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DOE OSTI2026

Understanding Biases in Simulated Cloud Radiative Effects in E3SMv3

This study systematically investigates biases in cloud radiative effects (CREs) within the recently released Energy Exascale Earth System Model version 3 (E3SMv3). Compared to its previous version (E3SMv2), E3SMv3 shows excessively strong shortwave CRE over tropical and subtropical oceans, the Southern Ocean, and the Northern Hemisphere storm tracks, which is primarily caused by an overestimation of optically intermediate low clouds. The model also displays excessive longwave CRE over the Maritime Continent and other tropical deep convection regions, resulting from an overestimation of optically thick high clouds. Implementing the Predicted Particle Properties (P3) scheme for stratiform clouds played the most significant role in these cloud changes. In addition, using a double-moment scheme for convective clouds contributed to the increase in intermediate low clouds and optically thick clouds in tropical deep convection regions. Error metrics for total cloud amount (E TCA ), cloud properties (E ctp-τ ), and cloud properties weighted by their SW and LW radiative impacts (E SW and E LW ) indicate that E3SMv3's ability to reproduce observed cloud radiative effect of low, middle, and high clouds has not been improved compared to E3SMv2. Nevertheless, the performance of E3SMv3 remains well within the spread of CMIP6 models, with E SW and E LW values smaller than those in most CMIP6 models. This study underscores the importance of integrating diverse satellite observations for robust cloud evaluation and using cloud-radiation relationships as consistency check for model errors. It suggests that further model developments focus on improving cloud microphysics and their interactions with radiation.

Environmental sciences↗

DOE OSTI2025

Cloud radiative effect dominates variabilities of surface energy budget in the dark Arctic

Climate models simulate a wide range of temperatures in the Arctic. Here we investigate one of the main drivers of changes in surface temperature: the net surface heat flux in the models. We show that in the winter months of the dark Arctic, there is a more than two-fold difference in the net surface heat fluxes among the models, and this difference is dominated by the downward infrared radiation from clouds. Owing to the small amount of water vapor in the winter Arctic, infrared radiation from clouds transmits more easily to the surface in the Arctic than at other latitudes, resulting in large cloud radiative effect at the surface. The dominant role of the cloud effect is also found in the transient variability of the net surface heat flux. Results demonstrate that accurate simulation of clouds is crucial for determining the net surface heat flux, which in turn affects surface temperature and sea ice properties in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Assessing modifications to the Abdul-Razzak and Ghan aerosol activation parameterization (version ARG2000) to improve simulated aerosol–cloud radiative effects in the UK Met Office Unified Model (UM version 13.0)

The representation of aerosol activation is a key source of uncertainty in global composition-climate model simulations of aerosol–cloud interactions. The Abdul-Razzak and Ghan (ARG) activation parameterization is used in several global and regional models that employ modal aerosol microphysics schemes. In this study, we investigate the ability of the ARG parameterization to reproduce simulations with a cloud parcel model and find its performance is sensitive to the geometric standard deviations (widths) of the lognormal aerosol modes. We recommend adjustments to three constant parameters in the ARG equations, which improve the performance of the parameterization for small mode widths and its ability to simulate activation in polluted conditions. For the accumulation mode width of 1.4 used in the Met Office Unified Model (UM), the modifications decrease the mean bias in the activated fraction of aerosols compared to a cloud parcel model from −6.6 % to +1.2 %. We implemented the improvements in the UM and compared simulated global cloud droplet concentrations with satellite observations. The simulated cloud radiative effect changes by −1.43 W m −2 (6 %) and aerosol indirect radiative forcing over the industrial period changes by −0.10 W m −2 (10 %).

