Climatological Extremes
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Climatological Extremes 13 November 2002 Albert Klein Tank KNMI, the Netherlands acknowledgements: 37 ECA-participants (Europe & Mediterranean)
description
Climatological Extremes. 13 November 2002 Albert Klein Tank KNMI, the Netherlands acknowledgements: 37 ECA-participants (Europe & Mediterranean). Guide. Definition of extremes and the use of indices Trends (1946-1999) for Europe and the world ECA&D project and website (demo). Guide. - PowerPoint PPT Presentation
Transcript of Climatological Extremes
Climatological Extremes13 November 2002
Albert Klein TankKNMI, the Netherlands
acknowledgements:37 ECA-participants (Europe & Mediterranean)
Guide
1. Definition of extremes and the use of indices2. Trends (1946-1999) for Europe and the world3. ECA&D project and website (demo)
Guide
1. Definition of extremes and the use of indices2. Trends (1946-1999) for Europe and the world3. ECA&D project and website (demo)
What type of extremes? Events characterised by the size of their societal or
economic impacts
Events characterised by parameters of extreme value distributions
Phenomena with a daily time scale and typical return period < 1 year as indicators of extremes
NO
What type of extremes? Events characterised by the size of their societal or
economic impacts
Events characterised by parameters of extreme value distributions
Phenomena with a daily time scale and typical return period < 1 year as indicators of extremes
NO
NO
What type of extremes? Events characterised by the size of their societal or
economic impacts
Events characterised by parameters of extreme value distributions
Phenomena with a daily time scale and typical return period < 1 year as indicators of extremes
NO
NO
YES
Approach Use daily series of observations at meteorological
stations throughout Europe and the Mediterranean
Define descriptive indices as proposed by the joint CCL/CLIVAR Working Group on Climate Change Detection (Peterson et al., WMO-TD No. 1071, 2001)
Count the days crossing a threshold; either absolute/fixed thresholds or percentile/variable thresholds relative to local climate
Approach Use daily series of observations at meteorological
stations throughout Europe and the Mediterranean
Define descriptive indices as proposed by the joint CCL/CLIVAR Working Group on Climate Change Detection (Peterson et al., WMO-TD No. 1071, 2001)
Count the days crossing a threshold; either absolute/fixed thresholds or percentile/variable thresholds relative to local climate
Approach Use daily series of observations at meteorological
stations throughout Europe and the Mediterranean
Define descriptive indices as proposed by the joint CCL/CLIVAR Working Group on Climate Change Detection (Peterson et al., WMO-TD No. 1071, 2001)
Count the days crossing a threshold; either absolute/fixed thresholds or percentile/variable thresholds relative to local climate
Example of thresholds in the definition of indices of temperature extremes
upper 10-ptile 1961-1990
the year 1996
lower 10-ptile1961-1990
Example of thresholds in the definition of indices of temperature extremes
upper 10-ptile 1961-1990
the year 1996
lower 10-ptile1961-1990
“frost days”
Example of thresholds in the definition of indices of temperature extremes
upper 10-ptile 1961-1990
the year 1996
lower 10-ptile1961-1990
“cold nights”
Example of thresholds in the definition of indices of temperature extremes
upper 10-ptile 1961-1990
the year 1996
lower 10-ptile1961-1990
“cold nights”
“warm nights”
Motivation The detection probability of trends depends on the
return period of the extreme event and the length of the series
For extremes in daily station series with typical length~50 years, the optimal return period is 10-30 days rather than 10-30 years
Motivation The detection probability of trends depends on the
return period of the extreme event and the length of the series
For extremes in daily station series with typical length~50 years, the optimal return period is 10-30 days rather than 10-30 years
Series length
605040302010
Req
uire
d re
lativ
e tr
end
(%/d
ecad
e)
120
100
80
60
40
20
0
Event return period
365 days
100 days
30 days
10 days
(see also:Frei & Schär, J.Climate,
2001)
Example: 80% detection probability (5% significance level)
Guide
1. Definition of extremes and the use of indices2. Trends (1946-1999) for Europe and the world3. ECA&D project and website (demo)
Trend examples Extreme indices for temperature related impacts /
applications
“Warm” and “cold” extreme indices describing how temperature distributions (pdf’s) shift in time
Extreme indices of heavy precipitation
Trend examples Extreme indices for temperature related impacts /
applications
“Warm” and “cold” extreme indices describing how temperature distributions (pdf’s) shift in time
Extreme indices of heavy precipitation
Trend examples Extreme indices for temperature related impacts /
applications
“Warm” and “cold” extreme indices describing how temperature distributions (pdf’s) shift in time
Extreme indices of heavy precipitation
Heating degree days Growing season(sum of 17°C - TG) length (6 days, TG 5°C)
Frich et al. (Clim.Res., 2002) in IPCC-TAR
IPCC-TAR (Ch.2, Folland and Karl)
Easterling et al. (BAMS, 2000) in IPCC-TARsee also Groisman et al. (Clim.Change, 1999)
Linear trends in rainy season over last ~50 years
Heavy precipitation: R95%tot-index (fraction due to very wet days)
1) Identify very wet days using a site specific threshold = 95th percentile of amounts at wet daysin the 1961-1990 period
2) Determine fraction of total precipitation in each year or season that is due to these days
3) Trend analysis in resulting series
Heavy precipitation: R95%tot-index (fraction due to very wet days)
1) Identify very wet days using a site specific threshold = 95th percentile of amounts at wet daysin the 1961-1990 period
2) Determine fraction of total precipitation in each year or season that is due to these days
3) Trend analysis in resulting series
Heavy precipitation: R95%tot-index (fraction due to very wet days)
1) Identify very wet days using a site specific threshold = 95th percentile of amounts at wet daysin the 1961-1990 period
2) Determine fraction of total precipitation in each year or season that is due to these days
3) Trend analysis in resulting series
Frich et al. (Clim.Res., 2002) in IPCC-TAR
Guide
1. Definition of extremes and the use of indices2. Trends (1946-1999) for Europe and the world3. ECA&D project and website (demo)
Conclusions and outlook The standardised descriptive indices (that are based on
daily series) reveal trends in climatological extremes for Europe that can directly be compared to the trends in other regions of the world; the indices are adequate for climate change detection as well as for impact assessment
Future plans ECA&D-project: 2006 assessment report, improved daily dataset (coverage / elements / homogeneity / metadata / gridding / web-access), additional participants, communication of results both towards climate change detection and modelling community and towards applied climatology community
Conclusions and outlook The standardised descriptive indices (that are based on
daily series) reveal trends in climatological extremes for Europe that can directly be compared to the trends in other regions of the world; the indices are adequate for climate change detection as well as for impact assessment
Future plans ECA&D project: 2006 assessment report, improved daily dataset (coverage / elements / homogeneity / metadata / gridding / web-access), additional participants, communication of results both towards climate change detection and modelling community and towards applied climatology community
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