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The tropospheric response to idealised stratospheric forcing: its dependence on basic state Mike Blackburn (1), Joanna D. Haigh (2), Isla Simpson (2,3),

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Presentation on theme: "The tropospheric response to idealised stratospheric forcing: its dependence on basic state Mike Blackburn (1), Joanna D. Haigh (2), Isla Simpson (2,3),"— Presentation transcript:

1 The tropospheric response to idealised stratospheric forcing: its dependence on basic state Mike Blackburn (1), Joanna D. Haigh (2), Isla Simpson (2,3), Sarah Sparrow (1,2) (1) NCAS-Climate, Department of Meteorology, University of Reading, UK (2) Space and Atmospheric Physics, Imperial College London, UK (3) Department of Physics, University of Toronto, Canada. SOLCLI Meeting 22 October 2009

2 Outline Tropospheric response to idealised stratospheric heating (review) Dependence on tropospheric climatological basic state equilibrium response spin-up ensembles – mechanisms Relationship to unforced annular variability

3 Solar index regressions using reanalysis data Crooks & Gray (2005) ECMWF reanalyses 1979-2001 (ERA-40) Observed stratospheric temperature signal solar max - solar min

4 Circulation changes over the 11-year cycle Weakening and poleward shift of the mid-latitude jets. Weakening and expansion of the Hadley cells. Poleward shift of the Ferrell cells. Haigh and Blackburn (2006) Multiple regression analysis of NCEP/NCAR reanalysis, DJF, 1979-2002

5 Simplified GCM - dynamical core model Based on University of Reading primitive equation model: (1) Spectral dynamics: T42 L15 No orography Newtonian cooling – idealised equinoctial radiative- convective equilibrium temperatures T R (lat,height) (2) Boundary layer friction (Rayleigh drag) Experiments / analysis: 1.Equilibrium response to perturbations to stratospheric T R (Haigh et al, 2005) 2.Spin-up ensembles: 200 x 50-day run (Simpson et al, 2009) 3.Annular variability in control run (Sparrow et al, 2009) (1) Hoskins & Simmons (1975) (2) Held & Suarez (1994)

6 The model: control climate Control run zonal wind Control run temperature Relaxation Temperature

7 Idealised stratospheric heating Heating perturbations can be applied to the stratosphere by changing the relaxation temperature profile P10 Polar heating (10K) 5K 0K 5K 0K E5 Equatorial heating (5K)U5 Uniform heating (5K) 10K Applied 3 different heating perturbations Haigh et al (2005)

8 Equilibrium Response Zonal mean Temperature Zonal mean zonal wind Control zonal wind E5U5P10 E5U5P10 E5 case gives a similar response in the troposphere to that seen over the solar cycle

9 Haigh et al (2005) - Equatorial heating gave a similar tropospheric response to that seen over the solar cycle Coherent displacement of the jet and storm-track How does this arise? Spin-up ensemble for the equatorial heating case: –200, 50-day runs Ensemble spin-up Experiments 5K 0K 4.5K 0.5K Simpson et al (2009)

10 Flux of wave activity in latitude-height plane Conserved following eddy group velocity (assumptions) Components proportional to eddy heat + momentum fluxes E-P flux divergence quantifies eddy forcing of mean state Eliassen-Palm flux

11 Eddy-feedback processes Ensemble spin-up response to stratospheric heating distributions in an idealised model (Simpson et al, 2009) Tropopause [ q y ] trigger Refraction feedback amplifies tropospheric anomalies Baroclinicity feedback moves wave source E-P Flux, days 0 to 9 E-P Flux, days 20 to 29 E-P Flux, days 40 to 49 u, days 20 to 29 u, days 40 to 49 Heating: δ T_ref

12 Refractive Index We can use the refractive index to see whats causing the change in eddy propagation. Eddies should be refracted towards regions of higher refractive index. Meridional PV gradient - Depends on the vertical gradients in temperature and zonal wind and meridional zonal wind curvature. Zonal wind Eddy phase speed

13 © Imperial College LondonPage 13 E5 - CONTROL There is a dependence of the magnitude of the response to stratospheric heating on the jet latitude/width TR1TR2TR3TR4TR5

14 E5 dependence on tropospheric basic state Equilibrium experiments with modified tropospheric reference temperature Stronger response to stratospheric forcing for lower latitude jets Indicative of stronger eddy feedback (despite weaker eddies in control) E5 zonal wind response Climatological zonal wind TR1TR2TR3TR4 Change to reference temperature Decreasing baroclinicityIncreasing baroclinicity TR5 TRTR u E5 δu NOTE: THERE IS 1 BLANK BOX HIDING TEXT ON THE RIGHT


16 Dynamical Mechanisms Hypotheses Sensitivity of EP-flux propagation / refraction to basic state: - expect spin-up to vary from t=0? Sensitivity of critical latitude wave absorption ( u=c or q y =0 ) : - different spectrum of eddy phase speeds (for climatology or spin-up)? - narrower latitude band for low-latitude jets ( u/ y larger) Strength of baroclinic feedback: - is low-latitude response more baroclinic ( higher eddy growth rates)? - simple metrics should verify/falsify this

17 © Imperial College LondonPage 17 Forcing / response correlation Eddy forcing correlates more strongly with wind response for low-latitude jets Indicative of stronger eddy feedback onto the annular dipole Evidence of refraction or critical line mechanisms? Correlation between u v convergence and zonal wind anomalies, for all latitudes and heights.