Ghosh, Pratapaditya [Carnegie Mellon University, P↗

DOE OSTI2025

Cloud radiative effects significantly increase wintertime atmospheric blocking in the Euro-Atlantic sector

Reliable simulation, prediction, and complete theoretical understanding of atmospheric blocking remain challenging despite its significant socio-economic impacts. Generations of climate models have notoriously underestimated blocking frequency, particularly over the Euro-Atlantic sector. Identifying factors controlling blocking frequency and dynamics is therefore essential for improving its simulation. Here, using a cloud-locking experiment, we show that cloud radiative effects (CREs) significantly increase the frequency of Euro-Atlantic blocking. CREs enhance upstream diabatic source of wave activity, both directly through longwave heating and indirectly through their feedback on latent heating, with the latter playing the dominant role. The resulting increase in the upstream diabatic source feeds into local wave activity downstream and promotes blocking formation. Qualitatively similar results are shown by multi-model experiments with radiatively inactive clouds to longwave radiation, albeit with a larger impact from mean-state changes. The results underscore the necessity of accurately representing cloud-radiation interactions in weather and climate models for improved prediction of blocking events.

Atmospheric dynamics↗

DOE OSTI2025

Radiative forcing from the 2020 shipping fuel regulation is large but hard to detect

Reduction in aerosol cooling unmasks greenhouse gas warming, exacerbating the rate of future warming. The strict sulfur regulation on shipping fuel implemented in 2020 (IMO2020) presents an opportunity to assess the potential impacts of such emission regulations and the detectability of deliberate aerosol perturbations for climate intervention. Here we employ machine learning to capture cloud natural variability and estimate a radiative forcing of +0.074 ±0.005 W m -2 related to IMO2020 associated with changes in shortwave cloud radiative effect over three low-cloud regions where shipping routes prevail. We find low detectability of the cloud radiative effect of this event, attributed to strong natural variability in cloud albedo and cloud cover. Regionally, detectability is higher for the southeastern Atlantic stratocumulus deck. These results raise concerns that future reductions in aerosol emissions will accelerate warming and that proposed deliberate aerosol perturbations such as marine cloud brightening will need to be substantial in order to overcome the low detectability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Increasing wintertime cloud opacity increases surface longwave radiation at a long-term Arctic observatory

As the Arctic warms, winter clouds are known and expected to change. Yet the extent to which these cloud changes amplify or dampen warming (cloud feedback) remains uncertain. This uncertainty results from systemic difficulties in modeling and observing Arctic low clouds. Surface-based observations avoid many of these difficulties. Here, we use two decades of surface-based observations (1998–2023) to constrain and explain longwave flux change during winter. We find that longwave flux into the surface is increasing and that this increase cannot be explained by direct impacts of temperature and greenhouse gases alone. Only when increasing cloud radiative effect (0.96 ± 0.64 W/m 2 /K) is considered can increasing longwave flux be explained. Cloud radiative effect increases due to increasing cloud opacity, which is driven equally by ice-only and mixed-phase clouds. The direct observational constraint from this work suggests that increasing cloud opacity drives increasing net surface radiation on Alaska’s North Slope during winter.

Bertrand, Leah [Univ. of Colorado, Boulder, CO (Un↗

DOE OSTI2025

Cloud Feedback Uncertainty in the Equatorial Pacific Across CMIP6 Models

Cloud feedback is the largest uncertainty in estimating Equilibrium Climate Sensitivity. In this study we focus on the equatorial Pacific, where CMIP6 model cloud feedback spread is notably large. Cloud radiative effects in this region are relevant for the global climate. Our findings show that models predict a consistent shift towards the ascent regime in response to El Nino-like sea surface warming. Models diverge in terms of the radiative impact due to differences in cloud characteristics in ascent and subsidence regimes. Using the observed relationship between circulation regime and cloud radiative effect, we find a reduction in the regional mean cloud feedback estimate from 0.77 to 0.22 W m -2 K -1 , though this does not substantially lessen the model spread in total feedback. Pathways to reduce this spread include: improving confidence in the regional ocean warming pattern, and using observations and models to understand cloud type and circulation interactions.

