卫星遥感业务系统海表温度误差控制方法

A temperature error control technology for an operational satellite application system

提高卫星遥感海表温度的反演精度是各种反演模型追求的目标,也是遥感系统业务化应用的关键.据相关文献报道,在晴空无云的条件下遥感海表温度的精度达到了0 5℃,但考虑到影响海表温度反演精度的多种因素,在遥感业务系统真正实现SST精度在1℃以内是非常困难的.在北太平洋渔场速报制作系统中,对遥感海表温度与船测温度误差统计显示均方根误差达到5 71℃,匹配点误差分布显示存在大量较大的负误差值,最大的为-17 2℃,遥感温度图也反映出存在片状温度低值区,这些区域很可能被错误地当作冷涡或冷锋区,严重干扰渔情分析,这些异常的温度误差很难通过海表温度反演模式和云检测技术来消除.采用一种标准海表温度参考图用于温度误差控制技术,可有效地检测温度反演异常值,将均方根值从5 71℃降低到1 75℃,如果采用2℃阈值控制计算均方根值,则海表温度精度达到0 785℃.该方法基本消除了遥感海表温度的低值现象,明显提高了遥感海表温度的精度,并已成功地应用于北太平洋渔区的海况速报产品制作中.

The accuracy of satellite measured sea surface temperature (SST) is the key for both SST algorithms and applications, which is reported to reach 0.5 ℃. In fact, the accuracy of satellite-measured SST is affected by many factors, it is very difficult to obtain root mean square (RMS) error within 1 ℃ in an operational satellite SST application system. Many values of SST are found to be much lower than temperature measured by the ships in evaluating the accuracy of SST derived from NOAA satellite data. The error distribution shows that larger negative values of temperature bias take up a high proportion with the maximum up to -17.2 ℃. Many patches of low temperature abnormality, distributing in the SST images, are caused by thin clouds or fogs, which may be mistakenly taken as eddy or front. The temperature abnormality is very difficult to be detected by SST inversion algorithm and cloud detection technology. A temperature error control technology is developed employing standard reference temperature images to detect the temperature abnormality. This method can efficiently detect the temperature abnormality to remove the abnormal low values of SST and improve the accuracy of satellite measured SST. The RMS error is improved from 5.71 to 1.75 ℃ in an operational SST system. It has been applied to drawing the fishery chart products of the North Pacific.