The Taklimakan Desert (TD) is located in the Eurasian continent in the mid-latitude region of the Northern Hemisphere (Rittner et al., 2016). As the second-largest desert in the world, it occupies the central part of the Tarim Basin, with a total area of ∼337,600 km 2 , and the average elevation is about 1.1 km. TD is flanked by high mountain ranges, the Pamirs to the west, Tianshan Mountain to the north, and Kunlun Mountain to the south. Due to the special topography, the easterly wind is dominant in the lower troposphere (Ge et al., 2016). As shown in Figure 1, TD is covered by moving sand that can spread hundreds of kilometers, causing inconvenient transportation (Sun et al., 2001). Besides, due to the dry climate, the frequency of sand storms have been increased in this region in the last decades (
In this article, precipitation in a new regional reanalysis dataset, namely, the East Asia regional reanalysis system (EARS‐CMA) with a 12‐km resolution based on the Weather Research and Forecast (WRF) model, ERA‐Interim, ERA5, TRMM 3B42V7, Climate Prediction Center Morphing Technique (CMORPH) and CN05.1, is compared in 2008–2017. The results show that EARS‐CMA can capture the spatial features and temporal variation in precipitation over East Asia well. Focusing on mainland China, CMORPH performs worse in regard to winter precipitation and dryer areas than TRMM against CN05.1. Although ERA5 behaves better with integrated properties compared with ERA‐Interim and EARS‐CMA over East Asia, EARS‐CMA produces more reliable annual, summer and winter mean precipitation pattern than ERA5 over the subregions dominated by large scales in mainland China, including the Tibetan Plateau and northwestern China, similar to its driving fields, ERA‐Interim. In addition, the improvement from ERA‐Interim to EARS‐CMA can be obtained in reasonably reproducing precipitation seasonality in South China, Indo‐China and southern Japan. Thus, the compatibility of EARS is outstanding in maintaining the advantages of its corresponding driving fields, ERA‐Interim, as well as developing finer small scales. Although slightly behind ERA5 in the subregions affected by tropical systems and monsoons, EARS‐CMA is competitive in acting as reference data for daily, seasonal, annual and interannual precipitation estimations over mainland China.
Both dynamic and cloud microphysical processes play significant roles in the intensity of severe rainfall within a convective storm. In this study, a quantitative analysis has been performed to investigate dynamic and cloud microphysical contributions to extreme hourly rainfall (EHR) with the peak value of 201.9 mm in Zhengzhou City, China, on 20 July 2021. It is found that the EHR is generated by the overlay of rainwater provided by both dynamic delivery and cloud microphysical production within a meso‐γ‐scale convective storm over Zhengzhou. Specifically, part of the rainwater is directly produced by cloud microphysical processes over the EHR region. More importantly, considerable rainwater, which is produced in the front of the storm associated with strong updraughts, is delivered into the EHR region. The dynamically delivered rainwater overlays the rainwater produced by cloud microphysical processes, forming a deep layer with a large amount of rainwater over the EHR region. As the massive rainwater pours down within a short time, EHR is formed. It should be highlighted that the dynamic delivery plays a decisive role in EHR formation, although sometimes EHR can be generated mainly through cloud microphysical production in the case of weak dynamic delivery. Concerning the cloud microphysical processes, the collision of cloud droplets by raindrops produces the largest amount of rainwater, followed by graupel melting. Linking the EHR with dynamic and cloud microphysical processes within a convective storm, a new light on further understanding and forecasting of short‐duration extreme rainfall would be shed.
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