中文摘要：

水体表面温度是研究全球或区域气候变化、数值天气预报的重要参数,是控制水体与大气热量、水分交换的重要变量,对理解水体生物物理过程具有重要意义。卫星观测水表温度具有传统手段不可比拟的技术优势,同时也存在精度和质量上的限制和挑战。本文总结了观测水表温度常用的红外、微波传感器及其分辨率特征,并比较分析了各类传感器的优势、劣势和分辨率适用的时空尺度;在区别不同手段观测的水表温度基础上,分别概述了红外遥感和微波遥感反演水表温度的理论基础,以及常用的算法模型;基于水表温度反演的原理和过程,系统分析了云、水汽、气溶胶、比辐射率等不确定性因素,对反演精度的影响及解决方法,并对精度验证方法做了简单介绍;最后,对水体表面温度反演的发展趋势进行了展望,并指出多源数据的同化融合、优势互补是提升水温反演精度的重要途径。

英文摘要：

Water surface temperature（including sea surface temperature and lake water surface temperature） is a key parameter for studying global or regional climate change and numerical weather prediction（NWP）, as well as being an essential controlling variable in the exchange of heat, moisture and gases between water surface and atmosphere. It has important significance for understanding the biophysical processes of water body. Satellite measurements of water surface temperature are well established with 30 years＇ collection of practical data and have incomparable advantages over traditional observations. Their limitations and challenges are also identified at the same time. There are more than 30 types of infrared/microwave radiometers which can be used for measuring SST/LWST, and their resolutions, advantages and disadvantages are summarized and compared in this paper.SST/LWST measurements depend on a combination of atmospheric properties and water surface radiances.Therefore, it is necessary to adjust and correct the atmospheric effect and water surface processes. The basic principles and the main types of algorithms for water surface temperature inversion using infrared and microwave data are illuminated and reviewed briefly. There are many uncertainties associated with SST/LWST measurements,and the magnitude of these uncertainties has put restrictions on the application or interpretation of SST/LWST measurements. A detailed analysis about these uncertainties in both infrared and microwave SST/LWST retrieval including undetected cloud, water vapor, aerosols, emissivity and skin effect is conducted. In order to determine the uncertainties in satellite-derived surface temperature, the validation of surface temperature retrieval is an indispensable step. Finally, a prospection about the trend of water surface temperature retrieval is proposed. Additionally, a strategy is advised for assimilating measurements from multi- sensor data in order to take the advantage of their complementary strengths.