Janus Willem Schipper

Verification of precipitation from regional climate simulations and remote-sensing observations with respect to ground-based observations in the upper Danube catchment

An evaluation of precipitation fields for four selected months simulated by the regional climate model At-moMM5 and provided by the satellite retrieval method AtmoSat is presented. As reference, observations at 5 km resolution on a daily and monthly basis are used. We applied conventional verification tools (root mean square error, grid-point based categorical error scores, etc.) as well as the new error score SAL, which separately considers aspects of the structure, amplitude and location of the precipitation field in a predefined area. We also discussed the advantages and disadvantages of each of the scores. The aim of our evaluation was to unfold the strengths and weaknesses of AtmoMM5 and AtmoSat to calculate daily and monthly high resolution precipitation. As a result we found that the catchment averaged monthly mean precipitation is simulated with an acceptable accuracy by both methods. The spatial pattern of the monthly precipitation (typically with a precipitation maximum in the alpine foreland) can only be reproduced by AtmoMM5. Regarding the daily precipitation, our evaluation revealed that both methods still need improvement. The deviations to the observations increase with decreasing precipitation amount resulting in large uncertainties in case of very dry conditions. Overall, we can conclude that AtmoMM5 is better suited to simulate precipitation at 5 km resolution on a daily basis than AtmoSat.

A pragmatic approach for downscaling precipitation in alpine-scale complex terrain

A statistical method is presented to downscale precipitation from a mesoscale atmospheric model simulation. The algorithm consists of two steps. First, local subscale variability is estimated based on a high resolution observed climatology. Second, there is a bias correction, which constrains the downscaled model climatology to be equal to the observed climatology on the coarse grid. Combining both steps results in a local scaling factor for each day of the climatological year. The method is applied to the upper Danube catchment which encompasses part of the European Alps and which is characterized by highly complex orography. The subgrid-scale variability described by the first part of the algorithm partly reflects the underlying orography, especially the narrow alpine valleys. The bias correction leads to a redistribution of precipitation on the catchment scale and accounts for the model deficiency producing too much precipitation in the inner alpine regions and too little at the edges of the Alps. An evaluation with regard to the simulated and observed daily precipitation indicating the significant potential of the method is presented.

Precipitation and Temperature

Climatological studies indicate that climate change lead to an increase in the mean global temperature of around 0.5 °C until the end of the twentieth century. This warming impacts the atmospheric humidity, wind, radiation, and precipitation. However, the magnitude of changes is not equally distributed over the globe but differs markedly with regions, making a regionalization of the global information essential. The GLOWA-Danube project follows such a downscaling approach with the focus on the drainage basin of the Upper Danube River.