Numerical analysis and case experiment for forecasting capability by using high accuracy moisture advectional algorithm

Summary The paper concerns the sensitivity of the regional mesoscale model (MM4) to a moisture transport algorithm with different accuracies, and the effective improvement of the capability to simulate meso-scale synoptical event by using the revised version of the algorithm. The two advective schemes of second-order moment conservational Prather scheme (PRS hereinafter) and the polynomial-fitted fourth-order Bott scheme and the upstream scheme (UPS) are introduced into the MM4 to calculate moisture transport in order to provide other types of the algorithm with different accuracies for choice in addition to the original B grid second-order central scheme. Of the three schemes, the first two ensure the positive definite character with high accuracy (almost no numerical disspation and computational dispersion); and the last one also keeps the positive definite feature, but possesses stronger capability of numerical dissipation. Case studies have been undertaken of several rainstorm and typhoon events by virtue of the different-accuracy moisture transport algorithm, other things being the same. Results reveal great differences between them. An significant improvement is found in determining meso-scale synoptic system structure, rain cluster activity, rainstorm belt and its center, severity and its persistence, and the false alarm of or failure to report subrainstorm center when the PRS scheme is employed. Obviously, these differences and improvement are only due to moisture re-distribution for different schemes of moisture transport and the related variation of latent heat. The paper investigates the influences of different numerical schemes. The high accuracy and positive solution PRS application which produces a significant improvement in the model result, demonstrating the sensitivity of the model to moisture distribution in the model represents an important measure to improve the simulation by means of revising the numerically calculating method.With 11 Figures