Retrieval algorithm of sea surface wind vectors for WindSat based on a simple forward model

• Published in: Chinese journal of oceanology and limnology 2013, Vol.31 (1), p.210-218
• Main Author: 赵屹立
• Format: Article
• Language: English
• Subjects: Algorithms; Data buoys; data collection; Earth and Environmental Science; Earth Sciences; linear models; Marine; Maximum likelihood estimation; Meteorological satellites; Microwave radiometers; Ocean-atmosphere interaction; Oceanography; Physics; Polarimetry; Radiometers; Radiometry; Remote sensing; Retrieval; Sea surface; Stokes parameters; Stokes参数; Surface wind; Vectors; Wind direction; Wind measurement; Wind speed; Wind vectors; 多元线性回归; 微波辐射计; 最大似然估计; 检索算法; 正演模型; 海面风速; 风矢量
• ISSN: 0254-4059; 2096-5508; 1993-5005; 2523-3521
• DOI: 10.1007/s00343-013-2079-1

WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center (NDBC), root mean square errors are 1.2 m/s and 30° for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.