Extreme Events in the Mediterranean Climate
Piero Lionello,
[email protected]
Science of Materials Department,
University of Salento, Italy
From present trends to future climate change::
•Cyclones
•heat waves,
•extreme precipitation,
•droughts,
•marine storminess
CUMULATED DISTRIBUTION
CO2
ERA
CTR
“CYCLONES in the
Mediterranean region
in the present and
doubled CO2 climate
scenario” (Lionello et
al. 2002)
according to ECHAM
(T106) 30-year long
time slice experiment
(2XCO2) carried out at
DMI
CO2
CTR
ERA
Heat Waves
A heat wave is a period with continuously extremely high
temperatures (and humidity). Its operative definition needs an air
temperature threshold and a minimum duration
Extreme summer temperatures in Iberia: health impacts and
associated synoptic conditions García-Herrera, R., Díaz, J.,
Trigo, R. M., and Hernández, E.:, Ann. Geophys., 23, 239-251,
2005.
HW is defined as the number of consecutive 3-day
periods in summer (JJA) that exceed the long-term
daily 80th percentile of daily maximum temperature.
Della-Marta PM et al (2007) Summer heat waves over western Europe 18802003, their relationship to large-scale forcings and predictability. Climate
Dynamics 29, 251-275
A hot day (HD) is defined as a day where the daily maximum
temperature exceeds the long-term daily 95th percentile of daily
maximum temperature.
The hot day index is the number of such days within a June-August
season expressed as a percentage of time.
A heat wave (HW) is defined as the maximum number of consecutive
days where the Daily Summer Maximum Temperature exceeds the
long-term daily 95th percentile of DSMT within a June-August season.
Over the period 1880 to 2005 the length of summer HW over western
Europe has doubled and the frequency of HD has almost tripled.
The Daily Summer Maximum Temperature Probability Density
Function (PDF) shows significant changes in the mean (+1.6 ± 0.4°C)
and variance (+6 ± 2%).
Doubled length of western European summer heat waves since 1880
P. M. Della-Marta, M. R. Haylock, J. Luterbacher, H. Wanner
2007, J. Geophys. Res., 112, D15103, doi:10.1029/2007JD008510.
Della-Marta P.M. et al (2007) Doubled length of western European summer
heat waves since 1880
Change of
variability
Change of mean
probability
The Daily Summer Maximum
Temperature Probability
Density Function (PDF)
shows significant changes in
the mean (+1.6 ± 0.4°C) and
variance (+6 ± 2%).
probability
anomaly
Change of
mean and
variability
anomaly
probability
Title1
anomaly
Heat waves in Italy (1951-2000)
Distribuzione decennale di HW (1951-2000)
200
180
160
140
120
100
80
60
40
20
0
num giorni
giorni (%)
1951-60
1961-70
1971-80
1981-90
1991-00
Heat wave distribution (number of days and
percentage) for each decade in the period
1951-2003 (Thanks to M.Baldi)
From the MICE project
Extremes in temperature and precipitation around the
Mediterranean basin in an ensemble of future climate scenario
simulations
Goubanova, K.; Li, L.
Global and Planetary Change, 2007, Volume 57, p. 27-42.
“In general terms, it is suggested that the Mediterranean basin
will experience a warmer climate with less total precipitation but
more intense precipitation events.”
Future changes of the annual
maximum temperature
simulated by LMDZ with A2
emission scenario with the
three global climate scenarios
(IPSL, CNRM and GFDL
respectively from top to
bottom) relative to
1970/1999: 30-yr return
values in 2030/2059, 30-yr
return values in 2070/2099,
Goubanova and Li, 2007. Extremes in temperature and precipitation around the
Mediterranean basin in an ensemble of future climate scenario simulations
PRUDENCE extremes paper:
Beniston et al. ‘Future extreme events in
European climate: an exploration of regional
climate model projections’ Climatic Change
(2007) 81:71–95
Regional surface warming causes the frequency, intensity and duration
of heat waves to increase over Europe. By the end of the twenty first
century, countries in central Europe will experience the same number
of hot days as are currently experienced in southern Europe. The
intensity of extreme temperatures increases more rapidly than the
intensity of more moderate temperatures over the continental interior
due to increases in temperature variability.
• Heat Wave Number – Number of heat waves that occur in a
given time interval (e.g., per decade) where a HW is defined a
period of at least 6 consecutive days with Tmax larger than the
90th percentile
•Heat Wave Frequency – Total duration (days) of all the heat
waves that occur in a given time interval
• Heat Wave Duration – Longest duration of a heat wave
(days), of all the heat waves occurring in a given time interval
• Heat Wave Intensity – Greatest exceedance of a given
threshold of temperature, expressed in degree-days, for all the
heat waves occurring in a given time interval.
