Increasing Cloud Coverage Deteriorates Evapotranspiration Estimating Accuracy From Satellite, Reanalysis and Land Surface Models Over East Asia - Yipu Wang; Jiheng Hu; Rui Li; Binbin Song; Mengsteab Hailemariam; Yuyun Fu; Jiawei Duan (Geophysical Research Letters, 2023)
Abstract Accurate estimation of evapotranspiration (ET) can be affected by cloud change, while cloud‐induced bias errors in ET change remain poorly understood. Here we evaluated seven ET data sets from satellite microwave and optical models, atmospheric reanalysis and land surface models over East Asia. Results showed that although the data sets estimated ET changes overall well under mild cloud increase, all of them had a systematic overestimation (by 73.8%–159.8%) and deteriorated capability of capturing ET change under heavy cloud increase, especially over dense vegetation with large cloud cover. Overestimated incident solar radiation under clouds contributed to the deteriorated performances of ET. Cloud‐induced change in radiation and its errors played larger role in summer ET change over densely vegetated lands, while those in air temperature and relative humidity were dominant jointly over grass and barren lands. These results can serve as a reference for improving ET models and their forcing inputs under clouds.