Comparison of Meso-Scale Modelled Fluxes and Measurements
The Weather Research and Forecasting model was evaluated over a forested and a grassland ecosystem. The model run was initialized with three nested domains and the second Intensive Observation Period (IOP2) of the EGER-Project (ExchanGE processes in mountainous Regions) in June/July 2008 was simulated.
To evaluate the model, mean bias error, root mean square error, mean average error, index of agreement and coefficient of efficiency were calculated for the whole period of the IOP2 as well as for each single day. These difference measures were calculated with the “nearest” grid point and with an “interpolated” grid point. Pressure and wind direction were evaluated with their absolute values.
It was proved that the least domain provided better results for five of six meteorological parameters: temperature, wind speed, wind direction, global radiation, sensible and latent heat flux. This shows that a resolution of 1 km in space and half an hour in time makes sense. Furthermore, differences in model results and measured values caused by micrometeorological phenomena (e.g. cold-air flowing off mountains or mountain-valley—wind-systems) could be shown. These micrometeorological phenomena could not be simulated because the resolution of the terrestrial input is too low. The more accurate terrestrial input can lead to better forecast results. Furthermore, large-scale weather patterns have an influence on the forecast. A comparison of the statistical parameters calculated with “interpolated” or “nearest” methods showed that there is no significant difference between them.
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