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Weather regimes and European heat waves. Summer 2003: a case study. Christophe Cassou, Laurent Terray & Adam Phillips. JPL OSE Meeting, February 2006. Outline of the OSE talk. The extreme events of 2003 The weather regime paradigm Summertime North Atlantic weather regimes
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Weather regimes and European heat waves. Summer 2003: a case study Christophe Cassou, Laurent Terray & Adam Phillips JPL OSE Meeting, February 2006
Outline of the OSE talk • The extreme events of 2003 • The weather regime paradigm • Summertime North Atlantic weather regimes • Suggestion for tropical Atlantic forcing in summer 2003 JPL OSE Meeting, February 2006
The extreme heat events of summer 2003 Part 1
Fail the quality control of the data Several heat events NASA Earth Observatory, based on data from the MODIS land team A large scale European pattern Cloud free zone Paris 20 July-20 Aug Surf. Temp. anomaly 8th August SeaWiFS project 1. The heat wave of August 2003 1. The extreme heat events of 2003 Anomalous Daily [(Min+Max)/2] temperature in Paris 27oF 11oF 0oF Source : Météo France -11oF
Several heat events 100% ~16,000 ~20,000 10% 2005 estimate 2. Persistent extreme temperature from May 15 to August 25 1. The extreme heat events of 2003 Anomalous Daily [(Min+Max)/2] temperature in Paris 27oF 11oF 20oC 0oF 69oF Source : Météo France -11oF Soil moisture 15 aug. 2003 Portugal Mortality excess due to heat
~ 5s Anomalous JJA temperature in Paris Linear Trend = 0.39oC/dec. Source : Météo France 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 1. The extreme heat events of 2003 3. An extreme event on top of a pronounced trend 500 hPa Geop. JJA 2003 JJA 2003 Temp. @850hPa Surface wind JJA 2003 5oK
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: 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.) 4. The statistico-dynamical approach 1. The extreme heat events of 2003 Means and associated statistics mask the high frequency of the observed weather especially in the extratropics. Predicting means and associated statistics masks what the daily weather could be. 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”
∫ day 5. Weather/Climate 1. The extreme heat events of 2003: Introduction Daily variability (weather) Seasonal-to-decadal (climate) transitions between régimes modification of the frequency of occurrence of regimes Spatio-temporal Scale Interaction/Downscaling Example: T850anom(season) = T850anom (regime) Application of the weather regime paradigm to the case of summer 2003
Determination of Weather regimes Part 2
Max 1pt=1day (e.g. Z500 daily map) [JJA 1950-2003 i.e. 92x54 maps] Probability Of occurrence EOF3 EOF1 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 1. Attractors in the EOF space 2. Determination of weather regimes EOF1
Optimal classification : Minimization of the variance intra-regimes 2. Classification 2. Determination of weather regimes 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 Day 1 Day N 1. Predetermined choice of the knumber 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 Optimization of the k number (Michelangeli et al 1995)
Max 1pt=1day (e.g. Z500 daily map) [JJA 1950-2003 i.e. 92x54 maps] Max 3. Attractors in the EOF space after classification 2. Determination of weather regimes After classif. (here k=4)
4. Movement in the EOF phase space 2. Determination of weather regimes Typical path of the atmosphere during a given summer 1st June 2nd June The weather we experience can be explained by the alternance/transition between the different regimes
Summertime North Atlantic weather regimes Part 3
3. Summertime North Atlantic regimes 1. Z500 summertime weather regimes Classification from geopotential height @ 500hPa for JJA NCEP-NCAR Reanalyses over 1950-2005.
