This study evaluates the performance of a global storm-resolving model (GSRM), the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM). We analyze marine boundary layer clouds in a cold air outbreak over the Norwegian Sea in a 40-day simulation, and compare them to observations from satellite and a field campaign of the Atmospheric Radiation Measurement program (ARM). SCREAM qualitatively captures the cold air outbreak cloud transition in terms of the boundary layer growth, cloud mesoscale structure, and phase partitioning. SCREAM also correctly locates the greatest ice and liquid in the mesoscale updraft. However, the study finds that SCREAM might underestimate cloud supercooled liquid water in the cumulus cloud regime. This study showcases the promise of employing high-resolution and high-frequency observations under similar large-scale conditions for evaluating GSRMs. This approach can help identify model features for future process-level studies before allocating extra resources for a time-matched model intercomparison of a specific case.

The effective climate sensitivity in the Department of Energy’s Energy Exascale Earth System Model (E3SM) has decreased from 5.3 K in version 1 to 4.0 K in version 2. This reduction is mainly due to a weaker positive cloud feedback that leads to a stronger negative radiative feedback. Present-day atmosphere-only experiments with uniform 4 K sea surface temperature warming are used to separate the contributions of individual model modifications to the reduced cloud feedback. We find that the reduced cloud feedback is mostly driven by changes over the tropical marine low cloud regime, mainly related to a new trigger function for the deep convection scheme and modifications in the cloud microphysics scheme. The new trigger function helps weaken the low cloud reduction by increasing the cloud water detrainment at low levels from deep convection under warming. Changes to the formula of autoconversion rate from liquid to rain and an introduced minimum cloud droplet number concentration threshold in cloud microphysical calculations help sustain clouds against dissipation by suppressing precipitation generation with warming. In the midlatitudes, the increased Wegener-Bergeron-Findeisen (WBF) efficiency strongly reduces present-day liquid water and leads to a stronger negative cloud optical depth feedback. The reduced trade cumulus cloud feedback in v2 is closer to estimates from recent observational and large-eddy modeling studies but might not be due to the right physical reasons. The reduced mid-latitude cloud feedback may be more plausible because more realistic present-day mixed-phase clouds are produced through the change in the WBF efficiency.

This study evaluates high-latitude stratiform mixed-phase clouds (SMPC) in the atmosphere model of the newly released Energy Exascale Earth System Model version 2 (EAMv2) by utilizing one-year-long ground-based remote sensing measurements from the U.S. Department of Energy Atmospheric Radiation and Measurement (ARM) Program. A nudging approach is applied to model simulations for a better comparison with the ARM observations. Observed and modeled SMPCs are collocated to evaluate their macro- and microphysical properties at the ARM North Slope of Alaska (NSA) site in the Arctic and the McMurdo (AWR) site in the Antarctic. We found that EAMv2 overestimates (underestimates) SMPC frequency of occurrence at the NSA (AWR) site nearly all year round. However, the model captures the observed larger cloud frequency of occurrence at the NSA site. For collocated SMPCs, the annual statistics of observed cloud macrophysics are generally reproduced at the NSA site, while at the AWR site, there are larger biases. Compared to the AWR site, the lower cloud boundaries and the warmer cloud top temperature observed at NSA are well simulated. On the other hand, simulated cloud phases are substantially biased at each location. The model largely overestimates liquid water path at NSA, whereas it is frequently underestimated at AWR. Meanwhile, the simulated ice water path is underestimated at NSA, but at AWR, it is comparable to observations. As a result, the observed hemispheric difference in cloud phase partitioning is misrepresented in EAMv2. This study implies that continuous improvement in cloud microphysics is needed for high-latitude mixed-phase clouds.

The water cycle is an important component of the earth system and it plays a key role in many facets of society, including energy production, agriculture, and human health and safety. In this study, the Energy Exascale Earth System Model version 1 (E3SMv1) is run with low-resolution (roughly 110 km) and high-resolution (roughly 25 km) configurations — as established by the High Resolution Model Intercomparison Project protocol — to evaluate the atmospheric and terrestrial water budgets over the conterminous United States (CONUS) at the large watershed scale. The water cycle slows down in the HR experiment relative to the LR, with decreasing fluxes of precipitation, evapotranspiration, atmospheric moisture convergence, and runoff. The reductions in these terms exacerbate biases for some watersheds, while reducing them in others. For example, precipitation biases are exacerbated at HR over the Eastern and Central CONUS watersheds, while precipitation biases are reduced at HR over the Western CONUS watersheds. The most pronounced changes to the water cycle come from reductions in precipitation and evapotranspiration, the latter of which results from decreases in evaporative fraction. While the HR simulation is warmer than the LR, moisture convergence decreases despite the increased atmospheric water vapor, suggesting circulation biases are an important factor. Additional exploratory metrics show improvements to water cycle extremes (both in precipitation and streamflow), fractional contributions of different storm types to total precipitation, and mountain snowpack.