CMIP6↗

DOE OSTI2026

Strong Sensitivity of Simulated Biomass Burning Aerosol Transport and Radiative Effects Over the South Atlantic to Carbonaceous Aerosol Aging and Particle Density

Biomass burning aerosol (BBA) impacts climate through aerosol‐cloud‐radiation interactions, but models disagree on the sign and magnitude of BBA radiative effects. We quantify the sensitivity of BBA radiative effects and transport to three BBA‐relevant processes and properties: parameterized oxidative aging of organic aerosol (OA), a combined change to black carbon (BC) density and the method for calculating aerosol refractive index, and reduction in OA density. We evaluate Unified Model simulations against two aircraft campaigns from summer 2017 over the Southeast Atlantic. The model generally performs well, such that discrepancies between the observational data sets may sometimes limit the precision of the evaluation. Our newly developed aging parameterization reproduces observed OA:BC mass ratios well and allows modeled OA:BC to decrease with smoke age, but increases bias in aerosol extinction and changes the BBA radiative effect little (+0.12 W m -2 ). We calculate aerosol refractive index using either a volume‐weighted component average or the Maxwell‐Garnett (MG) mixing assumption, which represents BC as small inclusions in a host material. Compared to MG mixing, the volume‐weighted average refractive index and reduced BC density increase aerosol absorption, substantially increasing the total BBA radiative effect (+2.66 W m -2 ) and amount of BBA transported across the ocean through BC self‐lofting. Reducing OA density to better match literature values changes the total BBA radiative effect by −1.96 W m -2 . Changes to direct radiative effects exceed changes to cloud radiative effects. Our findings emphasize the sensitivity of aerosol radiative effects and transport to these processes and properties, which we suggest could be improved in climate models.

Southeast Atlantic↗

DOE OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗

DOE OSTI2026

Prognostic simulations of mixed-phase clouds with model AC-1D v1.0: the impact of aerosol types and freezing parameterizations on ice crystal budgets

Mixed-phase clouds at high latitudes contribute to the uncertainty in predicting cloud feedbacks and climate sensitivity, mainly due to the complexity of microphysical processes that influence the partitioning between the supercooled liquid and ice phases, and hence, cloud radiative effects on regional scales. Particularly in Arctic mixed-phase clouds, the activation of ice-nucleating particles (INPs) from various aerosol populations remains a leading source of uncertainty. We developed an aerosol-cloud one-dimensional (AC-1D) model, which provides a novel framework to prognostically treat INP and ice crystal budgets while explicitly accounting for polydisperse and multicomponent aerosol that activate INPs following different freezing parameterizations. The AC-1D model is informed by large-eddy simulations to probe the impact of INP representation on predicted ice crystal number concentrations (N i ) and ice crystal budgets in mixed-phase Arctic stratus. We apply three immersion freezing (IMF) parameterizations, two time-independent (singular) and one time-dependent (classical nucleation theory), to predict the evolution of the INP reservoir and resulting ice crystal budget from polydisperse mineral dust, organic (humic-like substances), and sea spray aerosol particle size distributions. Our analysis focuses on how variations in aerosol number concentration and cloud system parameters such as cloud cooling rate, cloud-top entrainment rate, and ice crystal fall speed influence the INP reservoir and ice crystal budgets. Furthermore, this study investigates the competitive ice nucleation dynamics in mixed aerosol environments and provides a process-level quantification of the INP budget terms, which directly controls ice crystal budgets. For all studied case scenarios, the aerosol types and associated particle size distributions significantly impact INP and N i , and the choice between a time-dependent and a singular freezing description yields orders-of-magnitude differences in the predicted INP and N i over the 10 h simulation time, reflecting typical cloud lifetimes. Our results show that the influence of cloud cooling, INP entrainment, and sedimentation varies significantly depending on the chosen freezing parameterization. These findings underscore the critical need for robust IMF parameterizations and precise cloud system observations to enhance the accuracy of models in predicting mixed-phase cloud structure and evolution.

