Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements

Liu, Shubo; Li, Yinan; Yang, Xiaojiao; Zhou, Wu; Lv, Ailing; Jin, Xu; Dang, Hongxing

doi:10.3390/rs14133016

Open AccessArticle

Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements

by

Shubo Liu

^1,*,

Yinan Li

¹,

Xiaojiao Yang

¹,

Wu Zhou

²

,

Ailing Lv

¹,

Xu Jin

¹ and

Hongxing Dang

¹

China Academy of Space Technology (Xi’an), Xi’an 710100, China

²

National Satellite Ocean Application Service, Beijing 100081, China

^*

Author to whom correspondence should be addressed.

Remote Sens. 2022, 14(13), 3016; https://doi.org/10.3390/rs14133016

Submission received: 28 April 2022 / Revised: 9 June 2022 / Accepted: 20 June 2022 / Published: 23 June 2022

(This article belongs to the Special Issue Remote Sensing of Ocean Surface Winds)

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Abstract

The space-borne microwave radiometers and scatterometers can effectively measure global sea surface winds under non-precipitation. However, the measurements in rainy conditions significantly degrade, which are usually flagged as poor quality or invalidated for some scientific purposes. This paper develops a combined active–passive wind vector retrieval model for rainy conditions based on the HY-2B radiometer and scatterometer measurements. In our model, the polarization ratio of brightness temperatures at 6.925 GHz (PR06) is used as an indicator to implicitly represent the rain effect. For wind speed retrieval, a statistical regression model is trained as a function of PR06 and brightness temperatures of the radiometer. Moreover, two new geophysical model functions, including rain effect, are developed for wind direction inversion. Comparisons between HY-2B retrieval results and ERA5 wind products indicate that the retrieval model performs well under all rainy conditions. The overall root mean squared errors (RMSEs) of wind speed and direction retrievals are 1.60 m/s and 20.60°, respectively. With an increase in the rain rate, the wind retrieval performance degrades slightly and still provides a reliable retrieval result.

Keywords: sea surface wind speed; rain; HY-2B; active–passive; retrieval

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MDPI and ACS Style

Liu, S.; Li, Y.; Yang, X.; Zhou, W.; Lv, A.; Jin, X.; Dang, H. Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements. Remote Sens. 2022, 14, 3016. https://doi.org/10.3390/rs14133016

AMA Style

Liu S, Li Y, Yang X, Zhou W, Lv A, Jin X, Dang H. Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements. Remote Sensing. 2022; 14(13):3016. https://doi.org/10.3390/rs14133016

Chicago/Turabian Style

Liu, Shubo, Yinan Li, Xiaojiao Yang, Wu Zhou, Ailing Lv, Xu Jin, and Hongxing Dang. 2022. "Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements" Remote Sensing 14, no. 13: 3016. https://doi.org/10.3390/rs14133016

APA Style

Liu, S., Li, Y., Yang, X., Zhou, W., Lv, A., Jin, X., & Dang, H. (2022). Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements. Remote Sensing, 14(13), 3016. https://doi.org/10.3390/rs14133016

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Sea Surface Wind Retrieval under Rainy Conditions from Active and Passive Microwave Measurements

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