基于CALIOP双波长数据的海面测风信号筛选方法研究

Screening method of sea surface signals based on CALIOP dual-wavelength data

基于海面后向散射模型,提出了一种利用CALIOP双波长海面信号进行数据质量控制的星载激光雷达数据筛选方法。选取CALIOP 2018年1―9月Version 4.1.0 level 1数据进行全球海面风速反演,为提高数据可利用率,在无云海域探测海面风速的条件下增加了可穿透云CALIOP数据,经过大气校正和双波长信号质量控制后进行风速反演,以准同步AMSR-2风速数据作为参考值进行检验。分别采用Cox-Munk和Hu模型的经验关系反演风速,对于1―3月数据,前者标准偏差分别为1.14、1.18、1.16 m/s,相关系数分别为0.90、0.91、0.91;后者标准偏差分别为1.17、1.19、1.17 m/s,相关系数分别为0.91、0.91、0.91。而相较于无云海域的反演研究,可利用数据量提高约45.5%,表明利用该方法既能保证反演精度同时又能有效提高数据可利用率,可为海面风场研究提供更多的数据源。

Based on the sea surface backscattering model,a space-borne lidar data screening method using CALIOP dual-wavelength sea surface signal for data quality control is proposed.The global sea surface wind speed is retrieved from CALIOP's Version 4.1.0 level 1 data from January to September 2018.In order to improve data availability,under the condition of detecting sea surface wind speed in cloudless sea area,the cloud-penetrating CALIOP data were added,and then wind speed inversion was carried out after atmospheric correction and dual-wavelength signal quality control.At last,quasi-synchronous AMSR-2 wind speed data were used as reference values for verification.The two empirical relationships of Cox Munk model and Hu model were used to invert wind speed respectively.For the data from January to March,the standard deviations of the former model are 1.14,1.18 and 1.16m/s,respectively,with correlation coefficients of 0.90,0.91 and 0.91,while the standard deviations of the latter are 1.17,1.19 and 1.17m/s,respectively,with correlation coefficients of 0.91,0.91 and 0.91.In addition,compared with the inversion study in cloudless sea,the available data amount using the proposed method increases by about 45.5%.The results show that the method proposed can not only ensure the accuracy of inversion but also effectively improve the utilization rate of data,which can provide more data sources for the study of sea surface wind field.