Retrieval of Sea Surface Wind Fields Using Multi-Source Remote Sensing Data

Tangao Hu,Yue Li,Yiyue Wu,Dengrong Zhang,Yao Li

doi:10.3390/rs12091482

Tangao Hu, Yue Li + Show 3 more

Open Access

https://doi.org/10.3390/rs12091482

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Abstract

Timely and accurate sea surface wind field (SSWF) information plays an important role in marine environmental monitoring, weather forecasting, and other atmospheric science studies. In this study, a piecewise linear model is proposed to retrieve SSWF information based on the combination of two different satellite sensors (a microwave scatterometer and an infrared scanning radiometer). First, the time series wind speed dataset, extracted from the HY-2A satellite, and the brightness temperature dataset, extracted from the FY-2E satellite, were matched. The piecewise linear regression model with the highest R2 was then selected as the best model to retrieve SSWF information. Finally, experiments were conducted with the Usagi, Fitow, and Nari typhoons in 2013 to evaluate accuracy. The results show that: (1) the piecewise linear model is successfully established for all typhoons with high R2 (greater than 0.61); (2) for all three cases, the root mean square error () and mean bias error (MBE) are smaller than 2.2 m/s and 1.82 m/s, which indicates that it is suitable and reliable for SSWF information retrieval; and (3) it solves the problem of the low temporal resolution of HY-2A data (12 h), and inherits the high temporal resolution of the FY-2E data (0.5 h). It can provide reliable and high temporal SSWF products.

Highlights

Tropical cyclones (TCs) are one of the most intense weather hazards out of all meteorological phenomena that form over tropical oceans [1]
The wind speed accuracy was calculated, and the root mean square error (RMSE) and mean bias error (MBE) are 1.99 and 1.82 m/s. (2) Fitow: 430 points were successfully matched between the inversion result and the HY-2A wind speed product at 9:00 on October 3rd
The wind speed accuracy was calculated, and the RMSE and MBE are 2.10 and 1.35 m/s. (3) Nari: 360 points were successfully matched between the inversion result and the HY-2A wind speed product at 9:00 on October 12th

Summary

Introduction

Tropical cyclones (TCs) are one of the most intense weather hazards out of all meteorological phenomena that form over tropical oceans [1]. In order to better prevent the disasters caused by TCs, it is necessary to continuously monitor sea surface wind field (SSWF) information, such as wind speed and direction, so as to protect life and property as much as possible [2,3] These data contribute to improved warnings for ships at sea, and to improved global weather forecasts [4]. Microwave scatterometers (MSs) are often used to monitor global SSWFs due to their wide coverage and have the abilities of day-and-night operation and all-weather detection They can be adopted to continuously and simultaneously detect marine dynamic environmental elements with high precision [7,8]. A discussion and conclusions are presented in Sections 5 and 6

Study Area

Wind Speed Data Extraction from HY-2A

Model Validation

Sea Surface Wind Speed Inversion Model Establishment

Limitations of the Proposed Piecewise Model

Conclusions