A reformulation of the minimization control variables in the CMA-MESO km-scale variational assimilation system

In order to improve the analysis capability of micro- and meso-scale flows and provide a kilometer-scale applicable assimilation scheme for the China Meteorological Administration (CMA) operational regional numerical weather prediction system CMA-MESO, a new formulation of the minimization control variables in the GRAPES (Global/Regional Assimilation and Prediction System) variational assimilation system has been developed. The new scheme uses eastward velocity u and northward velocity v to replace the original stream function and velocity potential as the new momentum control variables, and uses temperature and surface pressure (T, p_s) to replace the original unbalanced dimensionless pressure as the new mass field control variable. In addition, the new scheme no longer introduces quasi-geostrophic balance constraint but uses a weak mass continuity constraint to ensure analysis balance. Results of background error statistics and numerical experiments show that the adoption of the reformulated control variables results in a more local propagation of observational information and a more reasonable analysis, avoiding the spurious correlation problem of the original scheme when applied at micro- and meso-scale analysis. The introduction of the weak mass continuity constraint suppresses unrealistic convergence and divergence in the analysis, making the new analysis more balanced. Results of one-month assimilation cycles and forecasts show that the new scheme can reduce analysis errors in wind and mass fields, which in turn significantly improves precipitation and 10 m wind field forecast scores of the CMA-MESO system.