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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗
DOE OSTI2026

The relative importance of wind and hydroclimate drivers in modulating the interannual variability of dust emissions in Earth system models

Windblown dust emissions are controlled by near-surface wind speed and sediment erodibility, the latter modulated by hydroclimate and land-use conditions. Accurate representations of these drivers are critical for reproducing historical dust variability and projecting future dust changes in Earth system models (ESMs). This study examines the discrepancies among 21 ESMs in the relative importance of wind speed versus five hydroclimate drivers in explaining the historical (1980–2014) variability of dust emissions from global drylands. In hyperarid areas, models show poor agreement in the simulated dust variability, with only 9 % out of 210 inter-model comparisons exhibiting significant positive correlations. In contrast, arid and semiarid areas exhibit a dual pattern driven by a “double-edged sword” effect of land surface memory: models with coherent hydroclimate variability show better agreement, whereas those with divergent hydroclimate representations show larger disagreement. While the ESMs capture the dominant role of wind speed in hyperarid areas, they diverge markedly in the relative contributions of wind and hydroclimate drivers in arid and semiarid areas. Replacing the Zender et al. (2003) dust scheme with the Kok et al. (2014) scheme in CESM and E3SM generally strengthens hydroclimate influences while reducing wind speed contributions to simulated dust variability. MERRA-2 reanalysis produces stronger wind influences than most ESMs across all dryland regions. These results underscore the need for improved near-surface wind simulations in hyperarid areas and more realistic land surface and hydroclimate representations in arid and semiarid areas to reduce uncertainties in global dust emission simulations.

Li, Xinzhu [Michigan Technological University, Hou↗
DOE OSTI2025

Global Carbon Budget 2024

Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC) are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The global net uptake of CO2 by the ocean (SOCEAN, called the ocean sink) is estimated with global ocean biogeochemistry models and observation-based fCO2 products (fCO2 is the fugacity of CO2). The global net uptake of CO2 by the land (SLAND, called the land sink) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The sum of all sources and sinks results in the carbon budget imbalance (BIM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2023, EFOS increased by 1.3 % relative to 2022, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (10.3 ± 0.5 GtC yr−1 when the cement carbonation sink is not included), and ELUC was 1.0 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.9 GtC yr−1 (40.6 ± 3.2 GtCO2 yr−1). Also, for 2023, GATM was 5.9 ± 0.2 GtC yr−1 (2.79 ± 0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 2.3 ± 1.0 GtC yr−1, with a near-zero BIM (−0.02 GtC yr−1). The global atmospheric CO2 concentration averaged over 2023 reached 419.31 ± 0.1 ppm. Preliminary data for 2024 suggest an increase in EFOS relative to 2023 of +0.8 % (−0.2 % to 1.7 %) globally and an atmospheric CO2 concentration increase by 2.87 ppm, reaching 422.45 ppm, 52 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2023, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living-data update documents changes in methods and datasets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2024 (Friedlingstein et al., 2024).

