A monthly 0.01° terrestrial evapotranspiration product (1982–2018) for the Tibetan Plateau

Abstract. Evapotranspiration (ET) is an important component of the water balance system in the “Asian water tower” region, the Tibetan Plateau (TP). However, accurately monitoring and understanding the spatial and temporal variability of the ET components (soil evaporation E_s, canopy transpiration E_c, and intercepted water evaporation E_w) on the TP remains gravely challenging due to the paucity of observational data for this remote area. In this study, the 37 years (1982–2018) of monthly ET component data for the TP were produced using the MOD16-STM model, which uses the recently available soil properties, meteorological conditions, and remote sensing datasets. The estimated ET results correlate very well with the measurements from nine flux towers, with a low root mean square error of 13.48 mm/month, mean bias of 2.85 mm/month, coefficient of determination of 0.83, and index of agreement of 0.92. The annual average ET for the entire TP (specified as elevations higher than 2500 m) is about 0.93 ± 0.037 Gt/year. The main contribution of the ET on the TP comes from the soil, with the E_s accounting for more than 84 % of the ET. During the study period, the ET exhibited a significant increasing trend, with rates of about 1–4 mm/year (p < 0.05), over most parts of the central and eastern TP and a significant decreasing trend, with rates of −3 to −1 mm/year, over the northwestern TP. The rate of increase in the ET on the TP over the past 37 years was around 0.96 mm/year. The increase in the ET over the entire TP from 1982 to 2018 can be explained by the warming and wetting trend of the climate on the TP during this period. The MOD16-STM ET data exhibited an acceptable performance over the TP compared with previous results. The MOD16-STM ET can adequately represent the actual ET and can be used for research on water resource management, drought monitoring, and ecological change. The whole datasets are freely available at the Science Data Bank (http://doi.org/10.11922/sciencedb.00020, Y. Ma, X.Chen, L. Yuan, 2021) and the National Tibetan Plateau Data Center (TPDC) (http://doi.org/10.11888/Terre.tpdc.271913, L. Yuan, X.Chen, Y. Ma, 2021).