Arctic clouds↗

DOE OSTI2026

Exposing and Reducing Biases of Simulating Mixed-Phase Clouds in the Convection-Permitting E3SM Atmosphere Model: Lessons From an Arctic Cold-Air Outbreak

Mixed-phase clouds modulate the water and energy cycles of high-latitude regions, yet their liquid-ice phase partitioning has long been poorly simulated in climate models. Here, simulations of Arctic mixed-phase clouds by the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) are assessed against large-eddy simulations, satellite data, and ground-based observations during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment field campaign. SCREAM simulates nearly completely frozen clouds, which is attributed largely to the unreasonably strong Wegener–Bergeron–Findeisen (WBF) process that converts liquid to ice excessively and partly to the early over-abundant ice production at cold temperatures from a temperature-deterministic deposition ice nucleation scheme. Assuming no subgrid variation for the WBF process in the original formulation particularly conflicts with the instantaneous saturation adjustment assumption in the condensation scheme that assumes subgrid variability, leading to exaggerated WBF process rates. A proposed simple physically-based improvement on the treatment of subgrid cloud overlap substantially increases supercooled liquid water content and notably improves cloud-top phase partitioning, aligning better with observations. Improvement of supercooled liquid water content also converges with increasing horizontal resolution. The deposition ice nucleation scheme is found responsible for a falsely-produced ice cloud aloft that is not observed, biasing the simulated cloud radiative effects and top-of-atmosphere radiative fluxes. This study identifies key deficiencies in cloud parameterizations that continue to challenge convection-permitting models.

Geosciences↗

DOE OSTI2025

Resolving Low Cloud Feedbacks Globally With E3SM High‐Res MMF: Agreement With LES but Stronger Shortwave Effects

This study investigates low cloud feedback in a warmer climate using global simulations from the High-Resolution Multi-scale Modeling Framework (HR-MMF), which explicitly simulates small-scale eddies globally. Two 5-year simulations—one with present-day sea surface temperatures (SSTs) and a second with SSTs warmed uniformly by 4 K—reveal a positive global shortwave cloud radiative effect (SWCRE = 0.3 W/m 2 /K), comparable to estimates from CMIP models. As the climate warms, significant reductions in low cloud cover occur over stratocumulus regions. This study is the first attempt to compare HR-MMF results with predictions from idealized large-eddy simulations from the CGILS intercomparison. Despite different underlying assumptions, we find qualitative agreement in SWCRE and inversion height changes between HR-MMF and CGILS predictions. This suggests reasonable credibility for the CGILS framework in predicting cloud responses under the out-of-sample conditions found in HR-MMF. However, the HR-MMF exhibits stronger SWCRE changes than predicted by CGILS. We explore potential causes for this discrepancy, examining variations in cloud-controlling factors (CCFs) and cloud conditions. Our results show a fairly homogeneous SWCRE response, with little systematic variation tied to the variations in CCFs. This reveals a dominant role for SST forcing in modulating SWCRE.

boundary-layer clouds↗

DOE OSTI2026

Influence of Surface Aerosol Injection on Stratocumulus‐to‐Cumulus Transition: Cloud‐Surface Coupling and Background Aerosol Concentrations

The influence of surface aerosol injection on the stratocumulus‐to‐cumulus transition (SCT) is explored using large‐eddy simulations. We examine how cloud‐surface coupling (or the strength of the marine boundary layer (MBL) stratification that limits vertical turbulent mixing and convection) impacts the vertical transport of aerosols, and how injected aerosols influence cloud properties and associated cloud radiative effects during the SCT. By injecting aerosols at different stages of the SCT, noting that cloud is more decoupled from the surface over time due to entrainment warming, we find that cloud‐surface coupling significantly affects aerosol vertical transport. However, injection timing (before drizzle if any) does not notably affect the SCT and the efficiency of marine cloud brightening, because aerosol number concentrations due to injections at different times rapidly converge before the transition onset. By varying the background aerosol concentration, we find that injected aerosols can significantly extend the persistence of stratocumulus decks by suppressing precipitation in clean environments but have little impact on stratocumulus breakup with higher background aerosol concentrations due to saturated aerosol effects. In clean MBLs, the SCT‐delay‐induced increase in cloud fraction dominates the overall cooling effects in response to aerosols, followed by Twomey effects. These cooling effects are slightly offset by decreased liquid water path (LWP) due to entrainment drying. In polluted MBLs, the Twomey effect is more dominant, followed by cloud fraction adjustments, and these coolings are also partly offset by LWP adjustments. All the simulations are made in relatively small domains in which injected aerosols are homogenized over a short time scale.

