YE Xiaomin, LIN Mingsen, YUAN Xinzhe, DING Jing, XIE Xuetong, ZHANG Yi, XU Ying. Satellite SAR observation of the sea surface wind field caused by rain cells[J]. Acta Oceanologica Sinica, 2016, 35(9): 80-85. doi: 10.1007/s13131-016-0936-4
Citation: YE Xiaomin, LIN Mingsen, YUAN Xinzhe, DING Jing, XIE Xuetong, ZHANG Yi, XU Ying. Satellite SAR observation of the sea surface wind field caused by rain cells[J]. Acta Oceanologica Sinica, 2016, 35(9): 80-85. doi: 10.1007/s13131-016-0936-4

Satellite SAR observation of the sea surface wind field caused by rain cells

doi: 10.1007/s13131-016-0936-4
  • Received Date: 2015-09-14
  • Rev Recd Date: 2015-11-09
  • Rain cells or convective rain, the dominant form of rain in the tropics and subtropics, can be easy detected by satellite Synthetic Aperture Radar (SAR) images with high horizontal resolution. The footprints of rain cells on SAR images are caused by the scattering and attenuation of the rain drops, as well as the downward airflow. In this study, we extract sea surface wind field and its structure caused by rain cells by using a RADARSAT-2 SAR image with a spatial resolution of 100 m for case study. We extract the sea surface wind speeds from SAR image by using CMOD4 geophysical model function with outside wind directions of NCEP final operational global analysis data, Advance Scatterometer (ASCAT) onboard European MetOp-A satellite and microwave scatterometer onboard Chinese HY-2 satellite, respectively. The root-mean-square errors (RMSE) of these SAR wind speeds, validated against NCEP, ASCAT and HY-2, are 1.48 m/s, 1.64 m/s and 2.14 m/s, respectively. Circular signature patterns with brighter on one side and darker on the opposite side on SAR image are interpreted as the sea surface wind speed (or sea surface roughness) variety caused by downdraft associated with rain cells. The wind speeds taken from the transect profile which superposes to the wind ambient vectors and goes through the center of the circular footprint of rain cell can be fitted as a cosine or sine curve in high linear correlation with the values of no less than 0.80. The background wind speed, the wind speed caused by rain cell and the diameter of footprint of the rain cell with kilometers or tens of kilometers can be acquired by fitting curve. Eight cases interpreted and analyzed in this study all show the same conclusion.
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