weather regimes and european heat waves. summer 2003: a case study jpl ose meeting, february...
TRANSCRIPT
Weather regimes and European heat waves.
Summer 2003: a case study
JPL OSE Meeting, February 2006Christophe Cassou, Laurent Terray & Adam Phillips
Outline of the OSE talk
1. The extreme events of 2003
2. The weather regime paradigm
3. Summertime North Atlantic weather regimes
4. Suggestion for tropical Atlantic forcing in summer 2003
JPL OSE Meeting, February 2006
1. The extreme heat events of 2003
Source : Météo France Several heat events
NASA Earth Observatory, based on data from the MODIS land team
20 July-20 AugSurf. Temp. anomaly
SeaWiFS project
8th August
Cloud free zone
Paris
A large scale European pattern
Fail the qualitycontrol of the data
1. The heat wave of August 2003
Anomalous Daily [(Min+Max)/2] temperature in Paris 27oF
11oF
0oF
-11oF
10%
100% Soil moisture
Portugal
1. The extreme heat events of 2003
Source : Météo France Several heat events
Anomalous Daily [(Min+Max)/2] temperature in Paris 27oF
11oF
0oF
-11oF
2. Persistent extreme temperature from May 15 to August 25
~16,000
~20,000
2005 estimate
15 aug. 2003
Mortality excess due to heat
20oC 69oF
Anomalous JJA temperature in Paris
Source : Météo France
Linear Trend = 0.39oC/dec.
1. The extreme heat events of 2003 3. An extreme event on top of a pronounced trend
~ 5
Need for an integrated approach to understand BOTHthe mean changes but also their associated daily changesthat can have tremendous impacts (extreme events etc.)
The weather regime approach
JJA 2003 Temp. @850hPa Surface wind JJA 2003 500 hPa Geop. JJA 2003
5oK
4. The statistico-dynamical approach
What does ‘mean’ mean in the extratropics?Temporal integration over a given period of the
occurrence of daily or quasi-daily events named “weather regimes”
1. The extreme heat events of 2003
Means and associated statistics mask the high frequency of the observed weather especially in the extratropics.
Weather regimesWeather regimes : elementary bricks of the large scale atmosphericcirculation that are spatially well defined, with a 5-10 day lifetime (persistent)and recurrent (e.g. Lorenz 1963, Vautard et al 1988)
Examples of weather regimesExamples of weather regimes: blocking events, persistent zonal flow etc.i.e. synoptic-type atmospheric circulation whose occurrence or recurrence has a significant influence in terms of impacts (temperature, precipitation, extremes etc.)
Predicting means and associated statistics masks what the daily weather could be.
5. Weather/Climate
Daily variability (weather) Seasonal-to-decadal (climate)
Spatio-temporal Scale Interaction/Downscaling
transitions between régimes modification of the frequencyof occurrence of regimes
Example: T850anom(season) = T850anom (regime)∫day
1. The extreme heat events of 2003: Introduction
Application of the weather regime paradigm to the case of summer 2003
1. Attractors in the EOF space
EOF11pt=1day (e.g. Z500 daily map) [JJA 1950-2003 i.e. 92x54 maps]Max
Max
Determination of the regimes: Determination of the maxima of density in the EOF space, or determination of the most probable i.e. recurrent atmospheric states (e.g. MSLP, Z500 patterns etc.)
Regimes can be considered as attractors in the climate phase space
EOF1
EOF3
Probability
Of occurrence
2. Determination of weather regimes
2. Classification
Weather regimes obtained by classification methods (no linearity constraint)
Ex of classified variable: 500 hPa Geopotential maps over the North Atlantic-Europe domain for a given season over a given period
1. Predetermined choice of the k number of regimes (nb. of attractors)2. Aggregation of the 2 most similar maps (choice of a criterion of similarity )
Optimal classification : Maximization of the variance inter-regimes
Optimal classification : Minimization of the variance intra-regimes
Optimization of the k number (Michelangeli et al 1995)
2. Determination of weather regimes
Day 1 Day N
3. Attractors in the EOF space after classification
Max
Max
1pt=1day (e.g. Z500 daily map) [JJA 1950-2003 i.e. 92x54 maps]
After classif.(here k=4)
2. Determination of weather regimes
4. Movement in the EOF phase space
Typical path of the atmosphereduring a given summer
2nd June
1st June
The weather we experience can be explained by the alternance/transition between the different regimes
2. Determination of weather regimes
3. Summertime North Atlantic regimes 1. Z500 summertime weather regimes
Classification from geopotential height @ 500hPa for JJA NCEP-NCAR Reanalyses over 1950-2005.
