The arid region of Northwest China and Mongolia (NCM) receives most of the precipitation in the summer. The need for a better understanding of the synoptic-scale mechanism responsible for precipitation formation is accentuated by the recent wetting trend and its implications for future hydroclimate change. By conducting a hierarchical clustering analysis on an observationally-based daily precipitation dataset, we show that there are three distinct precipitation patterns over NCM, one of which is associated with strong precipitation over the western part of the region and another over the eastern part. The corresponding large-scale circulation anomalies indicate that these strong precipitation events are triggered by the upper-tropospheric disturbances in the form of transient Rossby wave packets. Furthermore, the wetting trend is linked to more frequent strong precipitation events over the eastern NCM, suggesting that it may have been induced remotely by atmospheric circulation perturbations.

The uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step toward improved process understanding, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized general circulation model (GCM) are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme without water vapor and cloud feedbacks allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes. This enables the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. We show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low-level clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large-scale advection of moisture provides the main source of water vapor for the liquid-containing clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming.

Advances in high-performance computing have enabled large-eddy simulations (LES) of turbulence, convection, and clouds, but their potential to improve parameterizations in global climate models (GCMs) is only beginning to be harnessed. We design an experimental setup in which LES can be driven by large-scale forcings from GCMs. This can be done anywhere in the atmosphere, and we use this setup to create a library of LES of clouds across tropical and subtropical regimes. The LES are used to simulate the transition from stratoculumus to shallow cumulus over the East Pacific. The results are not very sensitive to the choice of the host GCM driving the LES. The setup is also used to simulate clouds under climate change. The LES simulate a positive but weak shortwave cloud feedback. The LES library expands the datasets available for calibrating parameterizations in GCMs.

The COVID-19 pandemic led to a widespread reduction in aerosol emissions. Anecdotal effects on air quality and visibility were widely reported. Less known are the impacts on the planetary energy balance. Using satellite observations and climate model simulations, we 15 study the underlying mechanisms of the large, precipitous decreases in solar clear-sky reflection (3.8 W m-2 or 7%) and aerosol optical depth (0.16 or 32%) over the East Asian Marginal Seas in March 2020. By separating the impacts due to meteorology and emissions in the model simulations, we find that about one-third of the anomalies can be attributed to pandemic-related emission reductions, and the rest to weather variability and long-term emission trends. The 20 current observational and modeling capabilities will be critical for monitoring, understanding, and predicting the radiative forcing and climate impacts of the ongoing crisis.