Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm
A rainfall retrieval algorithm for tropical cyclones (TCs) using 18.7 and 36.5 GHz of vertically and horizontally polarized brightness temperatures (Tbs) from the Microwave Radiation Imager (MWRI) is presented. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorpt...
Published in: | Remote Sensing |
---|---|
Main Authors: | , , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2018
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs10111770 |
id |
ftmdpi:oai:mdpi.com:/2072-4292/10/11/1770/ |
---|---|
record_format |
openpolar |
spelling |
ftmdpi:oai:mdpi.com:/2072-4292/10/11/1770/ 2023-08-20T04:08:01+02:00 Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm Ruanyu Zhang Zhenzhan Wang Kyle A. Hilburn 2018-11-08 application/pdf https://doi.org/10.3390/rs10111770 EN eng Multidisciplinary Digital Publishing Institute Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs10111770 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 10; Issue 11; Pages: 1770 tropical cyclone rain rate precipitation remote sensing radiometer retrieval algorithm Text 2018 ftmdpi https://doi.org/10.3390/rs10111770 2023-07-31T21:49:51Z A rainfall retrieval algorithm for tropical cyclones (TCs) using 18.7 and 36.5 GHz of vertically and horizontally polarized brightness temperatures (Tbs) from the Microwave Radiation Imager (MWRI) is presented. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption and theoretical Mie absorption coefficients at 18.7 and 36.5 GHz. To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. The comparison between MWRI and NSIDC rain rates is relatively encouraging, with a mean bias of −0.14 mm/h and an overall root-mean-square error (RMSE) of 1.99 mm/h. A comparison of pixel-to-pixel retrievals shows that MWRI retrievals are constrained to reasonable levels for most rain categories, with a minimum error of −1.1% in the 10–15 mm/h category; however, with maximum errors around −22% at the lowest (0–0.5 mm/h) and highest rain rates (25–30 mm/h). Additionally, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) Tbs are applied to retrieve rain rates to assess the sensitivity of this algorithm, with a mean bias and RMSE of 0.90 mm/h and 3.11 mm/h, respectively. For the case study of TC Maon (2011), MWRI retrievals underestimate rain rates over 6 mm/h and overestimate rain rates below 6 mm/h compared with Precipitation Radar (PR) observations on storm scales. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rainfall data provided by the Remote Sensing Systems (RSS) are applied to assess the representation of mesoscale structures in intense TCs, and they show good consistency with MWRI retrievals. Text National Snow and Ice Data Center MDPI Open Access Publishing Remote Sensing 10 11 1770 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
tropical cyclone rain rate precipitation remote sensing radiometer retrieval algorithm |
spellingShingle |
tropical cyclone rain rate precipitation remote sensing radiometer retrieval algorithm Ruanyu Zhang Zhenzhan Wang Kyle A. Hilburn Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
topic_facet |
tropical cyclone rain rate precipitation remote sensing radiometer retrieval algorithm |
description |
A rainfall retrieval algorithm for tropical cyclones (TCs) using 18.7 and 36.5 GHz of vertically and horizontally polarized brightness temperatures (Tbs) from the Microwave Radiation Imager (MWRI) is presented. The beamfilling effect is corrected based on ratios of the retrieved liquid water absorption and theoretical Mie absorption coefficients at 18.7 and 36.5 GHz. To assess the performance of this algorithm, MWRI measurements are matched with the National Snow and Ice Data Center (NSIDC) precipitation for six TCs. The comparison between MWRI and NSIDC rain rates is relatively encouraging, with a mean bias of −0.14 mm/h and an overall root-mean-square error (RMSE) of 1.99 mm/h. A comparison of pixel-to-pixel retrievals shows that MWRI retrievals are constrained to reasonable levels for most rain categories, with a minimum error of −1.1% in the 10–15 mm/h category; however, with maximum errors around −22% at the lowest (0–0.5 mm/h) and highest rain rates (25–30 mm/h). Additionally, Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) Tbs are applied to retrieve rain rates to assess the sensitivity of this algorithm, with a mean bias and RMSE of 0.90 mm/h and 3.11 mm/h, respectively. For the case study of TC Maon (2011), MWRI retrievals underestimate rain rates over 6 mm/h and overestimate rain rates below 6 mm/h compared with Precipitation Radar (PR) observations on storm scales. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rainfall data provided by the Remote Sensing Systems (RSS) are applied to assess the representation of mesoscale structures in intense TCs, and they show good consistency with MWRI retrievals. |
format |
Text |
author |
Ruanyu Zhang Zhenzhan Wang Kyle A. Hilburn |
author_facet |
Ruanyu Zhang Zhenzhan Wang Kyle A. Hilburn |
author_sort |
Ruanyu Zhang |
title |
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
title_short |
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
title_full |
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
title_fullStr |
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
title_full_unstemmed |
Tropical Cyclone Rainfall Estimates from FY-3B MWRI Brightness Temperatures Using the WS Algorithm |
title_sort |
tropical cyclone rainfall estimates from fy-3b mwri brightness temperatures using the ws algorithm |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2018 |
url |
https://doi.org/10.3390/rs10111770 |
genre |
National Snow and Ice Data Center |
genre_facet |
National Snow and Ice Data Center |
op_source |
Remote Sensing; Volume 10; Issue 11; Pages: 1770 |
op_relation |
Atmospheric Remote Sensing https://dx.doi.org/10.3390/rs10111770 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs10111770 |
container_title |
Remote Sensing |
container_volume |
10 |
container_issue |
11 |
container_start_page |
1770 |
_version_ |
1774720043056103424 |