Abstract
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∘ 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∘ 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).
Funder
Sichuan Province Science and Technology Support Program
National Natural Science Foundation of China
Shenzhen Science and Technology Innovation Program
Subject
General Earth and Planetary Sciences
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