Creation of a high resolution precipitation data set by merging gridded gauge data and radar observations for Sweden

Abstract

Summary Hydrological forecasting systems require accurate initial conditions, particularly for real time precipitation data, which are problematic to retrieve. This is especially difficult for high temporal and spatial resolutions, e.g. sub-daily and less than 10–20 km. Forecasting fast processes such as flash flood are, however, dependent on such high resolution data. Gridded gauge data produces too smooth fields and underestimates small scale phenomena, such as convection, whereas radar composites contain the small scale information, but suffer from inconsistencies between individual radars and have poor long term statistics. Here, we present a method to merge a radar composite with daily resolution gridded gauge data for Sweden for the time period 2009–2014 to produce a one hourly 4 × 4 km2 data set. The method consists of a main step where monthly accumulations of the radar data are scaled by those retrieved from the gridded data for each month. An optional quantile mapping based bias correction step makes sure that the daily intensity distribution agrees with the gridded observations. Finally, the data are dis-aggregated to an hourly time resolution. This results in a data set which has the same long-term spatial properties as the gridded observations, but with the spatial and temporal details of the radar data. Validation of the method is performed with high resolution gauge data, and shows a high quality of the derived product.