Friedlingstein, Pierre (ORCID:0000000333094739)↗
DOE OSTI2026

Global Carbon Budget 2025

Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise datasets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO 2 emissions (E FOS ) are based on energy and cement production data. Emissions from land-use change (E LUC ) are estimated by bookkeeping models based on land-use data. The global atmospheric CO 2 growth rate (G ATM ) is computed from changes in concentration measured at surface stations. The global net uptake of CO 2 by the ocean (S OCEAN ) is estimated with global ocean biogeochemistry models and observation-based fCO 2 -products. The global net uptake of CO 2 by the land (S LAND ) is estimated with dynamic global vegetation models. Additional lines of evidence are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. This year, we introduced corrections on the E LUC , S OCEAN and S LAND estimates. The sum of all sources and sinks results in the carbon budget imbalance (B IM ), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ± 1σ. For the year 2024, E FOS increased by 1.1 % relative to 2023, with fossil emissions at 10.3 ± 0.5 GtC yr −1 (including the cement carbonation sink, 0.2 GtC yr −1 ), E LUC was 1.3 ± 0.7 GtC yr −1 , for total anthropogenic CO 2 emissions of 11.6 ± 0.9 GtC yr −1 (42.4 ± 3.2 GtCO2 yr −1 ). Also, for 2024, G ATM was 7.9 ± 0.2 GtC yr−1 (3.73 ± 0.1 ppm yr −1 ), 2.2 GtC above the 2023 growth rate. SOCEAN was 3.4 ± 0.4 GtC yr −1 and S LAND was 1.9 ± 1.1 GtC yr −1 , leaving a large negative B IM (−1.7 GtC yr −1 ), suggesting that the total sink or G ATM is strongly overestimated in 2024. The global atmospheric CO 2 concentration averaged over 2024 reached 422.8 ± 0.1 ppm. Preliminary data for 2025 suggest an increase in E FOS relative to 2024 of +1.0 % (0.2 % to 1.7 %) globally, and atmospheric CO 2 concentration increasing by 2.1 ppm reaching 425.6 ppm, 53 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr −1 persist for the representation of annual to decadal variability in CO 2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO 2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the mean ocean sink. This living data update documents changes in methods and datasets applied to this most-recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2025 (Friedlingstein et al., 2025c).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Analysis of Land-Use Effects on Landscape Patterns and Biological Diversity in Pacific North Forests: 1972-1991

While there is widespread recognition of the importance of preserving biological diversity there is considerable uncertainty about how to map current patterns of diversity and monitor changes through time. Ground-based approaches are impractical for examining regional patterns of biological diversity, for monitoring change, and they may actually overlook important higher-order phenomena. Thus, there is a critical need for innovative techniques to examine land-use effects on biological diversity at the landscape and regional scales. In this project, we have used satellite-based remote sensing to examine land-use effects on forest ecosystems in the Pacific NorthWest region (PNW) of the U.S.A. Rates and patterns of forest change throughout the region were quantified for the period from 1972 to 1993. This information was then used to map changes in the abundance and distribution of potential habitat for selected vertebrate species. The results of this project will be useful for identifying "keystone" stands that are important in maintaining habitat connectivity at the regional scale and for evaluating the impact of future land-use on vertebrate diversity throughout the region. The approaches developed here will also be useful in other forested regions throughout the world.

Wallin, David O.↗
DOE OSTI2025

A framework for testing soil carbon dynamics post land-use transition in a multisector dynamics model

Soil carbon plays a crucial role in the global carbon cycle. Changes in land use can determine whether carbon is stored or is emitted into the atmosphere as carbon dioxide, which has broad implications for the human and Earth systems. These feedbacks to the carbon cycle and their socio-economic drivers are modelled by many global multisector dynamics models to project future possibilities for the human-Earth system. One notable model of this class is the Global Change Analysis Model (GCAM), which uses a simplified process to model soil organic carbon (SOC) content after land-use transition across 384 land units. While the current GCAM soil carbon framework is based on scientific principles, it has not been tested against experimental data. This work examines rates of SOC change from GCAM input data. Specifically, first order rate constants derived from model inputs were compared to values from two syntheses to assess GCAM’s accuracy. Welch’s t-tests and linear models were used to determine if rate constants were consistent across all tested geographical areas and land-use transition types. While we found that there was general agreement on the direction and magnitude (i.e., rate) of SOC change, the rate constant derived from GCAM and empirical values differed strongly in a subset of specific instances. These results indicate that GCAM’s current SOC dynamics during land use transition successfully capture broad patterns of change in this critical carbon pool, but should be interpreted with caution at finer spatial scales. One potential cause of these discrepancies is our highly aggregated variable, soil timescale, which could be made more granular to improve accuracy. When using economically rooted multisector dynamics models, such as GCAM, it is critical to understand such model limitations for representing specific Earth system processes.

carbon↗
NASA NTRS1998

Perspective: Climate Forcings in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗
NASA NTRS1998

Climate Forcing in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗
NASA NTRS1999