Number
Frequency
Max. Duration
Intensity
Changes (expressed as a ratio) in the heat wave indices N_HW (a),
HW_F (b), HW_D (c) and HW_I (d) between the 1961–1990 and
2071–2100 periods, based on HIRHAM4 simulations
Title1
Change of mean
probability
probability
Change of
variability
anomaly
Change of
mean and
variability
probability
anomaly
anomaly
EXTREME precipitation events and episodes
M. R. HAYLOCK and C. M. GOODESS: INTERANNUAL
VARIABILITY OF EUROPEAN EXTREME WINTER RAINFALL
AND LINKS WITH MEAN LARGE-SCALE CIRCULATION (2004)
Int. J. Climatol. 24: 759–776
Left: Linear trend in DJF CDD for 1958–2000. A ‘+’ signifies an increase and a ‘°’ shows
a decrease. The size of the symbol is linearly proportional to the magnitude of the trend.
Right: As for but for R90N
The CDD (Consecutive Dry Days) index is calculated by determining the maximum
number of consecutive days with rainfall less than 1 mm.
The R90N index is calculated by first determining the 90th percentile threshold of all
events greater than 1 mm for December–February (DJF) over the period 1961–90, then
for each winter counting the number of events above this threshold.
HAYLOCK M.R. and C. M. GOODESS, 2004
Goubanova and Li 2007
Christensen & Christensen, 2003 Intensification of extreme European
summer precipitation in a warmer climate, Nature ***
Change in mean JJA rainfall
from 1961-1990 to 20712100 (%)
Change in exceedence of 99th
percentile of JJA rainfall from
1961-90 to 2071-2100
“ …. although the summer time precipitation decreases over a
substantial part of Europe in the analysed scenarios, an increase in the
amount of precipitation exceeding the present-day 99th and in most
cases even the 95th percentile is found for large areas”
mm/day
Winter
Summer
mm/day
Future changes of 30-yr return values of extreme winter and summer
precipitation in 2070/2099 relative to 1970/1999 GFDL
Importance of statistical downscaling for prognosis of
climate extremes
A recent example
“Simulation of future changes in extreme rainfall and
temperature conditions over the Greek area: A
comparison of two statistical downscaling approaches
K.Tolika, C.Anagnostopoulou, P.Maheras, M. Vafiadis,
2008, Global and Planetary Change
“Concerning extreme temperatures, an increase of their
values is expected during the future period 2070–2100
[… ]The results for the extreme precipitation indices
showed a spatial incoherence and more complex
structure of change.”
Mediterranean droughts in future climate scenarios
Model-based scenarios of Mediterranean droughts
M. Weiß, M. Flörke, L. Menzel, and J. Alcamo
Adv. Geosci., 12, 145–151, 2007
This study examines the change in current 100year hydrological drought frequencies in the Mediterranean
in comparison to the 2070s as simulated by the global model
WaterGAP. The analysis considers socio-economic and climate
changes as indicated by the IPCC scenarios A2 and B2
and the global general circulation model ECHAM4. Under
these conditions today’s 100-year drought is estimated to occur
10 times more frequently in the future over a large part
of the Northern Mediterranean while in North Africa, today’s
100-year drought will occur less frequently. Water abstractions
are shown to play a minor role in comparison to the
impact of climate change, but can intensify the situation
Drought: a period of abnormally dry weather sufficiently prolonged so
that the lack of water causes a serious hydrologic imbalance (such as
crop damage, water supply shortage, etc.) in the affected area (McGraw
Hill, 2003)
Meteorological drought is defined as an interval of time during which the
actual moisture supply falls short of climatically specific moisture supply
at a given place.
Agricultural drought is defined as a period, in which soil moisture
content is inadequate to meet evapotranspirative demands to initiate
and sustain crop growth.
Hydrologic drought is associated with inadequate stream flow, reservoir
and lake levels or groundwater recharge.
Intensity of the drought:
Discharge deficit with respect to variable threshold following the
seasonality of the hydrograph, e.g. the long-term monthly means.
