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European Climate Assessment

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Instead: labelling of series - confidence for trend and variability analysis ... labelling system good basis for series selection in trend analysis. And... – PowerPoint PPT presentation

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Title: European Climate Assessment


1

European Climate Assessment Dataset Judging
homogeneity of daily series
Fourth seminar for homogenization Budapest, 6-10
October 2003
Janet Wijngaard, KNMI, the Netherlands
2
Topics
  • ECAD project
  • Approach to homogeneity
  • Results, Conclusions

3
ECAD project
  • data analysis focusing on observed changes in
    extremes
  • gather daily series of observations at
    meteorological stations in
  • Europe and the Middle East
  • quality control and homogeneity analysis of the
    series
  • dissemination of data and analyses results

4
Current participation
  • Most data from 1900 up to 2001
  • More than 200 stations
  • Tmin, Tmax, Tmean,
  • precipitation amount, pressure

5
Trend analysis of extremes requires A dense,
high-resolution, accurate and consistent dataset
6
Method
Homogenization of daily series
Instead labelling of series -gt
confidence for trend and variability analysis
7
Two-step approach
  1. Four homogeneity tests applied to ECA dataset to
    identify potential inhomogeneities in annual
    resolution testing variables representative for
    the daily resolution
  1. Grouping of results -gt overall classification

8
Homogeneity tests and variables
  • Tests (absolute)
  • SNHT
  • Buishand Range
  • Pettitt
  • Von Neumann Ratio
  •  Variables
  • precipitation number of wet days
  • temperature mDTR and vDTR (annual mean of
    absolute day-to-day

  • differences of DTR)

9
vDTR
DTRi Diurnal temperature Range for day i in a
specific year M number of days in the year
10
Classification
  • Labels
  • Useful (0/1 tests significant)
  • Doubtful (2 tests significant)
  • Suspect (3/4 tests significant)

 
11
Station Groningen (NL)

 
1948 change of observation hut 1951 relocation
1959 change in sensor height
12
Station Groningen (NL)
Buishand Range, Pettitt and Von Neumann
significant -gt suspect
13
Temperature 1946-1999
mDTR
vDTR
-gt54 suspect, breaks (partly) supported by
metadata
14
Precipitation 1946-1999
Number of wet days
Paper International Journal of
Climatology, May, 2003
-gt 10 suspect
15
Conclusions
  •  
  • most severe step-wise breaks are detected
  • metadata support for detected breaks essential
  • no homogenizing of daily series
  • labelling system good basis for series selection
    in trend analysis

16
And
  •  
  • further investigations to test homogeneity on
    daily basis
  • MASH method used for homogenization on monthly
    ECAD series

17
More info at http//www.knmi.nl/samenw/eca
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