Climate Simulations of Past, Present and Future

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗
NASA NTRS1998

Climate Forcings in the Industrial Era

The forcings that drive long-term climate change are not known with an accuracy sufficient to define future climate change. Anthropogenic greenhouse gases (GHGs), which are well measured, cause a strong positive (warming) forcing. But other, poorly measured, anthropogenic forcings, especially changes of atmospheric aerosols, clouds, and land-use patterns, cause a negative forcing that tends to offset greenhouse warming. One consequence of this partial balance is-that the natural forcing due to solar irradiance changes may play a larger role in long-term climate change than inferred from comparison with GHGs alone. Current trends in GHG climate forcings are smaller than in popular "business as usual" or 1% per year CO2 growth scenarios. The summary implication is a paradigm change for long-term climate projections: uncertainties in climate forcings have supplanted global climate sensitivity as the predominant issue.

Hansen, James E.↗
DOE OSTI2025

Community civic capacities for meaningful engagement in siting infrastructure for the energy transition

To address the driving forces of climate change and to ensure society has reliable and plentiful energy, considerable amounts of new energy infrastructure will need to be built in scores of communities over the near future. Democratic societies give communities considerable authority, influence, and autonomy on land-use decisions and regulatory policy making. Involving community members and stakeholders in decision making about facility siting and hosting is vital to minimize local opposition. But while there is much written about how to engage communities successfully, there is comparatively little attention given to understanding the civic capacities communities need to be able to participate. This paper reviews literatures on civic capacity and presents a new taxonomy based on six categories: leadership, knowledge, resources, civic engagement, social capital, and culture. It then proposes a systems framework to convey how capacities are developed and employed in collaborative decision making processes about siting and hosting energy facilities. Project sponsors, regulators, stakeholder groups, and communities can use these insights to better prepare and empower communities to participate as equal partners in conversations about energy facility siting.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics

Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.

14 SOLAR ENERGY↗
DOE OSTI2024

Anthromes and forest carbon responses to global change

Human effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling. Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900-present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO 2 and temperature change for different anthromes among regions. Modeled global forest carbon stock responses are positive for CO 2 increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO 2 and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests. The net effect of anthropogenic activities—including land-use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Future Spatially Explicit Patterns of Land Transitions in the United States With Multiple Stressors

Climate change, income and population growth, and changing diets are major drivers of the global food system with implications for land use change. Land use in the U.S. will be affected directly by local and regional forces and indirectly through international trade. In order to investigate the effects of several potential forces on land use changes in the U.S., we advanced capabilities in representing the interactions between natural and human systems by linking a multisectoral and multiregional socio-economic model of the world economy to a model that downscales land use to a 0.5°grid scale. This enables us to translate regional projections of future land use into higher-resolution representations of time-evolving land cover (effectively spatially explicit land use transitions). We applied the framework over the U.S., with a particular interest in the Mississippi River Basin and its four sub-basins, to consider how a range of global drivers affect land use and cover in the target regions. Our results show that under scenarios of high pressure on the world food system a comparative advantage in livestock production amplifies the recent trend toward less cropland and more pastures in the U.S. Under low pressures on the world food system agricultural land is used less intensively. However, there can be key differences among the various land-use transitions at the sub- basin scale. Overall, these results highlighted the need for high resolution details to explicitly understand the implications of land use change on environmental impacts such as carbon storage, soil erosion, chemical use, hydrology, and water quality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

United States multi-sector land use and land cover base maps to support human and Earth system models

Abstract Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Oliver, Jay↗
DOE OSTI2026

IAM-FIRE: a Climate Emulator–Based Framework to Project Wildfire Impacts and Risks for Integrated Assessment Models

