Hourly Quantitative Precipitation Estimation (QPE) Integration performance in Deep Convection Events for Southern Brazil

The Parana State is located at a 22º S - 27º S latitude range in Brazil and has characteristics of tropical and subtropical regimes. Cold fronts lead the regime in winter and spring seasons producing convection inside it. At the west, in the border with Paraguay, Convective Systems and Mesoscale Complex Convective (MCC) rule the storms in spring and summer seasons. In this period, squall lines occur over all state due the heat and moisture advection from Amazon Basin and northwestern regions. In this paper we investigate the Quantitative Precipitation Estimation (QPE) by radar and satellite information in convective environment and explosive events. Besides individual estimates of radar and satellite, the raingauge network was used to produce a 1hr-time integrated solution through the Poisson equation. The radar QPE was obtained from the reflectivity data of the S-Band Doppler radar located in Teixeira Soares (center of Parana), reflectivity and differential reflectivity from the Polarimetric S-Band radar situated at Cascavel city, near the Paraguay. The Multi-Sensor Precipitation Estimation (MPE) technique was used to provide the hourly satellite QPE. The integration of the three data type was yield from the Poisson equation, which was numerically solved using the parallel Multigrid algorithm that converged quickly to the solution, appropriated to the operational use. The first advantage of this method was the quick convergence of the QPE to the raingauge precipitation amplitude because the raingauge data is used as a boundary condition hypothesis. For that, the quality control of the precipitation data was critical to get a good integration. The second advantage is that the final solution keeps down the mesoscale signature captured by radar mosaic, modifying only the amplitude of the precipitation. The evaluation of the hourly QPE under convective areas show good results only if the bias correction and the hail filter were used. The satellite MPE technique tends to overestimate the precipitation and correction was required. The radar QPE was sensitive to use of the polarimetric information (ZDR and KDP), especially in precipitation rates higher than 20 mmhr 1. The hail “contamination” of the radar data could inhibit a good estimation and filter it is mandatory in all convective studies.