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DOE OSTI2026

Ocean physical‐biogeochemical interactions in the CMIP6 and E3SM Earth System Models

The primary objectives of this project are to quantify the spatio‐temporal linkages between physical climate and ocean biogeochemical variables in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM), in CMIP6 Earth System Models (ESMs), and in historical observations, to evaluate the E3SM’s ability to reproduce the observations, and to develop a solid diagnostic package to do so. It will revolve around four hypotheses and will focus on key physical and biogeochemical processes that regulate the upper ocean carbon and oxygen cycling: water mass distribution, ventilation, and biological production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling

High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth system models (ESMs) and ultra-high-resolution urban climate modeling, over large domains. Here, we present U-Surf, a first-of-its-kind 1 km resolution present-day (circa 2020) global continuous urban surface parameter dataset. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for satisfying dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet and canopy level. Generated using a systematically unified workflow, U-Surf ensures internal consistency among key parameters, making it the first globally coherent urban canopy surface dataset. U-Surf significantly improves the representation of the urban land heterogeneity both within and across cities globally; provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs; enables detailed city-to-city comparisons across the globe; and supports next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf can also be used as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to advance the research frontier of urban system science, climate-sensitive urban design, and coupled human–Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247598 (Cheng et al., 2024).

Cheng, Yifan [Univ. of Illinois at Urbana-Champaig↗

NASA NTRSDate not supplied

Ocean and Earth System Modelling

Petascale supercomputing infrastructure + modelling and analysis capabilities + interdisciplinary upper-ocean expertise Multiscale ocean turbulence simulation Physical-biogeochemical interactions Analysis of large data sets from remote sensing and Earth system model ensembles

Ocean↗

DOE OSTI2026

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗

NASA NTRSDate not supplied

Climate Change Impact on Surface Ozone Based on CMIP6 Earth System Models

It is presented an analysis of the effect of climate change on surface ozone (O3) discussing the related penalties and benefits around the globe from the global modeling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. All models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions scenario (SSP3-7.0). Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration varying spatially from -0.2 to -2 ppbv oC-1, with strongest decline over tropical oceanic regions, which is mainly linked to the dominating role of enhanced ozone chemical loss with higher water vapour abudances under a warmer climate. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural Biogenic Volatile Organic Compounds (BVOC) emission sources with a rate ranging regionally from 0.2 to 2 ppbv oC-1, implying a regional surface ozone penalty due to global warming. The individual models show this robustly for south-eastern China and India as well as for regions of Africa but there are inter-model differences in areas within Europe and the United States (US) as well as in South America. The future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

climate change↗

DOE OSTI2025

Enhanced Simulation of Atmospheric Blocking in a High‐Resolution Earth System Model: Projected Changes and Implications for Extreme Weather Events

Atmospheric blocking is closely linked to the occurrence of extreme weather events. However, low-resolution Earth system models often underestimate the frequency of blocking, undermining confidence in future projections. Here, in this study, we use the high-resolution Community Earth System Model (CESM-HR; 25 km atm and 10 km ocean) to show that CESM-HR reduces biases in atmospheric blocking for both winter and summer, particularly for events lasting longer than 10 days. This improvement is partly due to reduced sea surface temperature biases at higher resolution. Additionally, applying a bias correction to the 500 hPa geopotential height further enhances blocking frequency simulations, highlighting the crucial role of the mean state. Under the Representative Concentration Pathway 8.5 scenario, CESM-HR projects a decrease in wintertime blocking over regions such as the Euro-Atlantic and Chukchi-Alaska, consistent with previous studies. In contrast, summer blocking is expected to become more frequent and persistent, driven by weakened zonal winds. The blocking center shifts from historical locations over Scandinavia and eastern Russia to central Eurasia, significantly increasing blocking over the Ural region. Summer blocking frequency over the Scandinavia-Ural region may eventually surpass historical winter blocking over the Euro-Atlantic. This increase in summer blocking could exacerbate summer heatwaves in a warming climate, making severe heatwaves, like those observed recently, more common in the future.