3. Summertime North Atlantic regimes 2. Relationship between regimes and mean daily temperature Atl. Low Anomalous Surface Temperature (daily composites) Blocking Classified Z500 Atl. Ridge NAO-
Blocking Atl.Low NAO- Atl.Ridge ) JJA 2003 ~ ( + 3. Summertime North Atlantic regimes 3. Summer 2003 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 4. Interannual variability 2003: Warmest Summer Typical Summer
Changes in regime occurrence are consistent with the observed TS trend : High frequencies dynamical entities explains part of the very low-frequency fluctuations 3. Summertime North Atlantic regimes 5. Weather regime and low frequency variability Number of days In JJA Positive trend Positive trend No trend NCEP-NCAR Reanalyses (JJA) [1950-2004] Negative trend
Extreme definition -90% TMAX Mean +300% 15°C 30°C 15% 5% 5% (%) Relative change of extreme occurrence = 3. Summertime North Atlantic regimes 6. Relationship between regimes and extremes TMAX Climatological Distribution (Gaussian) for a given Station-data (all days) TMAX distributions per regime (days where regimes are excited) : 4 distributions Number of days (normalized) TMAX
3. Summertime North Atlantic regimes 7. % of chances for heat wave occurrence Blocking Atl. Low SQR Météo France Data [1950-2002] NAO- Atl. Ridge Clim x2 x3 Change of extreme occurrence = 15% 0% 5% 10%
Anomalous Daily temperature in Paris (2003) ) ( + JJA 2003 Z500 ) ( + ) ( + Anomalous JJA temperature[50-03] 3. Summertime North Atlantic regimes 8. Link between mean and regimes Time scale interaction : day-decade
Tropical Atlantic forcing On European heat waves Part 4
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 preferential transitions between regimes. Change in the regime occurrence rather than change in regimes by themselves
Wet Dry Displacement/Reinforcement of the ITCZ Increased convection over the western part of the Tropical Atlantic Question: Could the anomalous ITCZ position/strength have had a role in the occurrence of the 2003 heat events? Model experiments 4. Tropical Atlantic forcing on European heat waves 2. Tropical Atlantic ITCZ in 2003 Anomalous obs. OLR (proxy for convection) [satellite data]
4. Tropical Atlantic forcing on European heat waves 3. Experimental setup z 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 1st and perturbed • by diabatic heating anomalies anomalies limited to the tropical • Atlantic domain and estimated from observations 500mb Td’ Anomalous diabatic heating degrees Celcius/day 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 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 1st from the control integration) No oceanic anomalies are imposed
4. Tropical Atlantic forcing on European heat waves 4. Summertime weather regimes in CAM Blocking Atl. Ridge The model is able to correctly represent the summertime weather regimes Atl. Low NAO- N E C P C A M
Change in the position/strength of the Atlantic ITCZ in 2003 favors (inhibits) the occurrence of the warm regimes (cold regimes). 4. Tropical Atlantic forcing on European heat waves 5. Regime response to the tropical forcing Atl.Low ++ Atl.Ridge -- Favor inhibit Blocking ++ Atl.Ridge --
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). 4. Tropical Atlantic forcing on European heat waves 6. Mean response to the tropical forcing JJAT850 response (ensemble mean) JJA NCEP T850 Model
Rossby wave (PLN) Sahel-Mediterranean connection Sec Pluvieux 4. Tropical Atlantic forcing on European heat waves 7. Mechanisms Low High 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)
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
JJA TMAX France Corr. TMAX June/August = 0.18 Sec Pluvieux Low High Precip Precip Z500 Z500 Summer NAO (direct cell?) Rossby Wave (Carïbbean) 4. Tropical Atlantic …. 7. Monthly dependence of the tropical-extratropical connection
JJA TMAX France Corr. TMAX June/August = 0.18 Sec Pluvieux 4. Tropical Atlantic forcing on European heat waves 8. Rossby waves + direct cell Low High Model anomalous Aug. Meridional Stream function [45oW-30oE] Precip Z500 Summer NAO (direct cell?)
3. Summertime North Atlantic regimes 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 8. Link between mean and regimes Info ici sur la nature des regimes et sur leur modification + recurrent mais moins persistent et mois creuse.