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 pape...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 rn/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.展开更多
Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105...Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function （VEOF） method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.展开更多
文摘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 rn/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.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences (Nos. KZCX1-YW-12, KZCXZ-YW201)National Natural Science Foundation of China (No. 90411013)
文摘Using interpolation and averaging methods, we analyzed the sea surface wind data obtained from December 1992 to November 2008 by the scatterometers ERS-1, ERS-2, and QuikSCAT in the area of 2°N-39 °N, 105°E-130°E, and we reported the monthly mean distributions of the sea surface wind field. A vector empirical orthogonal function （VEOF） method was employed to study the data and three temporal and spatial patterns were obtained. The first interannual VEOF accounts for 26% of the interannual variance and displays the interannual variability of the East Asian monsoon. The second interannual VEOF accounts for 21% of the variance and reflects the response of China sea winds to E1 Nifio events. The temporal mode of VEOF-2 is in good agreement with the curve of the Nifio 3.4 index with a four-month lag. The spatial mode of VEOF-2 indicates that four months after an E1 Nifio event, the southwesterly anomalous winds over the northern South China Sea, the East China Sea, the Yellow Sea, and the Bohai Sea can weaken the prevailing winds in winter, and can strengthen the prevailing winds in summer. The third interannual VEOF accounts for 10% of the variance and also reflects the influence of the ENSO events to China Sea winds. The temporal mode of VEOF-3 is similar to the curve of the Southern Oscillation Index. The spatial mode of VEOF-3 shows that the northeasterly anomalous winds over the South China Sea and the southern part of the East China Sea can weaken the prevailing winds, and southwesterly anomalous winds over the northern part of the East China Sea, the Yellow Sea, and the Bohai Sea can strengthen the prevailing winds when E1 Nifio occurs in winter. If E1 Nifio happens in summer, the reverse is true.
