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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/npg-2016-13
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/npg-2016-13
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  27 Jan 2016

27 Jan 2016

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This preprint was under review for the journal NPG. A revision for further review has not been submitted.

Extended Application of the CNOP-P method in the Inner Mongolia using the Common Land Model

Bo Wang1,2,4, Zhenhua Huo3,4, Yujing Yuan5, and Shang Wu2 Bo Wang et al.
  • 1Institute of Applied Mathematics, Henan University, 475004 Kaifeng, China
  • 2School of Mathematics and Statistics, Henan University, 475004 Kaifeng, China
  • 3University of Chinese Academy of Sciences, 100049, Beijing, China
  • 4LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, 100029, Beijing, China
  • 5School of Mathematics, Shandong University, 250100 Jinan, China

Abstract. An extension method of the conditional nonlinear optimal perturbation about parameter (CNOP-P) is adopted to study the soil parameter optimization for the Hulunbeier Steppe within the common land model (CoLM) with the differential evolution (DE) method. Using National Center for Environmental Prediction/Department of Energy (NCEP/DOE) Atmospheric Model Intercomparison Project-II (AMIP-II) 6-hourly Reanalysis Gaussian Grid data and National Meteorological Center (NMC) Reanalysis 6-hourly surface fluxes data, three experiments (I and II) were designed to study the impact of the percentages of sand and clay of the shallow soil in CoLM on simulating the shallow soil moisture. To study the shallow soil moisture and the latent heat flux simultaneously, experiment (III) is designed. The optimal parameters obtained by the extended CNOP-P method are used to predict the shallow soil moisture in the following month. In all the three experiments, after optimization stage, the optimal soil parameters could significantly improve the simulation ability of CoLM in the Inner Mongolia to the shallow soil moisture at the stage of prediction; the optimal parameters attained by the double-parameter optimal experiment could make CoLM simulate the shallow soil moisture better than the single-parameter optimal experiment in the optimization slot. Moreover, the results of experiments (I and II) justify the conclusion that the more accurate the atmospheric forcing data and observation data are, the more effective the results of optimization will be.

Bo Wang et al.

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Bo Wang et al.

Bo Wang et al.

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Short summary
Under the background of climate change, researching how the component content of soil affects the simulating ability of CoLM in arid and semiarid area in China; Extension of CNOP-P method is adopted to study the parameter optimization of CoLM with DE optimal method; Convective precipitation and large scale precipitation are almost in accord with the occurrence of the peak of the shallow soil moisture; Optimized parameters make CoLM simulate the objective variable(s) better than before.
Under the background of climate change, researching how the component content of soil affects...
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