Status: 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 Wang,Zhenhua Huo,Yujing Yuan,and Shang Wu
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.
How to cite. Wang, B., Huo, Z., Yuan, Y., and Wu, S.: Extended Application of the CNOP-P method in the Inner Mongolia using the Common Land Model, Nonlin. Processes Geophys. Discuss. [preprint], https://doi.org/10.5194/npg-2016-13, in review, 2016.
Received: 19 Jan 2016 – Discussion started: 27 Jan 2016
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...