Flood forecasting: Meteorological data for the European Flood Awareness System
The European Flood Awareness System (EFAS) is in operation as a flood early warning system to be better prepared for floods. KISTERS contributes to EFAS by operating the Meteorological Data Collection Centre of the Copernicus Emergency Management Service (Copernicus EMS MDCC). Together with the Global Precipitation Climatology Centre (GPCC) of the German Weather Service (DWD), KISTERS is engaged in the operation and expansion of the meteorological data center [further information in the press release]. In operations, KISTERS uses Copernicus EMS MDCC to provide daily meteorological information in the form of raster data sets to EFAS. This data is used to calculate reliable flood forecasts throughout Europe up to ten days in advance and to send appropriate early warnings to the national and regional flood centers of the member states, as well as to the European Emergency Response Coordination Centre (ERCC).
Status quo: Flood forecasts and warnings based on reliable data
Currently, twelve active data suppliers provide data from approximately 21,000 measurement stations worldwide. Approximately 11,000 of these stations, which provide data from approximately 55,000 sensors, are located in the area of EFAS. Ten meteorological parameters are recorded, including precipitation, air temperature, wind, vapor pressure and solar radiation. With this, the KISTERS solution generates daily raster data sets by interpolating the station data with a cell size of 5 x 5 km.
KISTERS hosts and operates the system in its own data center in Aachen. The GPCC of the DWD monitors data transfers and data quality, and in the future will extend the system to include additional data providers and measurement stations.
KISTERS already uses Copernicus EMS MDCC to supply both EFAS and the European Forest Fire Information System (EFFIS), and in the future will potentially also provide data for additional applications. The solution is designed so that it can also integrate and process strongly growing data streams. High-performance validation methods and real-time processing of high-resolution time series are the basis for future development after the successful start of operations.