The operational radar based quantitative precipitation estimation in Denmark and its potential application in hydrological modeling

The Danish Meteorological Institute (DMI) is responsible for the operation of five C-band Doppler radars in Denmark for weather monitoring purposes. In the current setup, volume scans are undertaken every 10 minutes and have an entire nationwide coverage. CAPPI products are generated with the same time interval and converted to daily precipitation products by DMI's own areal radar precipitation algorithm, ARNE (for Arealnedbør in Danish).

The current version of ARNE consists of two modules. One is a single power law reflectivity-to-rainfall (Z-R) relationship and the other is a complex range dependent bias adjustment adapted from Baltic Sea Experiment (BALTEX). Other software packages concerning radar image clutter removal, hydrometeor classification based on synoptic temperature observations and storm type (stratiform/convective) separation are under development and will be added to the algorithm shortly. The algorithm was tested against an independent dataset for 2006, and daily precipitation was analyzed according to weather type (widespread rain, shower, drizzle) and precipitation type (rain, sleet, snow). The algorithm performs quite well for heavy rain events but has certain limitations in conditions such as drizzle or scattered light rain.

Due to the need of automation and optimization of the national raingauge network, a study was carried out to evaluate the performance of ARNE with respect to raingauge density. The study allows 6 scenarios with an increasing number of raingauges involved in ARNE's bias adjustment process. The results show a general reduction of bias with the increase of raingauge density. However, no optimal solution for balancing acceptable performance and appropriate investment was found.

In collaboration with the HOBE (Hydrological Observatory and Exploratorium) research center, which is a Danish initiative on water resources research bringing together five different universities and institutes, the final product of ARNE will be applied into integrated hydrological modeling. It is widely recognized that the precipitation input is one of the most important error sources in the simulation of surface water runoff. MIKE-SHE, which is a distributed full scale hydrological model, will be the modeling tool applied. In contrast with previous 10×10 km grid products based on raingauge observations, radar precipitation is expected to have a much higher spatial accuracy with a resolution up to 500×500 m.