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… Click to show full abstract
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 km2 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.Design Type(s)data collection and processing objective • statistical analysis and modeling objective • time series designMeasurement Type(s)temperature of waterTechnology Type(s)satellite imagingFactor Type(s)geographic location • size • temporal_intervalSample Characteristic(s)Tibetan Plateau • lakeMachine-accessible metadata file describing the reported data (ISA-Tab format)
               
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