To obtain a high-resolution wind field and to model snow drift over complex topography, the Swiss Federal Institute for Snow and Avalanche Research (SLF) uses the atmospheric model ARPS (Advanced Regional Prediction System, University of Oklahoma). ARPS accesses horizontally homogeneous initial fields. Until recently, this model was driven by atmospheric soundings recorded at sites far away from the actual model domain. In order to optimise the initial conditions of ARPS and to provide the option of producing real forecasts, a new downscaling method has been developed, which can also be applied to other uses. Based on the vertical structure of the atmosphere produced by the operational mesoscale forecast model aLMo (Alpine Model, MeteoSwiss), an artificial sounding is created for a specified location within the ARPS grid. Some of the techniques applied include model bias adjustment (based on aLMo verification studies), the introduction of horizontal filters, the assimilation of surface observation data and the vertical displacement of the boundary layer, motivated by the distinct topographies of the ARPS and the aLMo model. The combination of the methods differs from parameter to parameter. This paper describes details of the downscaling technique and gives an example of the application of the method.
MetGIS is an innovative Java-based, combined Meteorological and Geographic Information System, with a specific emphasis on snow and mountain weather. This constantly upgraded prediction scheme has been developed within the framework of a number of interdisciplinary international research projects. A principal focus of the system is the automated production of high-resolution, downscaled forecast maps of meteorological parameters such as precipitation, fresh snow amounts, the snow limit, the form of precipitation, wind and air temperature.The geographic part of the system includes topographies relying on data bases such as SRTM (Shuttle Radar Topographic Mission) and representations of roads, rivers, railway lines, political borders and cities. On top of these, partly linked to terrain features, down-scaled meteorological information can be visualized in a variety of display styles. Meteorological forecast data of any numerical model with common output data formats can be used as a starting point for the downscaling procedures. Currently, the real-time output of the GFS (Global Forecast System of the US National Weather Service) is used as a base for MetGIS forecasts. Verification results are quite encouraging so far. Mean absolute errors are in the range of 1.3-3°C for 36 h temperature forecasts, and around 80% of the 24 h forecasts predicted correctly, if the precipitation will be below or above 1 mm.
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