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Abstract This study investigates how clouds and their atmospheric radiative effects respond to meridional shifts in the Southern Hemisphere (SH) mid‐latitude jet, represented by the Southern Annular Mode (SAM), using reanalysis data, CloudSat/CALIPSO observations, and CMIP6 models. Consistent with previous studies, poleward jet shifts displace storm‐track clouds, creating lower tropospheric radiative heating anomalies poleward of the mean jet latitude and cooling anomalies on the equatorward side of the mean jet latitude where large‐scale subsidence increases low cloud fraction. Whether these radiative heating anomalies can affect SAM persistence is also investigated in CMIP6 models. If observed sea surface temperatures are prescribed, models that simulate low cloud responses more realistically show less SAM persistence, aligning more closely with observations. Our results based on CMIP6 models agree with a recent idealized modeling study and suggest that atmospheric cloud radiative heating anomalies, induced by the poleward jet shift, contribute to a reduction in SAM persistence. 

Abstract Two common methods used to develop a process-level understanding of global cloud cover are 1) analyzing large-scale meteorological variables (cloud controlling factors) associated with cloud variability and 2) classifying cloud types using clustering algorithms applied to satellite data, such as the International Satellite Cloud Climatology Project (ISCCP) weather states. The cloud controlling factor method is advantageous to apply to climate models, as it does not rely on cloud parameterizations or the availability of satellite simulator output. The purpose of this study is to document the relationship between cloud controlling factors and the ISCCP weather states in the observational record, providing a benchmark for the application of cloud controlling factors to study individual cloud types in future studies. Most ISCCP weather states are linked to distinct dynamical regimes characterized by unique combinations of six cloud controlling factors. These relationships are present in both the long-term mean climatology and daily-to-monthly climate variability. For example, deep convective and midlatitude storm clouds dominate ascending regions. In descending regions, shallow cumulus is more frequent in regimes characterized by weak boundary layer temperature inversions [estimated inversion strength (EIS)] and strong subsidence, and stratocumulus is more frequent in regimes with larger values of EIS, weaker subsidence, and relatively weak near-surface cold advection. Midlevel clouds are prominent in descending regions with strong cold advection. Overall, the results of this study suggest promise in using cloud controlling factors to identify dynamical regimes where individual cloud types are more or less likely and to understand the physical processes responsible for the transitions among them. 

Abstract Although the multi‐model average compares well with observations, individually most of the latest climate models do not simulate a realistic size of the Indo‐Pacific Warm Pool in the present‐day climate. This study explores the implications of this warm pool size bias in climate models in Northern Hemisphere winter. The warm pool size bias in phase 6 of the Coupled Model Intercomparison Project models is related to the subtropical jet and precipitation distribution, both in the present‐day climate and in response to climate change, through extratropical Rossby wave trains and tropical circulation pathways. Based on these relationships, emergent constraints are developed to observationally constrain the future subtropical jet response over Asia and the Atlantic Ocean and precipitation response over North and Central America, which can help to reduce uncertainty in future projections of these features. Thus, accurate model simulation of the warm pool in the present‐day climate is important for future projections of the subtropical jet and precipitation.