As more and more flood forecasting systems utilise quantitative precipitation forecast (QPF) in order to get a longer lead time, particularly for flash flood, attention has fallen upon the quality of QPF in such a model-train context. Weather radar and numerical weather predication (NWP) are two important sources for quantitative precipitation forecast both of which have pros and cons. In this paper, an attempt to combine rainfall prediction from radar and high resolution mesoscale weather model is discussed to explore the advantages from both sides. Data sets of a weather radar located over the Odra catchment in Poland have been collected for several months during which several heavy rainfall events have been selected. A mesoscale weather model (MM5) with high resolution has been set up over the same area to match the radar scans. The rainfall field is firstly corrected using raingauges values and then displacement is applied in accordance with the maximum cross-correlation between radar images and NWP fields; the final product therefore is able to incorporate both high accuracy forecast field locations from radar and growing-decaying mechanisms from NWP models. This study shows the practical values of applying QPF in flood forecasting.
|Translated title of the contribution||An experiment of rainfall prediction over the odra catchment by combining weather radar and a numerical weather model|
|Title of host publication||7th International Conference on Hydroinformatics, Nice, France|
|Number of pages||8|
|Publication status||Published - 2006|