VASClimO 50-year Precipitation ClimatologyEntry ID: DWD-GPCC_VASClimO
Abstract: [Text Extracted from the GPCC home page, http://gpcc.dwd.de/ ]
This climate visualization is organized into three sections. "Gridded Monthly Data", "Basic descriptive statistics for the period 1951-2000", and "Trend estimates for the period 1951-2000". Please see the ... paragraphs below for details.
+ Gridded Monthly Data: Maps showing monthly and annual gridded precipitation sums are provided for three different spatial resolutions (0.5??lat/lon, 1.0??lat/lon, 2.5??lat/lon). Additional maps of Jackknife-error estimates (based on the 0.5??lat/lon resolution) and visualizations of the spatial station distributions are as well available for each month during the period 1951 to 2000.
+ Basic descriptive statistics for the period 1951-2000:
Basic temporal statistics are calculated for each over-land-grid point at .5?? resolution. This is done for each calendar month as well as the annual averaged monthly precipitation.Maps of the 50 year average monthly precipitation, the standard deviation as well as the coefficient of variation are provided here. The latter is defined as the ratio of standard deviation to average. It is a measure of relative variability. A high coefficient of variation means that the standard deviation is high compared to average. This means that precipitation in single years may differ considerably from the long term average.
+ Trend estimates for the period 1951-2000:
Are there changes in regional and seasonal precipitation within the 50-year period? One simple approach to investigate this question is the calculation of linear trends. Maps of estimated linear trends (provided in mm/Month/50yrs) for each grid point and calendar month are provided here. However, in order to assess the magnitude of a trend the relative trend is of interest. Here we provide the relative trend as the absolute trend divided by the first-year value of the linear trend line. Thus a positive relative trend of 10% means that the trend-line value of the last year is 10% higher than that of the first year. We provide the relative trends in %/decade with respect to the starting year 1951. Another indicator of the importance of a trend is the trend-noise ratio which compares the trend magnitude with the standard deviation of the record. Thus, the higher the trend-noise ratio the more important becomes the trend compared to the year-to-year variability.Finally, there is the question on the trend significance, i.e. even a series of stationary but random numbers reveals a linear trend, though it usually is a small one. The question arises, if the estimated trend is likely not to be by chance. A very general statistic in order to test the likelyhood of a temporal change of the expectation within a time series is the Mann-Kendall test. Note that it is not restricted to linear trends only. It generally estimates the probability that the observed temporal change occurs even if there is no change in the variable itself. We provide maps of the probability (given in %) that a randomly generated temporal change is smaller than the observed one. Therefore, high values of this probability mean good chance of the trend to be realistic.
Data Set Citation
Dataset Originator/Creator: Global Precipitation Climatology Centre (GPCC), Johann Wolfgang Goethe-University Frankfurt, Institute for Atmosphere and Environment - Working Group for Climatology
Dataset Publisher: Global Precipitation Climatology Centre
Version: 1.1Online Resource: http://gpcc.dwd.de/
Start Date: 1951-01-01Stop Date: 2000-12-31
Latitude Resolution: 0.5 degree
Longitude Resolution: 0.5 degree
Horizontal Resolution Range: 250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees
Temporal Resolution: 50 years
Temporal Resolution Range: Monthly Climatology
ISO Topic Category
Quality Please view the VASClimO home page for quality information.
Use Constraints Please cite the data set creator if you use this data.
Data Set Progress
Distribution Media: Online (HTTP)
Distribution Format: jpeg
Fees: No Cost
Role: TECHNICAL CONTACT
Phone: + 49 - 69 - 8062 2872
Fax: + 49 - 69 - 8062 3987
Email: gpcc at dwd.de
Global Precipitation Climatology Centre GPCC c/o Deutscher Wetterdienst Postfach 10 04 65
Postal Code: D-63004
Role: CLIMATE DIAGNOSTIC RECORD AUTHOR
Email: Scott.A.Ritz at nasa.gov
NASA Goddard Space Flight Center Global Change Master Directory
Province or State: Maryland
Postal Code: 20771
U. Schneider, T. Fuchs, A. Meyer-Christoffer and B. Rudolf (2008): Global Precipitation Analysis Products of the GPCC. Global Precipitation Climatology Centre (GPCC), DWD, Internet Publikation, 1-12. Updated version of Rudolf, B. (2005): Global Precipitation Analysis Products of the GPCC. DWD, Klimastatusbericht 2004, 163-170. ISSN 1437-7691, ISSN 1616-5063, ISBN 3-88148-402-7.
Rudolf, B. & F. Rubel (2005): Global Precipitation. In: Hantel, M. (Ed.) Observed Global Climate. New Series on Landolt-B??rnstein, Numerical Data and Functional Relationships, Springer, Berlin, 11.1 - 11.53, extended online version (11.1 - 11.24, print version). ISBN 3-540-20206-4.
Rudolf, B., U. Schneider (2005): Calculation of Gridded Precipitation Data for the Global Land-Surface using in-situ Gauge Observations, Proceedings of the 2nd Workshop of the International Precipitation Working Group IPWG, Monterey October 2004, EUMETSAT, ISBN 92-9110-070-6, ISSN 1727-432X, 231-247.
Beck, C. , J. Grieser and B. Rudolf (2005): A New Monthly Precipitation Climatology for the Global Land Areas for the Period 1951 to 2000. DWD, Klimastatusbericht KSB 2004, ISSN 1437-7691, ISSN 1616-5063 (Internet), ISBN 3-88148-402-7, 181-190.
Rudolf, B., H. Hauschild, W. Rueth and U. Schneider (1994): Terrestrial Precipitation Analysis: Operational Method and Required Density of Point Measurements. In: Global Precipitations and Climate Change (Ed. M. Desbois, F. Desalmond), NATO ASI Series I, Volume 26, Springer-Verlag, page 173-186. (
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Creation and Review Dates
DIF Creation Date: 2008-07-15
Last DIF Revision Date: 2009-06-05