This work documents version two of the Department of Energy’s Energy Exascale Earth System Model (E3SM). E3SM version 2 (E3SMv2) is a significant evolution from its predecessor E3SMv1, resulting in a model that is nearly twice as fast and with a simulated climate that is improved in many metrics. We describe the physical climate model in its lower horizontal resolution configuration consisting of 110 km atmosphere, 165 km land, 0.5° river routing model, and an ocean and sea ice with mesh spacing varying between 60 km in the mid-latitudes and 30 km at the equator and poles. The model performance is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima (DECK) simulations augmented with historical simulations as well as simulations to evaluate impacts of different forcing agents. The simulated climate is generally realistic, with notable improvements in clouds and precipitation compared to E3SMv1. E3SMv1 suffered from an excessively high equilibrium climate sensitivity (ECS) of 5.3 K. In E3SMv2, ECS is reduced to 4.0 K which is now within the plausible range based on a recent World Climate Research Programme (WCRP) assessment. However, E3SMv2 significantly underestimates the global mean surface temperature in the second half of the historical record. An analysis of single-forcing simulations indicates that correcting the historical temperature bias would require a substantial reduction in the magnitude of the aerosol-related forcing.

Significant changes are found in the modeled phase partitioning of Arctic mixed-phase clouds in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1) compared to its predecessor, the Community Atmosphere Model version 5 (CAM5). In this study, we aim to understand how the changes in modeled mixed-phase cloud properties are attributed to the updates made in the EAMv1 physical parameterizations. Impacts of the Classical Nucleation Theory (CNT) ice nucleation scheme, the Cloud Layer Unified By Binormals (CLUBB) parameterization, and updated Morrison and Gettelman microphysical scheme (MG2) are examined. Sensitivity experiments using the short-term hindcast approach are performed to isolate the impact of these new features on simulated mixed-phase clouds. Results are compared to the DOE’s Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Cloud Experiment (M-PACE) observations. We find that mixed-phase clouds simulated in EAMv1 are overly dominated by supercooled liquid and cloud ice water is substantially underestimated. The individual change of physical parameterizations is found to decrease cloud ice water mass mixing ratio in EAMv1 simulated single-layer mixed-phase clouds. A budget analysis of detailed cloud microphysical processes suggests that the lack of ice particles that participate in the mass growth processes strongly inhibits the mass mixing ratio of cloud ice. The insufficient heterogeneous ice nucleation at temperatures warmer than -15C in CNT and the negligible ice processes in CLUBB are primarily responsible for the significant underestimation of cloud ice water content in the Arctic single-layer mixed-phase clouds.

This study performs a comprehensive evaluation of the simulated cloud phase in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM) atmosphere model version 2 (EAMv2) and version 1 (EAMv1). Enabled by the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) simulator, EAMv2 and EAMv1 predicted cloud phase is compared against the GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP) at high latitudes where mixed-phase clouds are prevalent. Our results indicate that the underestimation of cloud ice in simulated high-latitude mixed-phase clouds in EAMv1 has been significantly reduced in EAMv2. The increased ice clouds in the Arctic mainly result from the modification on the WBF (Wegner-Bergeron-Findeisen) process in EAMv2. The impact of the modified WBF process is moderately compensated by the low limit of cloud droplet number concentration (CDNC) in cloud microphysics and the new dCAPE_ULL trigger used in deep convection in EAMv2. Moreover, it is found that the new trigger largely contributes to the better cloud phase simulation over the Norwegian Sea and Barents Sea in the Arctic and the Southern Ocean where large errors are found in EAMv1. However, errors in simulated cloud phase in EAMv1, such as the overestimation of supercooled liquid clouds near the surface in both hemispheres and the underestimation of ice clouds over Antarctica, persist in EAMv2. This study highlights the impact of deep convection parameterizations, which has not been paid much attention, on high-latitude mixed-phase clouds, and the importance of continuous improvement of cloud microphysics in climate models for accurately representing mixed-phase clouds.

Nitrate aerosol plays an important role in affecting regional air quality as well as Earth’s climate. However, it is not well represented or even neglected in many global climate models. In this study, we couple the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) module with the four-mode version of the Modal Aerosol Module (MAM4) in DOE’s Energy Exascale Earth System Model version 2 (E3SMv2) to treat nitrate aerosol and its radiative effects. We find that nitrate aerosol simulated by E3SMv2-MAM4-MOSAIC is sensitive to the treatment of gaseous HNO3 transfer to/from interstitial particles related to accommodation coefficients of HNO3 (αHNO3) on dust and non-dust particles. We compare three different treatments of HNO3 transfer: 1) a treatment (MTC_SLOW) that uses a low αHNO3 in the mass transfer coefficient (MTC) calculation; 2) a dust-weighted MTC treatment (MTC_WGT) that uses a high αHNO3 on non-dust particles; and 3) a dust-weighted MTC treatment that also splits coarse mode aerosols into the coarse dust and sea salt sub-modes in MOSAIC (MTC_SPLC). MTC_WGT and MTC_SPLC increase the global annual mean (2005-2014) nitrate burden from 0.096 (MTC_SLOW) to 0.237 and 0.185 Tg N, respectively, mostly in the coarse mode. They also produce stronger nitrate direct radiative forcing (–0.048 and –0.051 W m–2, respectively) and indirect forcing (–0.33 and –0.35 W m–2, respectively) than MTC_SLOW (–0.021 and –0.24 W m–2). All three treatments overestimate nitrate surface concentrations compared with ground-based observations. MTC_WGT and MTC_SPLC improve the vertical profiles of nitrate concentrations against aircraft measurements below 400 hPa.