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\begin{document}

\title{Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances
Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017)}



\author[1,1]{Yunji Zhang}%
\author[2,2]{Scott B Sieron}%
\author[3,3]{Yinghui Lu}%
\author[1,1]{Xingchao Chen}%
\author[4,4]{Robert G Nystrom}%
\author[5,5]{Masashi Minamide}%
\author[1,1]{Man-Yau Chan}%
\author[1,1]{Christopher M Hartman}%
\author[1,1]{Zhu Yao}%
\author[6,6]{James H. Ruppert}%
\author[7,7]{Atsushi Okazaki}%
\author[1,1]{Steven J Greybush}%
\author[1,1]{Eugene E Clothiaux}%
\author[1,1]{Fuqing Zhang}%
\affil[1]{The Pennsylvania State University}%
\affil[2]{I.M. Systems Group Inc.}%
\affil[3]{Nanjing University}%
\affil[4]{NCAR}%
\affil[5]{The University of Tokyo}%
\affil[6]{The University of Oklahoma}%
\affil[7]{Hirosaki University}%


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  \date{May 25, 2024}


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\begin{abstract}
Ensemble-based data assimilation of radar observations across inner-core
regions of tropical cyclones (TCs) in tandem with satellite all-sky
infrared radiances across the TC domain improves TC track and intensity
forecasts. This study further investigates potential enhancements in TC
track, intensity, and rainfall forecasts via assimilation of all-sky
microwave radiances using Hurricane Harvey (2017) as an example.
Assimilating GPM constellation all-sky microwave radiances in addition
to GOES-16 all-sky infrared radiances reduces the forecast errors in the
TC track, rapid intensification, and peak intensity compared to
assimilating all-sky infrared radiances alone, including a 24-hour
increase in forecast lead-time for rapid intensification. Assimilating
all-sky microwave radiances also improves Harvey's hydrometeor fields,
which leads to improved forecasts of rainfall after Harvey's landfall.
This study indicates that avenues exist for producing more accurate
forecasts for TCs using available yet underutilized data, leading to
better warnings of and preparedness for TC-associated hazards in the
future.%
\end{abstract}%



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