A deficit volume is calculated for each cell of a river basin as the
difference between the long-term
EXTREMES and large scale patterns
In part, past changes can be explained by changes in circulation &
other predictors
CCA patterns – heavy rain day trends and SLP anomalies
Thanks to Clare Goodess, based on “Heavy winter rainfall and
links with North Atlantic Oscillation/SLP
Haylock & Goodess, IJC, 2004
RL6: Extreme Events
Coord: Garcia Ricardo, Lionello Piero
RL6 Participants
- ICAT-UL R. Trigo (Un. of Lisbon, Portugal)
- UVIGO, UCM L. Gimeno (Un. of Vigo Spain)
- UNIBERN J.Luterbacher; (Un. of Bern Switzerland)
- UEA T.Holt (University of East Anglia, Climatic Research Unit,UK)
- DMI W. May (Danish Meteorological Institute, Denmark)
- IBIMET M. Baldi; (IBIMET-CNR, Italy)
- FUBERLIN U.Ulbrich (Un. of Berlin)
- NOCS M.Tsimplis (National Oceanographic Center, UK)
- UCM R. García-Herrera (Un. Complutense, Madrid, Spain)*
- UNISA P. Lionello (Un. of Salento, Lecce, Italy)
Many weather extremes are associated with hazardous
situations and they have significant impacts on many socioeconomic issues and activities in the Mediterranean area,
namely: health, agriculture, forest management, energy
production, offshore activities, coastal and port
management,
energy
use,
tourism,
civil
protection/insurance.
The objectives of the RL6 work packages are
1) to understand the current space-time distribution of extreme
events over the Mediterranean
2) to analyse sets of climate simulations with several models to
understand how the intensity/distribution of extremes could
change in the 21st century
3) to provide information for impacts analysis.
Within RL6, the following variables are considered:
precipitation, temperature, waves, sea level, cyclones and
winds , upper troposphere height, cut-off lows, droughts.
Analysis is based on the definition of extreme event
indicators, the identification of thresholds, the analysis of
links with large scale patterns. These outcomes will be used
for the analysis of extremes in future climate scenarios in the
second part of the project.
Precipitation
A wide class of hazards is associated to both excess and scarcity
of precipitation. Irregular and scarce precipitation is a problem
already present over large areas of the Mediterranean region.
Temperature
Extremely high and low temperature are associated to health
problems,. Effects are related to temperature levels, but also to the
duration of episodes and to level of preparedness of the population,
Moreover both warm and cold extremes produce high energy
demands, because of increase heating and air conditioning.
Winds
Wind storms are a major hazard to forests and building and
among the major source of damage worldwide.
Cyclones
Cyclones have large effects on the environment, being associated
with winds, precipitation and fronts.
Tropopause and COL (Cut Off Lows)
COL are important as meteorological system and for their effect on the
precipitation
Sea Level
Extremes sea level is due to the mechanical action (sea level
pressure and surface wind) of the atmosphere which produce a
transient increase, called storm surge.
Waves
High waves are caused by strong winds over sea and they are
mostly associated with cyclones. High waves are a hazard for
shipping, for offshore activities and structures, especially if their level
is not adequately evaluated in planning and small ship routing.
Droughts
Within RL6 it has been considered important to propose a qutity
explicitly addressing the evaluation of droughts and the Palmer
Drought Severity Index (PSDI) is proposed.
Example: indicators for marine storminess
Sea Level
slx95p
daily sea level max 95percentile
slx5gev
5-year surge: 5-year return value of max sea level during
surge events
Slx100gev
100-year surge : 100-year return value of max sea level
during surge events
Slx95n
number of events exceeding the 95 percentile of long term
daily sea level max
Sudi
surge duration indicator number of consecutive hours
exceeding the long term 95 daily max percentile
extreme SWH threshold
swhx95p
daily swh max 95percentile
dead calm SWH threshold
Swhm5p
daily swh min 5 percentile
5year SWH
swhx5gev
5-year swh: return value of max swh during single events
100year SWH
swhx100gev
100-year swh: return value of max swh during single events
swhx95n
number of events exceeding the long term 95 percentile of
daily sea level max swh
mstdi
marine storm duration indicator: number of consecutive hours
exceeding the long term 95 daily max SWH percentile
wldi
consecutive waveless day duration indicator: number of
consecutive days with SWH below the long term min 5
percentile
extreme surge threshold
5year surge
100 year surge
extreme surge frequency
extreme surge duration
SWH Significant Wave
Height
extreme SWH frequency
extreme storm duration
dead calm duration
The RL6 is organized in a sequential set of 3 WPs (from WP1 to WP3)
with the subsequent WP4 and WP5 being based on their results, and
WP6 reserved for coordination
-WP1: Mediterranean extreme characterization and indices
- WP2 (T13-24): Diagnosis of trends/variability in extremes during the
20th century.
Analysis of existing sets of data and their integration with new
observations/data for the identification of characteristic variability
and trends
-WP3 (T19-30): extremes: causes and links to large scale patterns.
Analysis of link between the occurrence of different types of
extremes and large scale patterns and identification of causes for the
variation of their intensity.
- WP4 (T25-48) : Extremes in future climate scenarios
- WP5 (T25-48) : Data for the estimation of future impacts of weather
and climate extremes