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) |
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 subregions 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 subregions. Thus the decision was drawn to average them to one optimal version for all climate parameters (HISTALP map ).
Internal spatial decorrelation of the climatic fields within the subregions compared to the diameters of the subregions 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 (1x1 degree or 5x5 minutes) 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 PDF files below .
Element | relative 1961-1990 | relative 1900-2000 | Size |
mean sunshine duration | SU1-rel1961-1990_CRSM.zip | SU1-rel1901-2000_CRSM.zip | 24k |
mean precipitation sums | R01-rel1961-1990_CRSM.zip | R01-rel1901-2000_CRSM.zip | 33k |
mean cloudiness | N01-rel1961-1990_CRSM.zip | N01-rel1901-2000_CRSM.zip | 27k |
mean temperature |
T01-rel1961-1990_CRSM.zip | T01-rel1901-2000_CRSM.zip | 40k |
md5sum controlfile | CRSM.md5 |
For those interested in coordinates of the center for each subregion, we have calculated them for each element using the station coordinates (longitude, latitude and height). The central point of each subregion results from the weighted average of the subregion centers of the different elements.
Content | Download | Size |
Coordinates of the centerpoint of each subregion as CSV and Microsoft Excel files | CRSM-coordinates.csv | 1k |
CRSM-coordinates.xls | 14k |
Each of the PDF files here shows all 19 timeseries (Jan-Dez, the 4 seasons, 2 half years and the year) of the CRSM dataset, so you can use it for a preview of our data. They have been saved in high resolution to conserve all details - expect a rather large download (500-700kB).
In the unlikely case you don't have a viewer for pdf you can download one at www.adobe.com
Element | NE | SE | SW | NW | HIGH | LOW |
mean sunshine duration | SU1_NE.pdf | SU1_SE.pdf | SU1_SW.pdf | SU1_NW.pdf | SU1_SUMMITS.pdf | SU1_LOW.pdf |
mean precipitation sums | R01_NE.pdf | R01_SE.pdf | R01_SW.pdf | R01_NW.pdf | not available | R01_LOW.pdf |
mean temperature | T01_NE.pdf | T01_SE.pdf | T01_SW.pdf | T01_NW.pdf | T01_SUMMITS.pdf |
T01_LOW.pdf |