Liu Baojian, Wan Wei, Xie Hongjie, Li Huan, Zhu Siyu, Zhang Guoqing, Wen Lijuan, Hong Yang
School of Earth and Space Sciences, Peking University, Beijing, 100871, China.
Department of Geological Sciences, University of Texas at San Antonio, San Antonio, Texas, 78249, USA.
Sci Data. 2019 May 2;6(1):48. doi: 10.1038/s41597-019-0040-7.
Lake surface water temperature (LSWT) is of vital importance for hydrological and meteorological studies. The LSWT ground measurements in the Tibetan Plateau (TP) were quite scarce because of its harsh environment. Thermal infrared remote sensing is a reliable way to calculate historical LSWT. In this study, we present the first and longest 35-year (1981-2015) daytime lake-averaged LSWT data of 97 large lakes (>80 km each) in the TP using the 4-km Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data. The LSWT dataset, taking advantage of observations from NOAA's afternoon satellites, includes three time scales, i.e., daily, 8-day-averaged, and monthly-averaged. The AVHRR-derived LSWT has a similar accuracy (RMSE = 1.7 °C) to that from other data products such as MODIS (RMSE = 1.7 °C) and ARC-Lake (RMSE = 2.0 °C). An inter-comparison of different sensors indicates that for studies such as those considering long-term climate change, the relative bias of different AVHRR sensors cannot be ignored. The proposed dataset should be, to some extent, a valuable asset for better understanding the hydrologic/climatic property and its changes over the TP.
湖泊表层水温(LSWT)对于水文和气象研究至关重要。由于青藏高原(TP)环境恶劣,其地面LSWT测量数据相当稀少。热红外遥感是计算历史LSWT的可靠方法。在本研究中,我们利用4千米分辨率的高级甚高分辨率辐射计(AVHRR)全球区域覆盖(GAC)数据,呈现了青藏高原97个大型湖泊(每个湖泊面积大于80平方千米)首个也是最长的35年(1981 - 2015年)日间湖泊平均LSWT数据。该LSWT数据集利用了美国国家海洋和大气管理局(NOAA)下午卫星的观测数据,包括每日、8天平均和月平均三个时间尺度。由AVHRR得出的LSWT与其他数据产品(如中分辨率成像光谱仪(MODIS),均方根误差(RMSE) = 1.7°C;以及ARC - Lake,RMSE = 2.0°C)具有相似的精度。不同传感器的相互比较表明,对于诸如考虑长期气候变化的研究,不同AVHRR传感器的相对偏差不可忽视。所提出的数据集在一定程度上应是更好理解青藏高原水文/气候特性及其变化的宝贵资源。