TY - JOUR
T1 - Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017)
AU - Zhang, Yunji
AU - Sieron, Scott B.
AU - Lu, Yinghui
AU - Chen, Xingchao
AU - Nystrom, Robert G.
AU - Minamide, Masashi
AU - Chan, Man Yau
AU - Hartman, Christopher M.
AU - Yao, Zhu
AU - Ruppert, James H.
AU - Okazaki, Atsushi
AU - Greybush, Steven J.
AU - Clothiaux, Eugene E.
AU - Zhang, Fuqing
N1 - Publisher Copyright:
© 2021. The Authors.
PY - 2021/12/28
Y1 - 2021/12/28
N2 - 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.
AB - 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.
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U2 - 10.1029/2021GL096410
DO - 10.1029/2021GL096410
M3 - Article
C2 - 35865360
AN - SCOPUS:85121694432
SN - 0094-8276
VL - 48
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 24
M1 - e2021GL096410
ER -