advanced metrics of extreme precipitation events
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Workshop on extreme climate events, September 2010 Paris. Advanced metrics of extreme precipitation events. Olga Zolina. Meteorologisches Institut der Universität Bonn, Germany P.P.Shirshov Institute of Oceanology, Moscow, Russia. Outline:. Complexity of extreme precipitation, definitions - PowerPoint PPT PresentationTRANSCRIPT
Advanced metrics of extreme precipitation eventsOlga Zolina
Meteorologisches Institut der Universität Bonn, GermanyP.P.Shirshov Institute of Oceanology, Moscow, Russia
Complexity of extreme precipitation, definitions and uncertainties of metrics
Absolute extremes: use of raw data vs application of extreme value statistics
Relative extremeness: empirical and PDF-based indices
Problem of precipitation timing: duration of wet periods
Perspectives
MeteorologischesInstitut
Universit tBonn
ä
Outline:
Workshop on extreme climate events, September 2010 Paris
Complexity of precipitation process implies the complexity in estimation of precipitation extremes
Many more (compared to the other variables) metrics are needed to characterize it
Methods for estimation of extremes need to account for clustering in space and in time
Timing of the event is essential and should be accounted for both methods and data
Precipitation is an event-like phenomenon, clustered in space and in time, it is not aclassical scalar, like temperature or pressure 20 km
20 km
Datarequirement
s
Methodrequirement
sWorkshop on extreme climate events, September 2010 Paris
for treshhold=10 mm/day
in Stenslese - 3 days
in Bulken - 11 days
95%=12 mm/day2 days
95%=22 mm/day3 days
How to define what is extreme precipitation: uncertanties of metrics
Stensele, Sweeden
Bulken,Norway
JJA, 1982
0 10 20 30 40 50 60 70 80 90da y s
0
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mm
/da
y
0
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409 daystotal=35.3mmintensity=3.9mm/day
4 daystotal=22.0mmintensity=5.5mm/day
95% for 1950-2007 period =21.4 mm/dayBulken: 3 days, R95pTOT=33.021%Stensele: 0 days, R95pTOT=0%
Workshop on extreme climate events, September 2010 Paris
Approaches for estimating precipitation extremes
Absolute extremes
Extremeness (relative extremes)
Time- (area-)integrated extremes
Raw data – based
• Intensities• Maxima• Peaks over threshold
Contribution of the wettest days to totals
from empirical distributions
ETCCDI RxTOT index
Wet spell durations and associated
intensities & extremes
PDF –based
Percentiles of the theoretical
PDFs
IVD vs EVD
Contribution of the wettest days to totals
derived from theoretical PDFs
Intensity-duration-frequency (IDF)
distributionsFrom engineering
hydrology to climate
Workshop on extreme climate events, September 2010 Paris
Absolute extremes: IVD vs EVD
PDF for the core (IVD, e.g. Gamma) may not capture the extremes accurately EVD (e.g. GEV, GPD) may be strongly constrained by the threshold chosen and overestimate extremes “fetishism of heavy tails”
Is the concept “absence of evidence is not evidence of absence” always valid?
Gamma
GPD
Maraun et al. 2010
Cambridge
Daily precipitation is a time-integrated value, not an elementary event, difficulties in applying extreme statistics
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1 to 60 60 to 70 70 to 80 80 to 90 90 to 100 100 to 150 150 to 200 200 to 300 300 to 400 400 to 20000mm/day
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Overall record for Europe is 543 mm/day (Gard, France, 08.09.2002)
Workshop on extreme climate events, September 2010 Paris
1898-2009 maxima of daily precipitation
100-yr returns from GEV distribution
Zolina 2010
Absolute precipitation extremes:observed changes in 95% percentile of
precipitation
-10--6 -6--4 -4--2 -2-0 0-2 2-4 4-6 6-10 %
significant at 95% level
1951-2000 JJA
1951-2000 DJF
Zolina et al. 2005, Geophys. Res. Lett.
