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Abstract. This work assesses a recently produced 21-member climate model large ensemble (LE) based on the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2 (E3SM2). The ensemble spans the historical era (1850 to 2014) and 21st century (2015 to 2100), using the SSP370 pathway, allowing for an evaluation of the model's forced response. A companion 500-year preindustrial control simulation is used to initialize the ensemble and estimate drift. Characteristics of the LE are documented and compared against other recently produced ensembles using the E3SM version 1 (E3SM1) and Community Earth System Model (CESM) versions 1 and 2. Simulation drift is found to be smaller, and model agreement with observations is higher in versions 2 of E3SM and CESM versus their version 1 counterparts. Shortcomings in E3SM2 include a lack of warming from the mid to late 20th century, likely due to excessive cooling influence of anthropogenic sulfate aerosols, an issue also evident in E3SM1. Associated impacts on the water cycle and energy budgets are also identified. Considerable model dependence in the response to both aerosols and greenhouse gases is documented and E3SM2's sensitivity to variable prescribed biomass burning emissions is demonstrated. Various E3SM2 and CESM2 model benchmarks are found to be on par with the highest-performing recent generation of climate models, establishing the E3SM2 LE as an important resource for estimating climate variability and responses, though with various caveats as discussed herein. As an illustration of the usefulness of LEs in estimating the potential influence of internal variability, the observed CERES-era trend in net top-of-atmosphere flux is compared to simulated trends and found to be much larger than the forced response in all LEs, with only a few members exhibiting trends as large as observed, thus motivating further study. 

Abstract Studies have indicated exaggerated Maritime Continent (MC) barrier effect in simulations of the Madden–Julian oscillation (MJO), a dominant source of subseasonal predictability in the tropics. This issue has plagued the modeling and operational forecasting communities for decades, while the sensitivity of MC barrier on MJO predictability has not been addressed quantitatively. In this study, perfect-model ensemble forecasts are conducted with an aquaplanet configuration of the Community Earth System Model version 2 (CESM2) in which both basic state and tropical modes of variability are reasonably simulated with a warm pool–like SST distribution. When water-covered terrain mimicking MC landmasses is added to the warm pool–like SST framework, the eastward propagation of the MJO is disturbed by the prescribed MC aqua-mountain. The MJO predictability estimate with the perfect-model experiment is about 6 weeks but reduces to about 4 weeks when the MJO is impeded by the MC aqua-mountain. Given that the recent operational forecasts show an average of 3–4 weeks of MJO prediction skill, we can conclude that improving the MJO propagation crossing the MC could improve the MJO skill to 5–6 weeks, close to the potential predictability found in this study (6 weeks). Therefore, more effort toward understanding and improving the MJO propagation is needed to enhance the MJO and MJO-related forecasts to improve the subseasonal-to-seasonal prediction. 

Abstract Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall. 

Abstract Atmospheric rivers (ARs) manifest as transient filaments of intense water vapor transport that contribute to synoptic‐scale extremes and interannual variability of precipitation. Despite these influences, the synoptic‐ to planetary‐scale processes that lead to ARs remain inadequately understood. In this study, North Pacific ARs within the November–April season are objectively identified in both reanalysis data and the Community Earth System Model Version 2, and atmospheric patterns preceding AR landfalls beyond 1 week in advance are examined. Latitudinal dependence of the AR processes is investigated by sampling events near the Oregon (45°N, 230°E) and southern California (35°N, 230°E) coasts. Oregon ARs exhibit a pronounced anticyclone emerging over Alaska 1–2 weeks before AR landfall that migrates westward into Siberia, dual midlatitude cyclones developing over southeast coastal Asia and the northeast Pacific, and a zonally elongated band of enhanced water vapor transport spanning the entire North Pacific basin that guides anomalous moisture toward the North American west coast. The precursor high‐latitude anticyclone corresponds to a significant increase in atmospheric blocking probability, suppressed synoptic eddy activity, and an equatorward‐shifted storm track. Southern California ARs also exhibit high‐latitude blocking but have an earlier‐developing and more intense northeast Pacific cyclone. Compared to reanalysis, Community Earth System Model Version 2 underestimates Northeast Pacific AR frequencies by 5–20% but generally captures AR precursor patterns well, particularly for Oregon ARs. Collectively, these results indicate that the identified precursor patterns represent physical processes that are central to ARs and are not simply an artifact of statistical analysis. 

Abstract Recent studies have focused on the role of cloud radiative effects (CRE) in governing the mean atmospheric circulation and its response to climate change. This study instead examines the role of CRE in climate variability in the extratropics. Cloud locking experiments are performed using the Community Earth System Model. In these experiments, CRE are scrambled, such that they maintain the same climatology but no longer match the model's dynamical fields. The results of these experiments indicate that high‐frequency interactions between CRE and dynamics have a small (≤5–10%) but statistically significant damping effect on the intensity of the extratropical storm tracks, particularly in the Southern Hemisphere. Individual midlatitude cyclones have decreased intensity and shorter lifetime. These effects arise largely from clouds' radiative modification of static stability below 700 hPa. The coupling among clouds, radiation, and dynamics thus has a modest but potentially important influence on the extratropical storm tracks.