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.

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.