Zhang, Haipeng [Univ. of Maryland, College Park, M↗

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

Decomposing Cloud Radiative Feedbacks by Cloud-Top Phase

Changes in cloud scattering properties and emissivity that arise from atmospheric warming cause substantial radiative feedbacks in model projections of anthropogenic climate change, and the relative importance of the underlying mechanisms is poorly understood. One leading hypothesis is that ice-to-liquid conversions cause clouds to optically thicken, producing a major negative feedback. We test this hypothesis by developing a method to decompose cloud radiative feedbacks by cloud-top phase. The method is applied to an ensemble of six state-of-the-art global climate models run with prescribed sea surface temperature. In these simulations, the global mean of the net cloud scattering and emissivity feedback from cloud-phase conversions ranges from −0.17 to −0.01 W m −2 K −1 , while the overall net cloud feedback ranges from 0.02 to 0.91 W m −2 K −1 . The multimodel mean of the cloud scattering and emissivity feedback from cloud-phase conversions is approximately 19% of the magnitude of the multimodel mean of the overall cloud feedback (−0.10 vs 0.52 W m −2 K −1 ). These results indicate that cloud-phase conversions cause a robust negative feedback by changing cloud scattering and emissivity, but this mechanism makes a modest contribution to the overall cloud feedback at the global scale.

Climate change↗

DOE OSTI2026

Examining Cloud Feedback Components in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

Cloud feedback remains the main source of uncertainty in climate sensitivity estimated by global climate models (GCMs), largely because subgrid cloud responses are parameterized in GCMs due to their coarse resolution. Here, this study examines cloud feedback in the global 3.25-km Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM 3 km) through a pair of 1-yr atmosphere-only simulations with control and +4-K sea surface temperature perturbations. SCREAM 3 km produces a positive cloud feedback that falls within but at the upper end of the range of Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP phase 6 (CMIP6) models and expert judgment. The positive cloud feedback arises from positive contributions from both high- and low-level clouds, with increases in high-cloud altitude and decreases in low-cloud amount and optical depth playing key roles. The stronger-than-CMIP-average feedback is mainly attributable to the high-cloud altitude feedback, owing to cloud tops rising nearly isothermally in SCREAM 3 km. The positive low-cloud amount feedback is weaker in SCREAM than in GCMs because estimated inversion strength (EIS) increases more dramatically with warming. A coarser 12-km resolution version of SCREAM exhibits a weaker positive cloud feedback than SCREAM 3 km, mainly because its low-cloud-radiative flux is more sensitive to EIS, leading to a stronger negative low-cloud amount feedback. With this process-level assessment of cloud feedback, this study reveals where SCREAM aligns with and diverges from conventional GCMs and expert assessment, providing insights to inform further model improvement and future expert assessment.

Cloud radiative effects↗

DOE OSTI2025

Synoptic Weather Regime Classifications for June, July, August, and September, 2022

The synoptic weather regime classification has become a highly demanded product for the ARM site in recent years. This type of regime classification has shown applications in various studies and topics, including aerosol-cloud interactions, land-atmosphere interactions, and cloud radiative effects. The VAP employs an unsupervised machine learning method, Self-organizing map (SOM), to classify weather regimes for each day of the AMF campaigns and fixed sites, using ERA5 data. This idea is mainly based on our published study for TRACER in Wang et al. (2022, JGR-A). This dataset includes the data in June, July, August, and September; the last year of the data is 2022.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Synoptic Weather Regime Classifications for the whole year, from 2014 to 2015

54 ENVIRONMENTAL SCIENCES↗