Most Integrated Assessment Models (IAMs) underrepresent dynamic feedbacks from climate-driven disturbances such as wildfires, potentially overestimating the permanence of land-based carbon sinks. In particular, representing the impacts of forest fires is becoming increasingly important, as these are expected to intensify in the coming years. We introduce IAM-FIRE (Integrated Assessment Model – Fire Impacts & Risks Emulator), a novel framework that enables the projection of wildfire burned area (BA) and carbon emissions (CE) directly from IAM outputs. IAM-FIRE combines a spatial climate emulator, land-use downscaling, vegetation productivity modelling, and an empirical fire model to generate global annual wildfire impacts for arbitrary socioeconomic and emissions scenarios at 0.5° resolution for the period 2020–2100. Calibrated against GFEDv5 observations and using inputs from the Global Change Analysis Model (GCAM), we report projections BA and CE derived from IAM-FIRE for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-6.6 and SSP5-7.6. The model reproduces historical global trends for total BA, including the observed global decline since the early 2000s, and for forest BA. Projected fire trajectories differ strongly among scenarios: total BA range from declines under SSP1-2.6 (-3.36 Mha yr-1) to increases under SSP3-6.6 (+1.6 Mha yr-1). Corresponding total CE show a similar divergence ranging from -15 to +10.6 TgC yr-1. Socioeconomic development exerts a dominant suppressing effect on wildfire impacts while climate change and CO2-driven increases in vegetation productivity amplify fire risk, particularly under high-emissions pathways. Compared with CMIP6 fire-enabled Earth System Models, IAM-FIRE exhibits greater sensitivity to radiative forcing and a stronger role for human-driven fire suppression, highlighting substantial structural uncertainties in future fire projections. By providing a computationally efficient and internally consistent approach to represent wildfire impacts within IAMs, IAM-FIRE enables systematic exploration of fire–climate–land feedbacks and supports improved assessments of mitigation permanence and climate risks in future integrated scenarios.

Rouhette, Theo↗
DOE OSTI2025

Geospatial Diffusion for Land Cover Imperviousness Change Forecasting

Land-use and land-cover (LULC) has a significant effect on several Earth system processes. For example, impervious surfaces reduce infiltration and speed water flow, impacting regional hydrology and flood risk. While Earth System models have improved forecasting hydrologic and atmospheric processes at higher resolutions, the ability to forecast LULC change has lagged behind. In this paper, we propose a new paradigm exploiting Generative AI (GenAI) for land cover change forecasting by framing it as a data synthesis problem conditioned on historical and auxiliary data-sources. To demonstrate the feasibility of our methodology, we perform experiments where a diffusion model is trained for decadal forecasting of imperviousness change across the entire United States. We find that our model yields MAE lower than a no-change baseline for resolutions ≥ 0.7 X 0.7km2 on average, demonstrating its ability to capture and project accurate spatiotemporal patterns. Finally, we discuss future research to incorporate Earth's physical properties and enabling scenario simulations via driver variables.

Varshney, Debvrat [ORNL] (ORCID:0000000188981736)↗
DOE OSTI2026

CLM5 Simulations of Soil Moisture and Grain Carbon for CONUS at 0.125 degrees

This dataset provides 0.125° gridded simulations of soil moisture and crop grain carbon for the Contiguous United States (CONUS), generated using the Community Land Model version 5 (CLM5) with the biogeochemistry module enabled. The data covers a historical baseline (1980–2015) and mid-century future projections (2020–2055). Future projections are organized into two sets of scenarios to distinguish the impacts of different drivers: (1) Atmospheric Only (ATM-only): These scenarios apply future atmospheric forcings while holding land use and land cover change (LULCC) at historical baseline levels. The atmospheric forcings represent moderately versus severely hotter/drier atmospheric conditions (dynamically downscaled perturbed thermodynamics simulations based on CMIP6 SSP245 and SSP585 warming signals), each with cooler versus hotter Earth System Model temperature sensitivity instantiations. These scenarios are identified in the file names as atm45cooler, atm45hotter, atm85cooler, and atm85hotter. (2) Coupled Atmospheric and Land-Use (LAND+ATM): These scenarios apply future atmospheric forcing together with future LULCC by pairing atmospheric pathways with lower versus higher population/economic growth scenarios representing Shared Socioeconomic Pathways 3 and 5 (SSP3 and SSP5). These scenarios are identified in the file names as atm45cooler_ssp3, atm45hotter_ssp3, atm45cooler_ssp5, atm45hotter_ssp5, atm85cooler_ssp3, atm85hotter_ssp3, atm85cooler_ssp5, and atm85hotter_ssp5. Please refer to the README file for detailed information on file structure, variables, units, and data formats.

Yao, Lili [Pacific Northwest National Laboratory] ↗