Zagreb
95th percentile
mean intensity
Changes in extremes differ from those in totals Absolute extremes grow with seasonality in Western Europe
Workshop on extreme climate events, September 2010 Paris
Seasonality in extreme precipitation trendsover Germany 1950-2004
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intensity
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D J F
6 8 1 0 1 2 1 4
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J J A
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Precipitation classes (%)
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Li n
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%)
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Precipitation classes (%)
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Li n
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significant at 95% level
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6 8 10 12 14
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6 8 10 12 14
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6 8 10 12 14
6 8 10 12 14
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DJF MAM
JJA SON
(c)
%DJF JJA
95% significance level
DJF
Zolina et al. 2008, J. Geophys. Res.
JJA YEAR
Workshop on extreme climate events, September 2010 Paris
Approaches for estimating precipitation extremes
Absolute extremes
Extremeness (relative extremes)
Time- (area-)integrated extremes
Raw data – based
• Intensities• Maxima• Peaks over threshold
Contribution of the wettest days to totals
from empirical distributions
ETCCDI RxTOT index
Wet spell durations and associated
intensities & extremes
PDF –based
Percentiles of the theoretical
PDFs
IVD vs EVD
Contribution of the wettest days to totals
derived from theoretical PDFs
Intensity-duration-frequency (IDF)
distributionsFrom engineering
hydrology to climate
Workshop on extreme climate events, September 2010 Paris
Absolute extremes and relative extremeness
Analyzing interannual changes, it is critical to know how much the fraction contributed by the uppermost wet days has changed
Limitations of the empirical indices are associated with the finite number of wet days in sample (R95totfalls to zero) Need to extent index of relative extremeness to the theoretical distributions
Zolina et al. 2009, J. Hydrometeorol.
1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000y e a rs
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%0
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R95pTOT Sodankyla, Finland, (26.65E, 67.37N) DJF
Workshop on extreme climate events, September 2010 Paris
Distribution of fractional contribution (DFC) of daily precipitation to the total
yxxPyPn
iii )()(
1
xi, i=1, ...n is the daily precipitation, n is the number of wet days
n
iiii xxy
1
1)1(1 )1()(])1[(
)()(
nyy
n
nyF
DFC for Gamma distribution
),1,,1(
)1()(])1[(
)()(
12
)1(
ynF
yyn
nyC n
),,,(12 ycbaF - Gaussian hypergeometric function
PDF:
CDF:
Zolina et al. 2009, J. Hydrometeorol.
R95tt index instead of R95tot
Workshop on extreme climate events, September 2010 Paris
0.
4 to
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(a)
(b)
(c)
YEAR
DJF
JJA
Corellation R95tt vs R95tot
Relative precipitation extremeness:PDF-based vs empirical index
New index exhibits significant differences compared to the traditional index and may also show different variability patterns
R95tt DJF
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(a) (b)
(c) (d)
R95tt DJF
R95tt JJA
R95ttMAM
R95ttSON
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R95tt-R95tot DJF
R95tt-R95tot JJA
R95tot DJF1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
years
0
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%
0
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50Sodankyla, Finland (26.65°E, 67.37°N)
DJFR95totR95tt
Sondakyla, Finland26.65E, 67.37N, DJF
Linear trend, % per dec
Linear trend, % per dec
Workshop on extreme climate events, September 2010 Paris
Approaches for estimating precipitation extremes
Absolute extremes
Extremeness (relative extremes)
Time- (area-)integrated extremes
Raw data – based
• Intensities• Maxima• Peaks over threshold
Contribution of the wettest days to totals
from empirical distributions
ETCCDI RxTOT index
Wet spell durations and associated
intensities & extremes
PDF –based
Percentiles of the theoretical
PDFs
IVD vs EVD
Contribution of the wettest days to totals
derived from theoretical PDFs
Intensity-duration-frequency (IDF)
distributionsFrom engineering
hydrology to climate
Workshop on extreme climate events, September 2010 Paris
0 5 10 15 20 25 30
days
0
5
10
15
20
25
30
mm
/da
y
0
5
10
15
20
25
30
Duration of precipitation: essential metric for estimation extremes
For design purposes a critical metric is the precipitation accumulated during consecutive days or over area Time-integrated extremes may not correlate with the magnitude of extremes for single days
IDF (Intensity-duration-frequency)-distributions: developed in engineering hydrology, however for minute- and hourly time scales only, not yet applied to climate studies
Madsen, 2002, Wat. Res. Res.
