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Spatial decorrelation of the rain field in
region Southwest. Please take a look at the CRS1 (NE) examples and the
comparison between CRS2 (NW) and
CRS4 (SW)
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CRSM-series are subregional mean series (CRSM = Coarse Resolution
Subregional Means). They are arithmetic means of single station anomaly
series for the five principal subregions in the Greater Alpine Region.
The CRSs have been detected via EOF-based regionalisation for each of
the 5 leading climate parameters present in HISTALP (Auer et al, 2007 , chapt. 5). Single parameter regionalisation produced highly similar CRSs. Thus the decision was drawn to average them to one optimal version for all climate parameters (statmap-2 ).
Internal spatial decorrelation of the climatic fields within the CRSs compared to the diameters of the CRSs is such (Auer et al, 2007 ) that CRSM-series are the optimal choice for lower frequency analysis for all climate parameters. For higher frequency analysis (single months, seasons years, outliers, extreme events) higher resolution grids (grid-mode-1 or grid-mode-2 or station-mode are recommended. For the weakly decorrelating parameters air pressure and temperature CRSM-series may be the best choice also for such purposes. In CRSM-series eventually not yet detected inhomogeneities and outliers in single series are damped.
Monthly, seasonal and annual mean series of the leading climate parameters may be viewed in the CRSM-time series gallery .
Somebody might be interested in coordinates of the center for each subregion, we have calculated them for each element under use of the station coordinates (longitude, latitude an height). The central point of each CRS is the result of an weighted average above all element dependend centers.
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