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Discussion papers | Copyright
https://doi.org/10.5194/hess-2017-699
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Jan 2018

Research article | 03 Jan 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Evaluation of ORCHIDEE-MICT simulated soil moisture over China and impacts of different atmospheric forcing data

Zun Yin1, Catherine Ottlé1, Philippe Ciais1, Matthieu Guimberteau1,2, Xuhui Wang1,3,4, Dan Zhu1, Fabienne Maignan1, Shushi Peng3, Shilong Piao3, Jan Polcher4, Feng Zhou3, Hyungjun Kim5, and other China-Trend-Stream project members* Zun Yin et al.
  • 1Laboratoire des Sciences du Climat et de l’Environnement, CNRS-CEA-UVSQ, Gif-sur-Yvette 91191, France
  • 2UMR 7619 METIS, Sorbonne Universités, UPMC, CNRS, EPHE, 4 place Jussieu, Paris 75005, France
  • 3Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • 4Laboratoire de Météorologie Dynamique, UPMC/CNRS, IPSL, Paris 75005, France
  • 5Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
  • *A full list of authors and their affiliations appears at the end of the paper.

Abstract. 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), are used to drive simulations in China by the land surface model ORCHIDEE-MICT. Simulated soil moisture is compared with in-situ and satellite datasets at different spatial and temporal scales in order to: 1) estimate the ability of ORCHIDEE-MICT (ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature) to represent soil moisture dynamics in China; 2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow river basins; 3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China (median r=0.53; RMSE=0.06m3m−3), but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to RMSE (RMSEGSWP3=0.05m3m−3) and correlation coefficient (rWFDEI=0.64) respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies. The mismatch between simulated and observed soil moisture is mainly explained by squared bias (SB) and lack of correlation weighted by the standard deviation (LCS). Large SB suggests that the parameterization in ORCHIDEE-MICT should be calibrated for further study in China. High LCS and underestimated soil moisture in the North China Plain demonstrate possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies (D) of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the D of soil moisture is mainly caused by the D in precipitation frequency and air humidity rather than precipitation amount.

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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3,...
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