the models used for predicting the effects of global warning, contributing to the lack of consensus of future changes in the AO/NAO.

Rind, D.↗

NASA NTRS2016

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Jagge, Amy↗

DOE OSTI2024

Impacts of Forest Management-Induced Productivity Changes on Future Land Use and Land Cover Change

Anthropogenic land use and land cover change (LULCC) is projected to continue in the future. However, the influence of forest management on forest productivity change and subsequent LULCC projections remains under-investigated. This study explored the impacts of forest management-induced change in forest productivity on LULCC throughout the 21st century. Specifically, we developed a framework to softly couple the Global Change Analysis Model and Global Timber Model to consider forest management-induced forest productivity change and projected future LULCC across the five Shared Socioeconomic Pathways (SSPs). We found future increases in forest management intensity overall drive the increase of forest productivity. The forest management-induced forest productivity change shows diverse responses across all SSPs, with a global increase from 2015 to 2100 ranging from 3.9% (SSP3) to 8.8% (SSP1). This further leads to an overall decrease in the total area with a change of land use types, with the largest decrease under SSP1 (-7.5%) and the smallest decrease under SSP3 (-0.7%) in 2100. Among land use types, considering forest management-induced change significantly reduces the expansion of managed forest and also reduces the loss of natural land in 2100 across SSPs. This suggests that ignoring forest management-induced forest productivity change underestimates the efficiency of wood production, overestimates the managed forest expansion required to meet the future demand, and consequently, potentially introduces uncertainties into relevant analyses, for example, carbon cycle and biodiversity. Thus, we advocate to better account for the impacts of forest management in future LULCC projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Detection and attribution (D&A) of forced precipitation change are challenging due to internal variability, limited spatial, and temporal coverage of observational records and model uncertainty. These factors result in a low signal-to-noise ratio of potential regional and even global trends. Here, we use a statistical method – ridge regression – to create physically interpretable fingerprints for the detection of forced changes in mean and extreme precipitation with a high signal-to-noise ratio. The fingerprints are constructed using Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model output masked to match coverage of three gridded precipitation observational datasets – GHCNDEX, HadEX3, and GPCC – and are then applied to these observational datasets to assess the degree of forced change detectable in the real-world climate in the period 1951–2020. We show that the signature of forced change is detected in all three observational datasets for global metrics of mean and extreme precipitation. Forced changes are still detectable from changes in the spatial patterns of precipitation even if the global mean trend is removed from the data. This shows the detection of forced change in mean and extreme precipitation beyond a global mean trend is robust and increases confidence in the detection method's power as well as in climate models' ability to capture the relevant processes that contribute to large-scale patterns of change. We also find, however, that detectability depends on the observational dataset used. Not only coverage differences but also observational uncertainty contribute to dataset disagreement, exemplified by the times of emergence of forced change from internal variability ranging from 1998 to 2004 among datasets. Furthermore, different choices for the period over which the forced trend is computed result in different levels of agreement between observations and model projections. These sensitivities may explain apparent contradictions in recent studies on whether models under- or overestimate the observed forced increase in mean and extreme precipitation. Lastly, the detection fingerprints are found to rely primarily on the signal in the extratropical Northern Hemisphere, which is at least partly due to observational coverage but potentially also due to the presence of a more robust signal in the Northern Hemisphere in general.

54 ENVIRONMENTAL SCIENCES↗

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

Quattrochi, Dale A.↗

DOE OSTI2025

Potential Effects of Climate Change and Solar Radiation Modification on Renewable Energy Resources

Solar radiation modification (SRM) is a possible deliberate approach to decrease or reflect incoming solar radiation with the goal of reducing global temperatures, which have increased over the last decades due to high atmospheric greenhouse gas concentrations. Stratospheric aerosol injection, specifically, has shown potential for successfully reducing global temperatures in climate model simulations. Despite the growing literature in the areas of climate change and SRM, their combined effects on renewable energy generation, a climate change mitigation strategy, have not been addressed. In this review paper, we synthesize previous literature on the possible effects of climate change and SRM on renewable energy resources (i.e., wind energy, solar energy, biomass energy, and hydropower), review the status of climate change and SRM research, and explore potential effects of SRM on renewable energy primarily in the Continental United States (CONUS), but with global perspectives as well. We discuss the research challenges and impacts of SRM on renewable energy and conclude by discussing the potential implications of SRM for renewables for SRM governance and policy. This work is not advocating for or against SRM. It is highlighting an important potential impact for future decision makers.

Kumler, Andrew [National Renewable Energy Laborato↗

DOE OSTI2021

Genetic and plastic rewiring of food webs under climate change

Not provided.

Environmental Sciences & Ecology↗