Analysis and Forecasting of Heavy Rainfall Case on 21 July 2012 with Dynamical Parameters

For the extremely heavy rainfall case occurring between 21 and 22 July 2012 in North China, dynamical parameters, including the moist thermodynamic advection parameter, the vertical component of convective vorticity vector, the thermodynamic wave-activity density, the thermodynamic potential vorticity wave-activity density, the thermodynamic potential divergence wave-activity density, and the baroclinic vorticity were calculated and analyzed with the forecasting dataset obtained from the NCEP/NCAR Global Forecasting System（GFS） model. Results showed that the heavy rainfall case was caused by the interactions of high-level and low-level jet streams, low pressure trough, the sub-tropical high, a cold front, a convergence line, mesovortex, and similar features. The atmosphere in the precipitation region had both dynamic and thermodynamic characteristics of strong upward motion, evident vertical heat transport, downward extending moist isentropic surfaces, and strong vertical wind shear. All these characteristics were included in the studied dynamical parameters, which corresponded to the observed precipitation very well. Areas with high values of certain dynamical parameters calculated from the 48 h forecasting fields from the GFS were spatially near the rainfall areas, which demonstrated that these dynamical parameters can be used to indicate rainfall areas. Using the dynamical parameters to run the heavy rainfall forecasting equations in the GFS forecasting fields, it was found that precipitation forecasted using these dynamical parameters was closer to the observed precipitation compared to that forecasted by the GFS. Analyses of ETS（Equitable Threat Score） showed that for early warning forecasts, dynamical parameters had higher ETS than the GFS, meaning that the aforementioned dynamical parameters could be used to forecast the precipitation and the corresponding heavy rainfall forecasting equations should be routinely applied in weather forecasting.