ISSN 1000-0526
CN 11-2282/P
CN 11-2282/P
Archive > Volume 45 Issue 9 > 2019,45(9):1199-1212. DOI:10.7519/j.issn.1000-0526.2019.09.002 Prev Next
Study on the Numerical Predictivity of Localized Severe Mesoscale Rainstorm in Guangzhou on 7 May 2017
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Abstract:
Severe mesoscale rainstorm struck Guangzhou heavily from deep night of 6 May to early morning of 7 May 2017, and convection initiation was closely related to southerly wind enhancing in boundary layer near Pearl River Delta at night. Comparison between two subgroups in ECWMF ensemble forecasts shows members with strong rainfall have significant lowlevel convergence, updraft, moist air and convective instability in initial conditions. GRAPES mesoscale model performed well in forecasting the dynamic process of southerly wind strengthening in lower level, producing good forecasts for the rainfall process. Ensemble sensitivity analysis reveals that the high sensitivity depends on the relative position, strength of key synoptic systems for high pressure in Yangtze River Basin, high pressure on South China Sea and low pressure trough residing on South China. Precipitation forecast sensitivity to temperature is closely relative to convective instability in boundary layer, the boundary structure with warmer air in nearsurface and colder air near the top of boundary layer would increase convective instability obviously. Three sets of convectivescale simulations are applied to analyze sensitivity of convective precipitation forecast to initial thermal disturbance, lowlevel wind disturbance, and cloud microphysical scheme differences. Convective precipitation forecast shows more sensitivities to initial thermal disturbance compared with lowlevel wind disturbance, and forecast uncertainty could be estimated comprehensively through different cloud microphysical schemes. By carefully analyzing forecast sensitivity due to perturbations in initial conditions and physical process in the convectivescale ensemble forecasts, the predictability of mesoscale heavy rainfall events in warm seasons could be improved.
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