| WANG Tianyu,PAN Delu,HE Xianqiang,WANG Difeng. 2014. Wind vector retrieval algorithm from spaceborne lidar data. Acta Oceanologica Sinica, 33(3):129－135 |
| Wind vector retrieval algorithm from spaceborne lidar data |
| 星载激光雷达卫星海面风场反演算法研究 |
| Received:October 11, 2013 Revised:February 10, 2014 |
| DOI：10.1007/s13131-014-0448-z |
| Key words:remote sensing spaceborne Lidar wind retrieval GMF |
| 中文关键词: 遥感,星载激光雷达,海面风场,地球物理模型 |
| 基金项目: |
| Author Name | Affiliation | E-mail | | WANG Tianyu | State Key Laboratory of Satellite Ocean Environment Dynamics, the Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | | | PAN Delu | State Key Laboratory of Satellite Ocean Environment Dynamics, the Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | pandelu@sio.org.cn | | HE Xianqiang | State Key Laboratory of Satellite Ocean Environment Dynamics, the Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | | | WANG Difeng | State Key Laboratory of Satellite Ocean Environment Dynamics, the Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China | |
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| Abstract: |
| The principal purpose of this paper is to extract entire sea surface wind's information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to whitecaps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions implied in CMOD5n geophysical models function (GMF). Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted (IDW) from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC's TAO buoy-laying area as survey region in camparison with buoys' wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spatial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error (RMSE) less than 2m/s and wind direction's RMSE less than 21 degree. |
| 中文摘要: |
| 本文利用星载激光雷达CALIPSO Level 1 剖面数据和 Level 2的气溶胶光学厚度(AOD)、云光学厚度(COD)数据进行海面风场反演算法研究,选取2013年3到5月激光雷达脉冲采样点覆盖于NDBC的TAO浮标布放的海区,利用海面均方斜率和风速的经验关系以及CMOD5n地球物理模型(CMF)所隐含的风场变化趋势关系得到了激光雷达海面风场的反演模型。依据退偏比经验修正白帽散射影响,将邻近非奇异值反距离权重插值法(IDW)得到初始修正次表层水体影响,并通过利用NCEP风场时空匹配后的ASCAT卫星风速资料正演后向散射值得到最优次表层水体校正参数,依此建立次表层水体校正算法,并采用NCEP风场去除圆中滤波后的风向模糊。在此基础上,利用CALIPSO星载激光雷达卫星资料反演了东经137?至西经95?,南纬8?至北纬9?海区风场。对NDBC提供的TAO浮标风场数据和METOP卫星ASCAT的25KM海面风场数据进行时空匹配后,对激光雷达海面风场反演结果进行了比较。验证结果表明,本文的风场反演算法精度较好,风速均方根误差均小于2m.sec-1,风向均方根误差均小于21?。 |
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