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This study assesses the midsummer precipitation prediction over eastern China by the dynamic downscaling method. Based on the Climate Forecast System version 2 of the National Centers for Environmental Prediction and the Weather Research and Forecasting Model, the prediction performance of global and regional models on the July precipitation over eastern China is further analyzed by hindcast experiments from 1982 to 2010 and prediction experiments from 2011 to 2021. The results suggest that the regional model forced by the global model can noticeably improve the prediction skill for precipitation in eastern China, especially in the region from the South of North China to the Yangtze River Basin, referred as the northern China in this paper. In addition, we perform a diagnostic analysis of the reason for the improvement of the model prediction skill. The results indicate that the high resolution of the regional model and the refinement of physical process parameterizations contribute to improving the simulation ability for the East Asian atmospheric circulation pattern, heat flux, especially for the meridional teleconnection pattern in East Asia and the sensible heat flux in the northern China, thus further improving precipitation prediction. [ABSTRACT FROM AUTHOR]

The PM2.5 (fine particulate matter with diameter ≤2.5 μm) concentration anomalies over the North China Plain (NCP) in early and late winter sometimes show a subseasonal reversal, which brings a great challenge for precise control of air pollution, and mechanisms are not well understood. This paper reveals the key role of the Barents Sea sea‐ice in this reversal. In early winter, a negative Scandinavian‐like pattern causes an anticyclonic anomaly over Northeast Asia and thus leads to the positive PM2.5 concentration anomaly over the NCP. In addition, anomalous warm advection associated with the positive North Atlantic Oscillation‐like pattern accelerates winter sea‐ice loss in the Barents Sea, especially in late winter, which increases the surface turbulent heating flux. These heating causes a negative Polar/Eurasian‐like pattern that induces a cyclonic anomaly over Northeast Asia and eventually leads to a negative PM2.5 concentration anomaly over the NCP in late winter. Vice versa. Plain Language Summary: In this study, we find that there is a significant seesaw pattern of PM2.5 concentration anomalies over the North China Plain (NCP) in early and late winter. Further results reveal that variations in Barents Sea sea‐ice play a crucial role. More specifically, a negative (positive) Scandinavian‐like pattern in early winter tends to induce an anticyclonic (a cyclonic) anomaly over Northeast Asia. This anticyclonic (cyclonic) anomaly leads to a higher (lower) PM2.5 concentration anomaly over the NCP in early winter. In addition, a North Atlantic Oscillation‐related warm (cold) temperature advection promotes (inhibits) the sea‐ice loss in the Barents Sea, especially in late winter. The Barents Sea‐ice loss (increment) in late winter tends to heat (cool) the lower‐level atmosphere and thus triggers an anticyclonic (a cyclonic) response in the upper troposphere there. The anticyclonic (cyclonic) response in the Barents Sea region as a part of the negative (positive) Polar/Eurasian‐like pattern induces a cyclonic (an anticyclonic) anomaly over Northeast Asia, which leads to a lower (higher) PM2.5 concentration anomaly over the NCP in late winter. These findings could be of great value for the subseasonal predictions of PM2.5 concentrations over the NCP in winter. Key Points: PM2.5 concentration anomaly over the North China Plain shows an visibly subseasonal reversal in early and late winter on interannual scaleThe Scandinavia‐like pattern and Polar/Eurasian‐like pattern are responsible for the seesaw pattern of PM2.5 concentration anomaliesThe sea‐ice variations in the Barents Sea play a key role in modulating such atmospheric circulations [ABSTRACT FROM AUTHOR]

China's first Mars exploration mission (Tianwen‐1), launched on July 23, 2020 with the goal of "orbiting, landing, and roving," and its tentative landing areas (TLAs) are Chryse Planitia (TLA 1) and Isidis‐Elysium Planitia (TLA 2). Dust storm is a typical activity on Mars; it has strong interaction with atmospheric circulation and will influence the visibility of the Martian surface. To ensure the safety and accuracy for landing, it is meaningful to analyze the probability of dust storm activity during Entry‐Descent‐Landing (EDL) season in TLAs. First, based on Mars Orbiter Camera (MOC) and Mars Color Imager (MARCI) Daily Global Maps (MDGMs) from Mars Years 24–31, we identified 882 dust storms within the 2,000 km radius monitor circle of TLA 2 (short for TLA 2‐C). Second, the average daily probability of dust storm activity (Adp_ds) in TLA 2‐C was calculated, with a range of 0% to 14.13% showing obvious seasonality and discontinuity. Third, we divided TLA 2‐C into 0.5° longitude × 0.5° latitude square grids and calculated their spatial probability of dust storm activity. The spatial probability of dust storm in TLA 2‐C ranged from 0% to 11.87% and generally reduced from north to south. Finally, according to the temporal and spatial dust storm probability in TLA 2 during EDL season, we suggested the optimal landing time of China's Tianwen‐1 mission was in Ls = 20–41° and selected five preferred landing areas with the spatial probability of dust storm <3% for this mission. Plain Language Summary: The first China's Mars exploration mission (Tianwen‐1), will achieve the targets of "orbiting, landing, and roving." There are two tentative landing areas (TLAs) in the latitude range of 5–30°, Chryse Planitia (TLA 1) and Isidis‐Elysium Planitia (TLA 2). TLA 2 is on the south of Utopia which is an important origination area of dust storm sequences in the northern hemisphere. The probability of dust storm activity is an important criterion of atmospheric risk assessment for a Martian surface mission. Thus, it is crucial to evaluate the probabilities and characteristics of dust storm activity in and around TLA 2. In this paper, we used Mars Daily Global Maps (MDGMs) of Mars Orbiter Camera (MOC) and Mars Color Imager (MARCI) to (1) identify and catalog the dust storms in and around TLA 2; (2) calculate and analyze the temporal and spatial probability of dust storms in and around TLA 2; and (3) select the preferred landing time and areas for Tianwen‐1 mission based on the temporal and spatial probability of dust storm activity in TLA 2. Key Points: The temporal probability of dust storm activity in Isidis‐Elysium Planitia shows obvious seasonal and inconsecutive activityThe spatial probability of dust storm activity in Isidis‐Elysium Planitia is generally reduced from north to southThe optimal landing time was in Ls = 20–41°, and five preferred landing areas were selected for Tianwen‐1 [ABSTRACT FROM AUTHOR]