Impact of 4DVAR assimilation of rainfall data on the simulation of mesoscale precipitation systems in a mei-yu heavy rainfall event

Abstract

The multi-scale weather systems associated with a mei-yu front and the corresponding heavy precipitation during a particular heavy rainfall event that occurred on 4{5 July 2003 in east China were successfully simulated through rainfall assimilation using the PSU/NCAR non-hydrostatic, mesoscale, numerical model (MM5) and its four-dimensional, variational, data assimilation (4DVAR) system. For this case, the improvement of the process via the 4DVAR rainfall assimilation into the simulation of mesoscale precipitation systems is investigated. With the rainfall assimilation, the convection is triggered at the right location and time, and the evolution and spatial distribution of the mesoscale convective systems (MCSs) are also more correctly simulated. Through the interactions between MCSs and the weather systems at difierent scales, including the low-level jet and mei-yu front, the simulation of the entire mei-yu weather system is significantly improved, both during the data assimilation window and the subsequent 12-h period. The results suggest that the rainfall assimilation flrst provides positive impact at the convective scale and the in∞uences are then propagated upscale to the meso- and sub-synoptic scales. Through a set of sensitive experiments designed to evaluate the impact of difierent initial variables on the simulation of mei-yu heavy rainfall, it was found that the moisture fleld and meridional wind had the strongest efiect during the convection initialization stage, however, after the convection was fully triggered, all of the variables at the initial condition seemed to have comparable importance.