Department of Meteorology and Atmospheric Science Center for Advanced Data Assimilation and Predictability Techniques The Pennsylvania State University University Park PA USA
I.M. Systems Group Inc. (IMSG) College Park MD USA
Nanjing University Nanjing China
National Center for Atmospheric Research (NCAR) University Park PA USA
Department of Civil Engineering The University of Tokyo Tokyo Japan
School of Meteorology The University of Oklahoma Norman OK USA
Department of Global Environment and Disaster Prevention Sciences Hirosaki University Hirosaki Japan
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.
@article{osti_1837478,
author = {Zhang, Yunji and Sieron, Scott B. and Lu, Yinghui and Chen, Xingchao and Nystrom, Robert G. and Minamide, Masashi and Chan, Man‐Yau and Hartman, Christopher M. and Yao, Zhu and Ruppert, Jr., James H. and others},
title = {Ensemble‐Based Assimilation of Satellite All‐Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017)},
annote = {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.},
doi = {10.1029/2021GL096410},
url = {https://www.osti.gov/biblio/1837478},
journal = {Geophysical Research Letters},
issn = {ISSN 0094-8276},
number = {24},
volume = {48},
place = {United States},
publisher = {American Geophysical Union (AGU)},
year = {2021},
month = {12}}
Pennsylvania State University, University Park, PA (United States)
Sponsoring Organization:
National Aeronautics and Space Administration (NASA); National Center for Atmospheric Research (NCAR); National Oceanic and Atmospheric Administration (NOAA); National Science Foundation (NSF); Office of Naval Research (ONR); USDOE; USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI ID:
1837478
Alternate ID(s):
OSTI ID: 1837481 OSTI ID: 1903939
Journal Information:
Geophysical Research Letters, Journal Name: Geophysical Research Letters Journal Issue: 24 Vol. 48; ISSN 0094-8276