Atmospheric blocking↗

DOE OSTI2026

Benchmarking soil moisture and its relationship to ecohydrologic variables in Earth System Models

Soil moisture (SM) is a key regulator of ecosystem biogeophysics, influencing plant water relations and land-atmosphere energy exchanges. We evaluate the representation of SM in 16 Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) using the International Land Model Benchmarking (ILAMB) framework, focusing on surface (0–5, 0–10 cm) and rootzone (0–100 cm) depths, as well as key ecohydrological variables like gross primary productivity (GPP), leaf area index (LAI), and evapotranspiration (ET), and their coupling. Models are benchmarked against multiple observational and assimilated datasets to assess both state variables and cross-variable relationships. Surface SM is generally well represented (r > 0.87), while rootzone SM variability is systematically overestimated (normalized standard deviation > 1). ET shows strong agreement with observations (r > 0.9), whereas GPP and LAI exhibit larger inter-model spread. Skill in individual variables does not guarantee realistic SM–ecohydrology coupling, which varies strongly across models and depends on the reference dataset. Köppen-based regional analyses reveal strong regime dependence, with several models performing well in Tropical and Temperate regions but degrading in Continental (high-latitude) zones. Across both global and regional benchmarks, models cluster by land surface framework, indicating that structural choices in soil hydrology and soil–plant coupling exert a first-order control on performance. These results provide process-relevant benchmarks and suggest that improving the representation of vertical soil structure, rooting depth distributions, and soil–plant hydraulic coupling will be central to advancing soil moisture realism in next-generation Earth system models.

CMIP6↗

NASA NTRS2022

Climate Change Penalty and Benefit on Surface Ozone: A Global Perspective Based on CMIP6 Earth System Models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modelling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of −0.96 ± 0.07 ppbv °C−1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abundances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from −0.2 to −2 ppbv °C−1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural biogenic volatile organic compounds emission sources with a rate ranging regionally from 0.2 to 2 ppbv C−1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

surface ozone↗

DOE OSTI2024

Evaluation of Global Fire Simulations in CMIP6 Earth System Models

Fire is the primary form of terrestrial ecosystem disturbance on a global scale and an important Earth system process. Most Earth system models (ESMs) have incorporated fire modeling, with 19 of them submitting model outputs of fire-related variables to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study provides the first comprehensive evaluation of CMIP6 historical fire simulations by comparing them with multiple satellite-based products and charcoal-based historical reconstructions. Our results show that most CMIP6 models simulate the present-day global burned area and fire carbon emissions within the range of satellite-based products. They also capture the major features of observed spatial patterns and seasonal cycles, the relationship of fires with precipitation and population density, and the influence of the El Niño–Southern Oscillation (ENSO) on the interannual variability of tropical fires. Regional fire carbon emissions simulated by the CMIP6 models from 1850 to 2010 generally align with the charcoal-based reconstructions, although there are regional mismatches, such as in southern South America and eastern temperate North America prior to the 1910s and in temperate North America, eastern boreal North America, Europe, and boreal Asia since the 1980s. The CMIP6 simulations have addressed three critical issues identified in CMIP5: (1) the simulated global burned area being less than half of that of the observations, (2) the failure to reproduce the high burned area fraction observed in Africa, and (3) the weak fire seasonal variability. Furthermore, the CMIP6 models exhibit improved accuracy in capturing the observed relationship between fires and both climatic and socioeconomic drivers and better align with the historical long-term trends indicated by charcoal-based reconstructions in most regions worldwide. However, the CMIP6 models still fail to reproduce the decline in global burned area and fire carbon emissions observed over the past 2 decades, mainly attributed to an underestimation of anthropogenic fire suppression, and the spring peak in fires in the Northern Hemisphere midlatitudes, mainly due to an underestimation of crop fires. In addition, the model underestimates the fire sensitivity to wet–dry conditions, indicating the need to improve fuel wet-ness estimation. Based on these findings, we present specific guidance for fire scheme development and suggest a postprocessing methodology for using CMIP6 multi-model outputs to generate reliable fire projection products.

