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Validation of wind speed retrieval from HY-2B calibration microwave radiometer data during tropical cyclones.

Authors :
Chen, Jiale
Hao, Mengyu
Shao, Weizeng
Marino, Armando
Hu, Yuyi
Song, Xingai
Source :
Remote Sensing Letters; Jul2024, Vol. 15 Issue 7, p700-708, 9p
Publication Year :
2024

Abstract

In this letter, we present a validation of the wind speed retrieval from data from the calibration microwave radiometer onboard the Haiyang-2B (HY-2B) satellite against the observations from the stepped-frequency microwave radiometer (SFMR) onboard hurricane aircraft of the National Oceanic and Atmospheric Administration (NOAA) during 50 tropical cyclones (TCs). These data were collected during the cyclone season for the period from 2019 to 2022. The validation yields a root mean square error (RMSE) of 2.99 m s<superscript>−1</superscript>, a correlation coefficient (r) of 0.69, and a scatter index (SI) of 0.21 for the wind speed at wind speeds of <25 m s<superscript>−1</superscript>, which are worse than those achieved through the comparison with the HY-2B scatterometer, i.e. an RMSE of 1.15 m s<superscript>−1</superscript>, an r value of 0.96, and an SI of 0.11. This is probably caused by the fact that the brightness temperature measurement from the calibration microwave radiometer is likely affected by whitecaps caused by wave breaking; however, whitecaps have less influence on the sea surface backscattering signal under a regular sea state. At wind speeds of >25 m s<superscript>−1</superscript>, the accuracy is reduced to an RMSE of 2.19 m s<superscript>−1</superscript>, an r value of 0.75, and an SI of 0.07. In the presence of rain, significant distortion was observed, i.e. a variation of 3 m s<superscript>−1</superscript> for a rain rate of 15 mm hr<superscript>−1</superscript>. This behaviour was also observed in the analysis of the HY-2B scatterometer product at low-to-moderate wind speeds. In this sense, it is believed that correction associated with rain has to be conducted in wind retrieval from HY-2B data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2150704X
Volume :
15
Issue :
7
Database :
Complementary Index
Journal :
Remote Sensing Letters
Publication Type :
Academic Journal
Accession number :
178151927
Full Text :
https://doi.org/10.1080/2150704X.2024.2368926