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

Yunji Zhang, Scott B. Sieron, Yinghui Lu, Xingchao Chen, Robert G. Nystrom, Masashi Minamide, Man Yau Chan, Christopher M. Hartman, Zhu Yao, James H. Ruppert, Atsushi Okazaki, Steven J. Greybush, Eugene E. Clothiaux, Fuqing Zhang

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

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.

Original languageEnglish (US)
Article numbere2021GL096410
JournalGeophysical Research Letters
Volume48
Issue number24
DOIs
StatePublished - Dec 28 2021

All Science Journal Classification (ASJC) codes

  • Geophysics
  • General Earth and Planetary Sciences

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