Improved SAL method and its application to verifying regional soil moisture forecasting

Abstract

The regional verification of soil moisture is a vital step in evaluating and improving numerical model performance and utilizing forecast results. Currently, even with improved spatial and temporal resolutions of numerical model, verification methods for soil moisture data still rely on the traditional intensity verification parameters, such as mean error (ME) and root-mean-squared error (RMSE). Those methods provide only incomplete and sometimes inaccurate messages and thus hinder a proper evaluation of a forecast model. The SAL method is an object-based regional verification method with respect to precipitation forecasts. Based on the SAL method, a novel object-based method (SAL-DN) is proposed here, which can be used to test regional soil moisture. Both the ideal experiment and real experiment show that the SAL-DN method can reveal the differences between the observed and forecast soil moisture in three aspects: structure, amplitude, and location, and the results can reflect the actual situation. Furthermore, compared with the SAL method, the SAL-DN method is also capable of verifying physical quantities with high-value and low-value centers like temperature. Therefore, the SAL-DN method enhances verification accuracy and can be applied widely.