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)

Upgraded website at: www.knmi.nl/samenw/eca

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

the end...