基于微波遥感技术海面盐度反演方法

海面盐度(sea surface salinity,SSS)是研究海洋变化及其气候效应重要的物理量,对海洋生态环境、海洋可持续发展至关重要.为了提高海面盐度反演精度,本文通过对SMAP卫星L波段微波辐射计测量的亮温数据进行海面盐度反演研究,考虑风、浪等影响海面粗糙度的环境因子对Klein-Shift模型(简称K-S模型...

Inversion method of sea surface salinity based on microwave remote sensing technology

Sea surface salinity is an important physical quantity in studying ocean changes and climate effects, which are very significant to the marine ecological environment and the sustainable development of the ocean. To improve the accuracy of the sea surface salinity inversion, the brightness temperature data measured by the SMAP L-band microwave radiometer is used to study the sea surface salinity inversion, and the Klein-Shift (K-S) model is improved by considering environmental factors such as wind and waves that affect the sea surface roughness. Comparing the salinity retrieved by Newton''s method with the measured salinity of Argo, results show that the improved K-S model inversion salinity has a significant correlation with the Argo salinity correlation coefficient R=0.99, the average deviation and root mean square error are respectively 0.16 and 0.17, and the residuals are basically distributed within 0.2. For the K-S model, the inversion accuracy is improved by about 0.5. In general, the improved K-S model has a small deviation between the salinity inversion and the Argo salinity, the inversion accuracy is better than the other two, and the spatial distribution tends to be consistent. Moreover, the spatial variation of sea surface salinity has obvious geographic characteristics of latitude distribution.