Application and Evaluation of the Gravel Parameterization Scheme in WRF‐CLM4 Model

As the gravel is a vital component of soil that affects the soil hydrothermal condition, its application can help improve the numerical simulations. In this study, a soil data set containing gravel content suitable to the Weather Research and Forecasting Model‐Community Land Model version 4 (WRF‐CLM4) is firstly established, and a gravel parameterization scheme is coupled to the WRF‐CLM4. On this basis, numerical simulations are conducted over the Tibetan Plateau, whose results are further compared with the global atmospheric Re‐Analysis released by the China Meteorological Administration (CRA‐40) for evaluation. The results show that the new scheme can improve the simulation effect of soil temperature to a certain extent. The correlation coefficient (R) with the CRA‐40 data for soil temperature is enhanced in the shallow soil layer in the new scheme. Besides, the root mean square errors (RMSEs) of soil temperature are significantly reduced in shallow soil layer. Comparatively, the new scheme has a better simulation effect for soil moisture. The values of R increase significantly for soil moisture in the shallow soil layer. The RMSEs for soil moisture in both shallow and deep layers are greatly reduced. Regional‐averages over the three areas and time series show that gravel has large impact on soil temperature and moisture compared with the old scheme. Overall, the values of R and RMSEs for soil temperature and moisture in the new scheme have been greatly improved, while their trends in the shallow layer are closer to the comparison data.