ESTIMATION OF SURFACE PRECIPITATION FIELD BASED ON MULTI-SOURCE DATA AND QUALITY INFORMATION

The ground quantitative precipitation estimation (QPE) is a key issue from operational hydrology perspective. Works on multi-source QPE are carried out in IMGW-PIB for a new hydrological platform in Poland. The QPE is a combination of data provided by: (i) telemetric rain gauge network, (ii) weather radar network POLRAD: eight Doppler radars, and (iii) meteorological satellite Meteosat (visible and infrared observations). The data burdened with errors of different structures are generated with various spatial and temporal resolutions. The data quality is characterized by means of quality index (QI). For each of the three data sources different algorithms for their quality determination are designed. Radar data are quality controlled by RADVOL-QC software, spatially interpolated rain gauge data are characterized due to their quality, mainly by distances to nearest gauges, and estimates based on Meteosat observations are assessed by comparison of two different estimation methods. The final quality-based QPE is generated with 1-km space resolution every 10 minutes. The approach for quality-based combination is conditional merging which considers quality information. This method takes advantage of good points of each kind of data, i.e. high spatial resolution of radar observation, unbiased rain gauge data from relatively dense gauge network, and high availability of satellite images.