Title | A global terrestrial evapotranspiration product based on the three-temperature model with fewer input parameters and no calibration requirement |
Authors | Yu, Leiyu Qiu, Guo Yu Yan, Chunhua Zhao, Wenli Zou, Zhendong Ding, Jinshan Qin, Longjun Xiong, Yujiu |
Affiliation | Peking Univ, Shenzhen Grad Sch, Sch Environm & Energy, Shenzhen 518055, Peoples R China Columbia Univ, Dept Earth & Environm Engn, New York, NY 10027 USA Max Planck Inst Biogeochem, Hans Knoll Str 10, D-07745 Jena, Germany Shenzhen Investment Holdings Co LTD, Shenzhen 518048, Peoples R China Sun Yat Sen Univ, Sch Civil Engn, Guangzhou 510275, Peoples R China Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Peoples R China |
Keywords | LATENT-HEAT FLUX SURFACE-TEMPERATURE EDDY COVARIANCE EVAPORATION MODIS UNCERTAINTY CHINA SCALE GLDAS ALGORITHM |
Issue Date | 12-Aug-2022 |
Publisher | EARTH SYSTEM SCIENCE DATA |
Abstract | Accurate global terrestrial evapotranspiration (ET) estimation is essential to better understand Earth's energy and water cycles. Although several global ET products exist, recent studies indicate that ET estimates exhibit high uncertainty. With the increasing trend of extreme climate hazards (e.g., droughts and heat waves), accurate ET estimation under extreme conditions remains challenging. To overcome these challenges, we used 3 h and 0.25 degrees Global Land Data Assimilation System (GLDAS) datasets (net radiation, land surface temperature (LST), and air temperature) and a three-temperature (3T) model, without resistance and parameter calibration, in global terrestrial ET product development. The results demonstrated that the 3T model-based ET product agreed well with both global eddy covariance (EC) observations at daily (root mean square error (RMSE) = 1 1 mm (d(-1), N = 294 058) and monthly (RMSE = 24 9 mm month(-1), N = 9632) scales and basin-scale water balance observations (RMSE = 116.0 mm yr(-1), N = 34). The 3T model-based global terrestrial ET product was comparable to other common ET products, i.e., MOD16, P-LSH, PML, GLEAM, GLDAS, and Fluxcom, retrieved from various models, but the 3T model performed better under extreme weather conditions in croplands than did the GLDAS, attaining 9.0 %-20 % RMSE reduction. The proposed daily and 0.25 degrees ET product covering the period of 2001-2020 could provide periodic and large-scale information to support water-cycle-related studies. The dataset is freely available at the Science Data Bank (https://doi.org/10.57760/sciencedb.o00014.00001, Xiong et al., 2022). |
URI | http://hdl.handle.net/20.500.11897/650433 |
ISSN | 1866-3508 |
DOI | 10.5194/essd-14-3673-2022 |
Indexed | SCI(E) |
Appears in Collections: | 深圳研究生院待认领 |