Microwave temperature sounders onboard polar‐orbiting satellites can provide global observation data twice a day, supplying a large amount of temperature information for global data assimilation and serving as a crucial instrument to improve operational numerical forecasts. However, regional numerical forecasts are still subject to a lack of polar‐orbiting satellite data within regional model domains, and even multiple polar‐orbiting satellites may simultaneously miss measurements. Establishing a three‐orbit observation system of polar‐orbiting satellites is crucial to improve the spatiotemporal coverage of polar‐orbiting satellite data. In this study, we investigate the impact of assimilating microwave temperature sounding data from a three‐orbit constellation on precipitation forecasts in inland China based on the data from the US afternoon‐orbit satellite NOAA‐19, the European morning‐orbit satellite Meteorological Operational satellite‐A and the Chinese early‐morning‐orbit satellite Fengyun‐3E (FY‐3E) launched recently. The research results indicate that there are data gaps at 0600 and 1800 UTC in the East Asian region only for the morning‐orbit and afternoon‐orbit satellite observations. The FY‐3E satellite can provide additional microwave temperature sounding observations over the eastern region of China, thus partially compensating for the gap in polar‐orbiting satellite data in China. Moreover, the additional assimilation of the FY‐3E data can further improve numerical forecasts, effectively adjusting the spatial structure and eastward movement of the weather system, thereby considerably increasing the prediction accuracy of rainfall location and intensity. Rolling‐prediction results show that the data from the three‐orbit constellation provide a stable and notable improvement in precipitation forecasts in inland China, especially for forecasts longer than nine hours and amounts of rainfall below 10 mm. These research findings provide valuable insights for optimizing the assimilation application of polar‐orbiting satellite data in regional numerical forecasts.
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Huang et al. (2024) studied this question.
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