1. Weather regimes and European heat waves. Summer 2003: a case study JPL OSE Meeting, February 2006Christophe Cassou, Laurent Terray & Adam Phillips

2. 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

3. The extreme heat events of summer 2003 Part 1

4. 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 Aug Surf. Temp. anomaly SeaWiFS project 8 th August Cloud free zone Paris A large scale European pattern Fail the quality control of the data 1. The heat wave of August 2003 Anomalous Daily [(Min+Max)/2] temperature in Paris 27 o F 11 o F 0oF0oF -11 o F

5. 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 27 o F 11 o F 0oF0oF -11 o F 2. Persistent extreme temperature from May 15 to August 25 ~16,000 ~20,000 2005 estimate 15 aug. 2003 Mortality excess due to heat 20 o C69 o F

6. Anomalous JJA temperature in Paris Source : Météo France Linear Trend = 0.39 o C/dec. 1. The extreme heat events of 20033. An extreme event on top of a pronounced trend ~ 5  Need for an integrated approach to understand BOTH the mean changes but also their associated daily changes that can have tremendous impacts (extreme events etc.) The weather regime approach JJA 2003 Temp. @850hPaSurface wind JJA 2003 500 hPa Geop. JJA 2003 5oK5oK

7. 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 regimes Weather regimes : elementary bricks of the large scale atmospheric circulation 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 regimes Examples 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.

8. 5. Weather/Climate Daily variability (weather)Seasonal-to-decadal (climate) Spatio-temporal Scale Interaction/Downscaling transitions between régimesmodification of the frequency of occurrence of regimes Example : T850 anom (season) = T850 anom (regime) ∫ day 1. The extreme heat events of 2003: Introduction Application of the weather regime paradigm to the case of summer 2003

9. Determination of Weather regimes Part 2

10. 1. Attractors in the EOF space EOF1 1pt=1day (e.g. Z500 daily map) [JJA 1950-2003 i.e. 92x54 maps] 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

11. 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 1Day N

12. 3. Attractors in the EOF space after classification 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

13. 4. Movement in the EOF phase space Typical path of the atmosphere during a given summer 2 nd June 1 st June The weather we experience can be explained by the alternance/transition between the different regimes 2. Determination of weather regimes

14. Summertime North Atlantic weather regimes Part 3

15. 3. Summertime North Atlantic regimes 1. Z500 summertime weather regimes Classification from geopotential height @ 500hPa for JJA NCEP-NCAR Reanalyses over 1950-2005.

16. 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-

17. 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

18. 4. Interannual variability 2003: Warmest Summer Typical Summer 3. Summertime North Atlantic regimes

19. 5. Weather regime and low frequency variability Positive trend NCEP-NCAR Reanalyses (JJA) [1950-2004] Number of days In 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

20. 15% 5% 30°C 15°C 5% Number of days (normalized) TMAX Mean Relative change of extreme occurrence = (%) +300%-90% TMAX Climatological Distribution (Gaussian) for a given Station-data (all days) TMAX distributions per regime (days where regimes are excited) : 4 distributions TMAX 6. Relationship between regimes and extremes 3. Summertime North Atlantic regimes Extreme definition

21. 7. % of chances for heat wave occurrence SQR Météo France Data [1950-2002] 3. Summertime North Atlantic regimes Atl. Low Blocking Atl. RidgeNAO- Change of extreme occurrence = 0%5%10% 15% x2x3 Clim

22. 8. Link between mean and regimes 3. Summertime North Atlantic regimes + ( ) JJA 2003 Z500 + ( ) Anomalous Daily temperature in Paris (2003) ( ) + Anomalous JJA temperature[50-03] Time scale interaction : day-decade

23. Tropical Atlantic forcing On European heat waves Part 4

24. 4. Tropical Atlantic forcing on European heat waves1. 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 preferential transitions between regimes. Change in the regime occurrence rather than change in regimes by themselves

25. Anomalous obs. OLR (proxy for convection) [satellite data] WetDry Question: Could the anomalous ITCZ position/strength have had a role in the occurrence of the 2003 heat events? Model experiments Displacement/Reinforcement of the ITCZ Increased convection over the western part of the Tropical Atlantic 4. Tropical Atlantic forcing on European heat waves2. Tropical Atlantic ITCZ in 2003

26. 3. Experimental setup Model = Community Atmospheric Model (CAM2+) coupled to an Oceanic mixed layer (MLM) (NCAR-Cerfacs collaboration) -120 year of control simulation -40 members of 7 months long starting April 1 st and perturbed by diabatic heating anomalies anomalies limited to the tropical Atlantic domain and estimated from observations The 40 members differ by their 1 st April i.e. 1 st day atmospheric initial conditions (random selection from the control integration) and the coupling between the Ocean and atmosphere is activated only in the Atlantic (north of 40S). The 40 members have the same 3D initial oceanic conditions (average of the 120 April 1 st 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’Td’ 500mb

27. 4. Summertime weather regimes in CAM4. Tropical Atlantic forcing on European heat waves CAMCAM NECPNECP The model is able to correctly represent the summertime weather regimes Atl. Low Blocking Atl. Ridge NAO-

28. Favor inhibit Atl.Low ++ Atl.Ridge -- Blocking ++ Atl.Ridge -- 5. Regime response to the tropical forcing 4. 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).

29. 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 forcing 4. Tropical Atlantic forcing on European heat waves JJAT850 response (ensemble mean) JJA NCEP T850 Model

30. 7. Mechanisms 4. Tropical Atlantic forcing on European heat waves PluvieuxSec LowHigh Rossby wave (PLN) Sahel-Mediterranean connection Anomalous convection in the Caribbean favors Atl.Low regimes (via forced Rossby Waves) Anomalous convection in the Sahel favors Blocking regimes (via direct cell circulation)

31. Conclusions The weather regime approach is powerful to investigate the 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

32. JJA TMAX France Corr. TMAX June/August = 0.18 PluvieuxSec Precip LowHigh Rossby Wave (Carïbbean) Summer NAO (direct cell?) Z500 7. Monthly dependence of the tropical-extratropical connection 4. Tropical Atlantic ….

33. JJA TMAX France Corr. TMAX June/August = 0.18 PluvieuxSec Precip LowHigh Summer NAO (direct cell?) Z500 4. Tropical Atlantic forcing on European heat waves Model anomalous Aug. Meridional Stream function [45 o W-30 o E] 8. Rossby waves + direct cell

34. 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 of Spatio-temporal scales Low frequency, seasonal characteristics and extremes 3. Summertime North Atlantic regimes

35. 8. Link between mean and regimes Info ici sur la nature des regimes et sur leur modification + recurrent mais moins persistent et mois creuse. 3. Summertime North Atlantic regimes