1 research outputs found
Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data
Soil moisture is a key variable of land surface hydrology, and its correct
representation in land surface models is crucial for local to global climate
predictions. The errors may come from the model itself (structure and
parameterization) but also from the meteorological forcing used. In order to
separate the two source of errors, four atmospheric forcing datasets, GSWP3
(Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological
Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental
Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim
reanalysis data), were used to drive simulations in China by the land surface
model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms:
aMeliorated Interactions between Carbon and Temperature). Simulated soil
moisture was compared with in situ and satellite datasets at different
spatial and temporal scales in order to (1) estimate the ability of
ORCHIDEE-MICT to represent soil moisture dynamics in China; (2) demonstrate
the most suitable forcing dataset for further hydrological studies in Yangtze
and Yellow River basins; and (3) understand the discrepancies of simulated
soil moisture among simulations. Results showed that ORCHIDEE-MICT can
simulate reasonable soil moisture dynamics in China, but the quality varies
with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows
the best performance according to the root mean square error (RMSE) and
correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI
are good choices for further hydrological studies in the two catchments. The
mismatch between simulated and observed soil moisture is mainly explained by
the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT
should be revised for further simulations in China. Underestimated soil
moisture in the North China Plain demonstrates possible significant impacts
of human activities like irrigation on soil moisture variation, which was not
considered in our simulations. Finally, the discrepancies of meteorological
variables and simulated soil moisture among the four simulations are
analyzed. The result shows that the discrepancy of soil moisture is mainly
explained by differences in precipitation frequency and air humidity rather
than differences in precipitation amount.</p