Variability Analyses of Surface Climate Observations (VASClimO) Precipitation Climatology

The data can be found here.

The following citation should referenced:
Beck, C., J. Grieser and B. Rudolf (2005): A New Monthly Precipitation Climatology for the Global Land Areas for the Period 1951 to 2000. (published in Climate Status Report 2004, pp. 181 - 190, German Weather Service, Offenbach, Germany.) A preprint of this report can be downloaded here.

Variability Analysis of Surface Climate Observations is a joint climate research project of the German Weather Service (Global Precipitation Climatology Centre - GPCC) and the Johann Wolfgang Goethe-University Frankfurt (Institute for Atmosphere and Environment - Working Group for Climatology). The project is funded by the Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie BMBF within the German Climate Research Program DEKLIM(DEKLIM Project-No.: 33 11 0307 - "Development of an observational data basis (Europe and global) for DEKLIM and related statistical analysis with regard to climate variability on a decadal to centennial time scale").

The VASClimO Climatology is a globally gridded data set of observed station precipitation.

It is prepared by Dr. Christoph Beck and Dr. Jürgen Grieser at the Global Precipitation Climatology Centre (GPCC). The work is done in the frame of the project VASClimO which is part of the German Climate Research Programme (DEKLIM) and is supported financially by the Bundesministerium für Bildung und Forschung under DEKLIM project-No. 33 11 0307.

The globally gridded monthly precipitation sums from January 1951 to December 2000 are provided in three resolutions. Note that the Antarctica and Greenland are not included because of lack of data.

Though the merging of the different data sources, the quality control with respect to outliers and homogeneity (both, test and removal) as well as the interpolation and gridding is done as thoroughly as possible in order to obtain optimal results we can give no warranty in any way that these data truely reflect the spatiotemporal precipitation.

In order to get an idea of the quality of the results spatial patterns of Jackknife-error estimates are provided. This Jackknife error is the difference of the interpolated value of the location of the nearest station (taking only other stations into account) and the observation at that station. It therefore tells what would have been estimated if there were no observation and thus it is a rather conservative measure of error.

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