Wildfire, Earth system models↗

DOE OSTI2025

Mechanisms in Regulating the Quasi‐Biennial Oscillation in Exascale Earth System Model Version 2

Abstract The update to the deep convection parameterization in the energy exascale Earth system model version 2 (E3SMv2) makes the simulated quasi‐biennial oscillation (QBO) have a shorter period than without the update when other tunable parameters the same since the update makes convection more intense but less frequent while leaving the time‐mean convective heating tendency almost unchanged. Amplitudes of momentum fluxes of parameterized gravity waves (GWs) are intensified since they are determined by the square of convective heating tendency. In addition, stronger planetary waves are simulated in E3SMv2 with the convection scheme update, partially due to the tropospheric precipitation change. Furthermore, there is evidence that planetary waves are intensified in the stratosphere due to the dissipation of enhanced parameterized GWs. These factors are found to be responsible for modulating the QBO simulated in E3SMv2.

Li, Yuanpu [Climate and Global Dynamics Division U↗

NASA NTRS2021

Earth system modeling: can we stay ahead of what's actually happening?

Over the last forty years, Earth System Models have become more and more comprehensive and detailed. They have assimilated previously independent modeling efforts in ocean circulation, atmospheric composition, the stratosphere, land surface, and the cryosphere, and are today demonstrably more skillful than earlier efforts. Yet the structural uncertainty in the latest model projections is actually increasing. Meanwhile, impacts of climate change on, for instance, wildfires, tropical cyclones and sea level, appear to be increasing faster than we have been able to predict. I will address some of the current issues at the bleeding edges of model development and the continuing importance of model evaluation.

Gavin A Schmidt↗

DOE OSTI2025

Bias correcting regional scale Earth system model projections: novel approach using empirical mode decomposition

Bias correction is a crucial step in using Earth system model outputs for assessments, as it adjusts systematic errors by comparing the model to observations. However, standard methods – ranging from mean-based linear scaling to distribution-based quantile mapping typically treat bias correction as a single-scale process, overlooking the fact that biases can manifest differently across daily, seasonal, and annual timescales. In this study, we propose a novel, timescale-aware bias-correction approach built on Empirical Mode Decomposition. By decomposing the meteorological signal into multiple oscillatory components and aggregating them to represent distinct timescales, we apply targeted corrections to each component, thereby preserving both short- and long-term structure in the data. Experimental illustrations show that the timescale-aware EMDBC framework matches the performance of conventional quantile-delta mapping (QDM) at the native daily scale and achieves progressively larger bias reductions at bi-weekly, seasonal, and annual scales. As a result, the proposed approach offers a more robust path to accurate and reliable Earth system projections, strengthening their utility for resilience and adaptation planning.

Ganguli, Arkaprabha [Argonne National Laboratory (↗

DOE OSTI2026

Diagnosing the representation of surface and layered soil moisture in Earth system models

Surface soil moisture (mrsos) and vertically integrated soil moisture (mrsol) over the top 10 cm should, by definition, be physically consistent in Earth System Models (ESMs). However, an evaluation of nine CMIP6 models reveals substantial inconsistencies: in some models, mrsos and integrated mrsol agree globally; in others, they align only in specific regions; and in a few, they diverge across all grid cells. These discrepancies arise from a combination of factors, including metadata errors, inconsistent variable definitions, or diagnostic sequencing within the model. We demonstrate how such issues can lead to significant biases, even when both variables are present and seemingly well-defined. As model complexity increases and multi-model comparisons become more common, assumptions about variable equivalence may lead to flawed conclusions. This study highlights the need for routine consistency checks, improved metadata standards, and community-wide practices that ensure reliability of derived variables across ESM outputs, particularly in preparation for CMIP7.

Earth system models↗

DOE OSTI2026

Numerical Water Tracers in the Atmospheric Component of the Energy Exascale Earth System Model: Implementation and Changes in Moisture Origin

Numerical water tracers are implemented in the Energy Exascale Earth System Model version 2. Simulations performed with the water‐tag‐enabled model for both pre‐industrial and future greenhouse gas concentrations reveal a marked increase in the role of mid‐latitude and southern subtropical regions as exporters of atmospheric moisture—to the extratropical upper troposphere and the tropical free troposphere. For the latter, the northward shift of the Intertropical Convergence Zone increases cross‐hemispheric transport of subtropical water vapor to the Northern Hemisphere. In the polar regions, most of the lower tropospheric moistening instead arises from increases in local evaporation. These findings illustrate the utility of the water tags, underscore critical changes in global hydrologic cycle, and provide insight into atmospheric dynamics under future climate scenarios. For applications when a global grid is desired, we additionally propose a novel statistical reconstruction, based on copula modeling, of the joint distribution of origin of water vapor, which reduces the number of tracers from order $\mathcal{O}\left({n}^{2}\right)$to order $\mathcal{O}(n)$, substantially ameliorating the considerable computational cost of water tracers. This statistical reconstruction is particularly beneficial to the interpretation of the relationship between latitude and longitude of origin of moisture over the tropical oceans and in the lower troposphere over land.

