2021
DOI: 10.1155/2021/6427620
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Assimilation of MWHS-2/FY-3C 183 GHz Channels Using a Dynamic Emissivity Retrieval and Its Impacts on Precipitation Forecasts: A Southwest Vortex Case

Abstract: The dynamic emissivity retrieved from window channels of the microwave humidity sounder II (MWHS-2) onboard the China Meteorological Administration’s FengYun (FY)-3C polar orbiting satellite can provide more realistic emissivity over lands and potentially improve the numerical weather prediction (NWP) forecasts. However, whether the assimilation with the dynamic emissivity works for the precipitation forecasts over the complex geography is less investigated. In this paper, a typical precipitating case generate… Show more

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Cited by 10 publications
(10 citation statements)
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“…In the Met Office global model, MWHS-2 was found to reduce the 24 h forecast error significantly, by 0.6% [37]. With regional models, assimilating FY-3C/MWHS-2 observations under both clear-and all-sky conditions improved the forecasts of typhoons [38], Meiyu [39] and the Southwest Vortex [40]. Later, FY-3D was successfully launched in October 2017.…”
Section: Introductionmentioning
confidence: 99%
“…In the Met Office global model, MWHS-2 was found to reduce the 24 h forecast error significantly, by 0.6% [37]. With regional models, assimilating FY-3C/MWHS-2 observations under both clear-and all-sky conditions improved the forecasts of typhoons [38], Meiyu [39] and the Southwest Vortex [40]. Later, FY-3D was successfully launched in October 2017.…”
Section: Introductionmentioning
confidence: 99%
“…Until now, the MWHS‐I and MWHS‐II have been operationally assimilated by the European Centre for Medium‐range Weather Forecasts (ECMWF; Bormann et al, 2021; Lawrence et al, 2018) and the UK Met Office (Carminati et al, 2021; Carminati & Migliorini, 2021). The impacts of these sensors on several data assimilation systems have been studied, including the Gridpoint Statistical Interpolation global analysis system (Jiang et al, 2020), the Weather Research and Forecasting data assimilation system (Chen, Fan, & Xian, 2021; Jiang et al, 2019; Mi et al, 2014; Su et al, 2013; Tang et al, 2018; Xian et al, 2019; Zhang et al, 2013), the Weather Research and Forecasting Hybrid‐3DVAR data assimilation system (Sun & Xu, 2021; Xu et al, 2016), the ensemble three‐dimensional variational assimilation method based on proper orthogonal decomposition (POD‐3DEnVar; Zhang, Liu, Liu, et al, 2019; Zhang, Lu, & Gu, 2019; Zhang, Lu, Hu, et al, 2019; Zhang, Zhang, Zhang, et al, 2019) and the Rapid‐refresh Multi‐scale Analysis and Prediction System‐Short Term (RMAPS‐ST) operational system (Liu et al, 2021). The special channels at 118 GHz on the MWHS‐II have some difficulties for operational assimilation, due to their complex sensitivity to both temperature and humidity (Bormann et al, 2021; Carminati et al, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…Yang et al (2011) proposed a forecast equation for SWV precipitation and emphasized different forecast focuses for various SWV types [13]. Chen et al (2021) enhanced the assimilation of dynamic emissivity data to improve 24-h predictions of initial fields and precipitation distribution [14].…”
Section: Introductionmentioning
confidence: 99%