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DOI10.1016/j.atmosres.2020.104912
Improving forecasts of a record-breaking rainstorm in Guangzhou by assimilating every 10-min AHI radiances with WRF 4DVAR
Wu, Yali1,2,3; Liu, Zhiquan3; Li, Deqin4
2020-07-15
发表期刊ATMOSPHERIC RESEARCH
ISSN0169-8095
EISSN1873-2895
出版年2020
卷号239
文章类型Article
语种英语
国家Peoples R China; USA
英文摘要

On 6 May 2017, a record-breaking warm-sector torrential rainfall (WSTR) event initiated over Guangzhou city around 1600 UTC and lasted for 20 h. To replicate this rainfall event, both three-dimensional and four-dimensional variational (3DVAR/4DVAR) data assimilation (DA) strategies were used to initialize a convectionallowing configuration of the Weather Research and Forecasting (WRF) model in an attempt to evaluate precipitation forecasts with or without the assimilation of Advanced Himawari Imager (AHI) radiances from three water vapor (WV) channels. This case study yielded impressions that both the 4DVAR experiments with and without the assimilation of AHI radiances prominently improved convection initiation (CI) forecasts, and replicated the observations accurately in predicting hourly area precipitation totals. Due to the small spatial scale of this event, the impacts of assimilating every 10-min AHI radiances on the convection evolution and hourly precipitation forecasts were subjectively small to be seen, but the equitable threat score (ETS) and fractions skill score (FSS) did show slight improvement for both hourly and 20-h accumulated precipitation. For example, the 4DVAR technique combined with AHI radiances improved the FSS of 20-h accumulated precipitation forecasts by 2%-4.5%, 1%-3%, 6%-20%, and 8%-24% for 5 mm, 20 mm, 50 mm, and 80 mm thresholds, respectively, over those with only conventional observations assimilated. Reasons for these improvements were attributed to better analyses and forecasts of temperature, moisture, and wind.


英文关键词10-min AHI radiances 4DVAR Warm-sector torrential rainfall Record-breaking
领域地球科学
收录类别SCI-E
WOS记录号WOS:000525324000009
WOS关键词VARIATIONAL DATA ASSIMILATION ; SATELLITE INFRARED RADIANCES ; COASTAL METROPOLITAN CITY ; RADAR DATA ASSIMILATION ; WARM-SECTOR ; SOUTH CHINA ; OPERATIONAL IMPLEMENTATION ; CONVECTIVE SYSTEMS ; WEATHER RESEARCH ; HEAVY RAINFALL
WOS类目Meteorology & Atmospheric Sciences
WOS研究方向Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/289282
专题地球科学
作者单位1.Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou 510275, Peoples R China;
2.Guangzhou Inst Trop & Marine Meteorol, Key Lab Reg Numer Weather Predict, Guangzhou 510080, Peoples R China;
3.Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA;
4.Inst Atmospher Environm, Shenyang 110166, Peoples R China
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Wu, Yali,Liu, Zhiquan,Li, Deqin. Improving forecasts of a record-breaking rainstorm in Guangzhou by assimilating every 10-min AHI radiances with WRF 4DVAR[J]. ATMOSPHERIC RESEARCH,2020,239.
APA Wu, Yali,Liu, Zhiquan,&Li, Deqin.(2020).Improving forecasts of a record-breaking rainstorm in Guangzhou by assimilating every 10-min AHI radiances with WRF 4DVAR.ATMOSPHERIC RESEARCH,239.
MLA Wu, Yali,et al."Improving forecasts of a record-breaking rainstorm in Guangzhou by assimilating every 10-min AHI radiances with WRF 4DVAR".ATMOSPHERIC RESEARCH 239(2020).
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