copula modeling↗

DOE OSTI2025

The Energy Exascale Earth System Model Version 3: 1. Overview of the Atmospheric Component

This paper describes the atmospheric component of the US Department of Energy's Energy Exascale Earth System Model (E3SM) version 3. Significant updates have been made to the atmospheric physics compared to earlier versions. Specifically, interactive gas chemistry has been implemented, along with improved representations of aerosols and dust emissions. A new stratiform cloud microphysics scheme more physically treats ice processes and aerosol‐cloud interactions. The deep convection parameterization has been largely improved with sophisticated microphysics for convective clouds, making model convection sensitive to large‐scale dynamics, and incorporating the dynamical and physical effects of organized mesoscale convection. Improvements in aerosol wet removal processes and parameter re‐tuning of key aerosol and cloud processes have improved model aerosol radiative forcing. The model's vertical resolution has increased from 72 to 80 layers with the extra eight layers added in the lower stratosphere to better simulate the Quasi‐Biennial Oscillation. These improvements have enhanced E3SM's capability to couple aerosol, chemistry, and biogeochemistry and reduced some long‐standing biases in simulating tropical variability. Compared to its predecessors, the model shows a much stronger signal for the Madden‐Julian Oscillation, Kelvin waves, mixed Rossby‐gravity waves, and eastward inertia‐gravity waves. Aerosol radiative forcing has been considerably reduced and is now better aligned with community best estimates, leading to significantly improved skill in simulating historical temperature records. Its simulated mean‐state climate is largely comparable to E3SMv2, but with some notable degradation in shortwave cloud radiative effect, precipitable water, and surface wind stress, which will be addressed in future updates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Downscaled Earth System Model Data for Resilient Energy System Planning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. In this presentation, we explore the output characteristics of the dataset and various validation analyses. We also present and discuss plans for the integration of this data into power system planning models using a decision-making under deep uncertainty (DMDU) methodology.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2024

Assessing Acetone for the GISS ModelE2.1 Earth System Model

Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Acetone↗

NASA NTRS2021

Evaluation of SO2, SO4(2−) and an Updated SO2 Dry Deposition Parameterization in the United Kingdom Earth System Model

In this study we evaluate simulated surface SO2 and sulphate (SO4(2-)) concentrations from the United Kingdom Earth System Model (UKESM1) against observations from ground based measurement networks in the USA and Europe for the period 1987 to 2014. We find that UKESM1 captures the historical trend for decreasing concentrations of atmospheric SO2 and SO4(2-) in both Europe and the USA over the period 1987 to 2014. However, in the polluted regions of the eastern USA and Europe, UKESM1 over-predicts surface SO2 concentrations by a factor of 3, while under-predicting surface SO4(2-) concentrations by 25-35%. In the cleaner western USA, the model over-predicts both surface SO2 and SO4(2-) concentrations by a factor of 12 and 1.5 respectively. We find that UKESM1’s bias in surface SO2 and SO4(2-) concentrations is variable according to region and season. We also evaluate UKESM1 against total column SO2 from the Ozone Monitoring Instrument (OMI) using an updated data product. This comparison provides information about the model’s global performance, finding that UKESM1 over predicts total column SO2 over much of the globe, including the large source regions of India, China, the USA and Europe as well as over outflow regions. Finally, we assess the impact of a more realistic treatment of the model’s SO2 dry deposition parameterization. This change increases SO2 dry deposition to the land and ocean surfaces, thus reducing the atmospheric loading of SO2 and SO(sup 2-)(sub 4). In comparison with the ground-based and satellite observations, we find that the modified parameterization reduces the models over prediction of surface SO2 concentrations and total column SO2. Relative to the ground-based observations the simulated surface SO4(2-) concentrations are also reduced, while the simulated SO2 dry deposition fluxes increase.

SO2↗