Ensemble‐Based Assimilation of Satellite All‐Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017). Issue 24 (26th December 2021)

• Record Type: Journal Article
• Authors: Zhang, Yunji; Sieron, Scott B.; Lu, Yinghui; Chen, Xingchao; Nystrom, Robert G.; Minamide, Masashi; Chan, Man‐Yau; Hartman, Christopher M.; Yao, Zhu; Ruppert, James H.; Okazaki, Atsushi; Greybush, Steven J.; Clothiaux, Eugene E.; Zhang, Fuqing
• Is Part Of: Geophysical research letters. Volume 48:Issue 24(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-26
• Subjects: tropical cyclone -- numerical modeling -- weather forecast -- data assimilation -- Ensemble Kalman filter -- satellite observation; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2021GL096410
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Ensemble‐based data assimilation of radar observations across inner‐core regions of tropical cyclones (TCs) in tandem with satellite all‐sky infrared (IR) 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 (MW) radiances using Hurricane Harvey (2017) as an example. Assimilating Global Precipitation Measurement constellation all‐sky MW radiances in addition to GOES‐16 all‐sky IR radiances reduces the forecast errors in the TC track, rapid intensification (RI), and peak intensity compared to assimilating all‐sky IR radiances alone, including a 24‐hr increase in forecast lead‐time for RI. Assimilating all‐sky MW 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. Plain Language Summary: Track, intensity, and rainfall are fundamental elements of all forecasts and warnings associated with tropical cyclones (TCs). Over the last few decades, the forecast community has significantly improved TC track forecasts. Notable improvements in TC intensity forecasts have recently been achieved using high‐resolution models and remote‐sensing observations over the inner‐core region of TCs. This study builds on these earlier efforts by investigating the impacts of microwave (MW) observations on the forecast accuracy of TC track, intensity, and rainfall. Because MW radiances are sensitive to water vapor, liquid water, and ice, assimilating these observations into numerical TC forecasts is expected to improve estimates of the liquid water and ice within TCs, leading to better rainfall forecasts. These expectations are borne out in our study of Hurricane Harvey. Results indicate that incorporating currently available yet underutilized observations into numerical TC forecasts can further improve warnings of, and preparedness for, TC‐associated hazards in the future. Key Points: Satellite all‐sky infrared (IR) and microwave (MW) radiances are assimilated to assess their impacts on forecasts for Hurricane Harvey Along with IR radiances, MW radiances improve the track and intensity forecasts for Harvey MW radiance assimilation leads to better analyses of the hydrometeor fields and more accurate rainfall forecasts