IDFs for Vietnam
IDFs for CopenhagenWP=3 daysMax = 27.1mmTotal = 32.8mm
WP=12 daysMax = 6.2mmTotal = 51.5mm
Workshop on extreme climate events, September 2010 Paris
0 5 10 15 20 25 30 35 40 45 50fraction of wet days due to wet spells (%)
0 5 10 15 20 25 30 35 40 45 50ocurrence of wet spells (%)
1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005years
-2.0-1.8-1.6-1.4-1.2-1.0-0.8-0.6-0.4-0.10.00.10.40.60.81.01.21.41.61.82.0-0.2-0.6-1.0-1.8-2.0 0.2 0.6 1.0 1.4 2.0-1.4 1.8
12
123456789
1011
dura
tion
of w
et s
pells
(day
s) 12
123456789
1011
a
-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5
-0.5 -0.4 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5linear trend in the fracion of wet days
b c
Changes in the duration of European wet periods
normalized occurrence anomalies
Zolina et al. 2010, Geophys. Res. Lett.
Net effect of the number of wet days(Monte-Carlo simulation of the growing
number of wet days, % per decade)
1% 2% 3%
0.17±0.10 0.31±0.19 0.47±0.25
It is not the effect of changingnumber of wet days!!!
Linear trend in the WP duration: 1950-2008
Workshop on extreme climate events, September 2010 Paris
How changing wet spells affect precipitation
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00 t
o -
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-3 t
o -
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o 0
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to 1
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to 2
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to 3
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to 1
00< - 3
- 3 - - 2- 2 - - 1
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1 - 22 - 3 > 3
- 1 0 0 1 0 2 0 3 0 4 0 5 0 6 0
- 1 0 0 1 0 2 0 3 0 4 0 5 0 6 0
3 0
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7 0
- 1 0 0 1 0 2 0 3 0 4 0 5 0 6 0
- 1 0 0 1 0 2 0 3 0 4 0 5 0 6 03 0
4 0
5 0
6 0
7 0
Linear trends in fractional contrbution of extremes to the total
Short WPs (<2 days) Long WPs (>2 days)
Workshop on extreme climate events, September 2010 Paris
Changes in the IDF distrbutions for daily preciptiation in Europe (1950-2009)
0 4 8 1 2 1 6 2 0 2 4 2 8m e a n i n t e n s i t y ( m m / d a y )
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0 4 8 1 2 1 6 2 0 2 4 2 8m e a n i n t e n s i t y ( m m / d a y )
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1 0
dura
tion
of w
et s
pells
(day
s)
5
6 0
4 0
1 0
1 5 0
8 0
1 2 0
1 0 0
2 03 0
a
significant at 95% level
Intensity-durationdistribution for
Central Germany
Acc. precipitation
Linear trends in time-integrated precipitationfor all European stations (% per decade)
All wet periods Extremes (95th percentile)
Longer wet periods imply stronger extremes!Workshop on extreme climate events, September 2010 Paris
Conclusions and perspectives
Absolute extremes:
Existing methods are quite accurate, however more close look is needed on the approaches to estimation of very rare events Absolute extremes show primarily growing intensity over Europe (up to 5% per
decade) but for most regions spatial patterns are noisy and significance is low There is a clear seasonality in long-term trends of Central European
precipitation extremes: more extremes in winter and less in summer Relative extremeness:
New R95tt index allows to overcome the problem of the finite number of wet days in the raw time series of daily precipitation Compared to R95tot index, new R95tt index shows more homogeneous trend
pattern with the trends being statistically significantly larger in the Central and Eastern Europe Duration of wet spells:
During the last 60 years European wet spells have become longer by about 15-20%. Lengthening was not caused by the net effect of wet days Extreme precipitation associated with longer wet spells have intensified
by 12-18%, while extremes associated with short wet spells became weaker
Workshop on extreme climate events, September 2010 Paris
Thank you
Soja & Starkel, 2007, Geomorph.
4-month (1998) daily precipitation In Cherrapunji
Extreme precipitation season (summer 1998) andcatastrophic flood and land slide in Ladakh,
Himalay
Workshop on extreme climate events, September 2010 Paris