Geen diatitel

1
Climatological Extremes
13 November 2002 Albert Klein Tank KNMI, the
Netherlands acknowledgements37
ECA-participants (Europe Mediterranean)
2
Guide

• Definition of extremes and the use of indices
• Trends (1946-1999) for Europe and the world
• ECAD project and website (demo)

3
Guide

• Definition of extremes and the use of indices
• Trends (1946-1999) for Europe and the world
• ECAD project and website (demo)

4
(No Transcript)
5
(No Transcript)
6
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 lt 1 year as indicators of extremes

7
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 lt 1 year as indicators of extremes

8
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 lt 1 year as indicators of extremes

YES
9
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

10
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

11
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

12
Example of thresholds in the definition of
indices of temperature extremes
upper 10-ptile 1961-1990 the year 1996 lower
10-ptile 1961-1990
13
Example of thresholds in the definition of
indices of temperature extremes
upper 10-ptile 1961-1990 the year 1996 lower
10-ptile 1961-1990
14
Example of thresholds in the definition of
indices of temperature extremes
upper 10-ptile 1961-1990 the year 1996 lower
10-ptile 1961-1990
15
Example of thresholds in the definition of
indices of temperature extremes
upper 10-ptile 1961-1990 the year 1996 lower
10-ptile 1961-1990
16
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
  length50 years, the optimal return period is
  10-30 days rather than 10-30 years

17
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
  length50 years, the optimal return period is
  10-30 days rather than 10-30 years

18
Example 80 detection probability
(5 significance level)
(see also Frei Schär, J.Climate, 2001)
19
(No Transcript)
20
Guide

• Definition of extremes and the use of indices
• Trends (1946-1999) for Europe and the world
• ECAD project and website (demo)

21
Trend examples

• Extreme indices for temperature related impacts /
  applications
• Warm and cold extreme indices describing how
  temperature distributions (pdfs) shift in time
• Extreme indices of heavy precipitation

22
Trend examples

• Extreme indices for temperature related impacts /
  applications
• Warm and cold extreme indices describing how
  temperature distributions (pdfs) shift in time
• Extreme indices of heavy precipitation

23
Trend examples

• Extreme indices for temperature related impacts /
  applications
• Warm and cold extreme indices describing how
  temperature distributions (pdfs) shift in time
• Extreme indices of heavy precipitation

24
Heating degree days Growing season (sum
of 17C - TG) length (6 days, TG 5C)
25
(No Transcript)
26
Frich et al. (Clim.Res., 2002) in IPCC-TAR
27
(No Transcript)
28
IPCC-TAR (Ch.2, Folland and Karl)
29
(No Transcript)
30
(No Transcript)
31
(No Transcript)
32
(No Transcript)
33
Easterling et al. (BAMS, 2000) in IPCC-TAR see
also Groisman et al. (Clim.Change, 1999)
Linear trends in rainy season over last 50 years
34
Heavy precipitation R95tot-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
35
Heavy precipitation R95tot-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
36
Heavy precipitation R95tot-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
37
(No Transcript)
38
Frich et al. (Clim.Res., 2002) in IPCC-TAR
39
(No Transcript)
40
Guide

• Definition of extremes and the use of indices
• Trends (1946-1999) for Europe and the world
• ECAD project and website (demo)

41
Upgraded website at www.knmi.nl/samenw/eca
42
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 ECAD-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

43
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 ECAD 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

44

• the end...