2. Relationship between regimes and mean daily temperature
Classified Z500
3. Summertime North Atlantic regimes
Anomalous Surface
Temperature(daily
composites)
Atl. Low
Blocking
Atl. Ridge
NAO-
3. Summer 2003
Blocking
NAO-Atl.Ridge
Atl.Low
Decomposition in weather regimes leads to a better interpretation of the interannual variability and build a bridge between impacts and large scale atmospheric fluctuations (Importance of scale interaction)
3. Summertime North Atlantic regimes
~ +( )JJA 2003
5. Weather regime and low frequency variability
Positive trend
NCEP-NCAR Reanalyses (JJA) [1950-2004]
Number of daysIn JJA
3. Summertime North Atlantic regimes
Positive trend
No trend
Negative trend
Changes in regime occurrence are consistent with the
observed TS trend :High frequencies dynamical entities explains part of the
very low-frequency fluctuations
15%5%30°C15°C
5%
Nu
mb
er o
f d
ays
(no
rmal
ized
)
TMAXMean
Relative change of extreme occurrence = (%)
+300%
-90%
TMAX ClimatologicalDistribution (Gaussian)
for a givenStation-data (all days)
TMAX distributionsper regime
(days where regimesare excited) : 4 distributions
TMAX
6. Relationship between regimes and extremes3. Summertime North Atlantic regimes
Extremedefinition
7. % of chances for heat wave occurrence
SQR MétéoFrance Data [1950-2002]
3. Summertime North Atlantic regimes
Atl. LowBlocking
Atl. RidgeNAO-
Change of extreme occurrence =0% 5% 10% 15%
x2 x3Clim
8. Link between mean and regimes3. Summertime North Atlantic regimes
+( )JJA 2003 Z500
+( )Anomalous Daily temperature in Paris (2003)
( )+Anomalous JJA temperature[50-03]
Time scale interaction : day-decade
4. Tropical Atlantic forcing on European heat waves 1. Impact of the forcing
Chaos (not predictive) + External forcing (ocean, Greenhouse gazes etc.)
The low frequency variability (seasonal to decadal) can be explained by changes in amplitude of the probability density function or in preferentialtransitions between regimes.
Change in the regime occurrence ratherthan change in regimes by themselves
Anomalous obs. OLR (proxy for convection) [satellite data]Wet Dry
Question: Could the anomalous ITCZ position/strength have had a role in theoccurrence of the 2003 heat events?
Model experiments
Displacement/Reinforcement of the ITCZIncreased convection over the western part of the Tropical Atlantic
4. Tropical Atlantic forcing on European heat waves 2. Tropical Atlantic ITCZ in 2003
3. Experimental setup
Model = Community Atmospheric Model (CAM2+) coupled to anOceanic mixed layer (MLM) (NCAR-Cerfacs collaboration)
-120 year of control simulation-40 members of 7 months long starting April 1st and perturbedby diabatic heating anomalies anomalies limited to the tropical Atlantic domain and estimated from observations
The 40 members differ by their 1st April i.e. 1st day atmospheric initial conditions(random selection from the control integration) and the coupling between theOcean and atmosphere is activated only in the Atlantic (north of 40S).The 40 members have the same 3D initial oceanic conditions (average of the120 April 1st from the control integration) No oceanic anomalies are imposed
degrees Celcius/day
Anomalous diabatic heating
4. Tropical Atlantic forcing on European heat waves
z
Td’
500mb
4. Summertime weather regimes in CAM4. Tropical Atlantic forcing on European heat waves
CAM
NECP
The model is able tocorrectly representthe summertime weather regimesAtl. Low
Blocking
Atl. Ridge
NAO-
Favo
r
inh
ibit
Atl.Low ++Atl.Ridge --
Blocking ++Atl.Ridge --
5. Regime response to the tropical forcing4. Tropical Atlantic forcing on European heat waves
Change in the position/strength of the Atlantic ITCZ in 2003 favors (inhibits) the occurrence of the warm regimes
(cold regimes).
Thanks to the links between extremes and regimes from observations, assessing the changes of regime occurrence in response to a forcing is promising in a seasonal forecast context (complementary information to the traditional ensemble mean).
6. Mean response to the tropical forcing4. Tropical Atlantic forcing on European heat waves
JJAT850 response (ensemble mean)
JJA NCEP T850 Model
7. Mechanisms4. Tropical Atlantic forcing on European heat waves
PluvieuxSec
Low High
Rossby wave(PLN)
Sahel-Mediterraneanconnection
Anomalous convectionin the Caribbean favors
Atl.Low regimes (via forced Rossby Waves)
Anomalous convectionin the Sahel favors
Blocking regimes (viadirect cell circulation)
Conclusions
The weather regime approach is powerful to investigatethe day-to-decade variability
Scale interaction from extremes to trends
Suggestions of tropical Atlantic forcing in summer 2003
New challenge for seasonal-to-interannual forecast for the extratropics
JJA TMAX France
Corr. TMAX June/August = 0.18
PluvieuxSec
Precip Precip
Low High
Rossby Wave(Carïbbean)
Summer NAO(direct cell?)
Z500
Z500
7. Monthly dependence of the tropical-extratropical connection4. Tropical Atlantic ….
JJA TMAX France
Corr. TMAX June/August = 0.18
PluvieuxSec
Precip
Low High
Summer NAO(direct cell?)
Z500
4. Tropical Atlantic forcing on European heat waves
Model anomalous Aug. Meridional Stream function [45oW-30oE]
8. Rossby waves + direct cell
8. Link between mean and regimes
% of regime occurrence for the 5 warmest year in France (JJA 1950-2003)
Decomposition in regime builds a bridge between a large blend ofSpatio-temporal scales
Low frequency, seasonal characteristics and extremes
3. Summertime North Atlantic regimes