18 E5 spin-up dependence on climatology Correlation of eddy forcing and zonal wind response Vertical integrals Strat. Trop.

19 Relationship to unforced internal variability Find strongest response to forcing for lower latitude jets How is this related to the unforced internal variability? Fluctuation-Dissipation Theorem (FDT) predicts a stronger response for longer timescales of internal variability Due to stronger internal (eddy) feedbacks, maintaining the leading mode(s) of variability against damping NOTE: THERE IS 1 BLANK BOX HIDING PLOTS ON THE RIGHT

20 © Imperial College LondonPage 20 Timescales of variability 1-point correlation maps of zonal wind anomalies wrt peak negative response at 200hPa Mid-latitude jets: short timescale; propagating Low latitude jets: long timescale; stationary

21 Annular variability in TR3 control Evidence for 2 types of natural variability: poleward propagating anomalies – short timescale persistent stationary anomalies – long timescale Persistent behaviour dominates for lower latitude jets Propagating behaviour dominates for higher latitude jets

22 Conclusions Previously identified eddy feedbacks responsible for the tropospheric response to idealised stratospheric heating Large variation of response magnitude to climatological basic state Several possible dynamical mechanisms Response variation consistent with timescale of unforced variability (FDT) poleward propagating anomalies – short timescale – weak response persistent stationary anomalies – long timescale – strong response Future Work Analyse dynamics of forcing response & spin-up (mechanisms) Dynamics of unforced variability – separate & characterise 2 types Extended stratosphere; mechanical forcing (Alice Verweyen PhD) NOTE: THERE IS 1 BLANK BOX HIDING TEXT ON THE RIGHT

23 - Thank you - SOLCLI Meeting 22 October 2009



26 Reconstructed low-frequency sector composite winds at 240 hPa

27 Climate Change: annular response Lorenz & DeWeaver (2007) IPCC AR4 models 2080-2099 minus 1980-1999 A2 scenario (business as usual) Zonal mean zonal wind850hPa zonal wind Temperature change

28 Idealised GCM: annular response Lorenz & DeWeaver (2007) Zonal wind response to localised heating 150hPa deep, 20° wide latitude


30 Modes of Annular Variability in the Atmosphere and Eddy-Zonal Flow Interactions Sarah Sparrow 1,2, Mike Blackburn 2 and Joanna Haigh 1 1. Imperial College London, UK 2. National Centre for Atmospheric Science, University of Reading, UK MOCA-09 M06 Theoretical Advances in Dynamics 20 July 2009 v.6

31 Leading Modes of Variability EOF 1 (51.25%) EOF 2 (18.62%) EOF1 represents a latitudinal shift of the mean jet. EOF2 represents a strengthening (weakening) and narrowing (broadening) of the jet. Both of these patterns are needed to describe a smooth latitudinal migration of the jet. Control Run Latitude (equator to pole) Height

32 Phase Space Trajectories At low frequencies circulation is anticlockwise with a timescale of 82 ± 27 days. At high frequencies circulation is clockwise with a timescale of 8.0 ± 0.3 days. Unfiltered Periods Longer than 30 Days Low Pass Filter Periods Shorter than 30 Days High Pass Filter PC1 PC2

33 Phase Space View of Momentum Budget Eddies change behaviour at high and low frequencies and jet migration changes direction. At low frequencies it is unclear what drives the poleward migration. PC1 PC2 PC1 PC2 Low Pass High Pass

34 Empirical Mode Decomposition (EMD): Spectra EMD is a technique for analysing different timescales in non-linear and non-stationary data. Resulting time- series are similar to band-pass filtered data. For a given mode a similar frequency band is sampled for both PC1 and PC2. Period (Days) Amplitude (ms -1 ) Zonal Wind PC1 Zonal Wind PC2

35 Empirical Mode Decomposition: Phase Space Mode 1Mode 2 Mode 4 Mode 3 Mode 6Mode 5 T c = 4.96 ± 0.05 days T c = 8.0 ± 0.3 daysT c = 20.3 ± 0.8 days T c = 39 ± 2 daysT c = 78 ± 5 days T c = 198 ± 19 days

36 Transformed Eulerian Mean Momentum Budget High Frequencies: Eddies drive equatorward migration. Eddies out of phase with winds near the surface. Intermediate Frequencies: Eddies drive poleward migration. Residual circulation drives jet migration at lower levels. Eddies in phase with the winds near the surface. – – + ω

37 TEM Momentum Budget at 240 hPa Mode 2 Mode 4 Latitude Phase Angle – – + ω

38 Phase angle lagged correlation Phase Space Angle Lag Mode 2 Mode 4 240 hPa967 hPa Correlation – – + ω Consideration of the phase lag between the zonal wind anomalies and.F at low levels, together with each modes circulation timescale, shows that the EP-flux source responds to low level baroclinicity with a lag of 2-4 days for all modes. Low frequencies: almost in phase, small.F lag. High frequencies: almost out of phase.

39 Eddy propagation responds to current zonal wind anomalies. Resulting upper level EP- flux divergence forces further zonal wind changes. Refractive index anomalies determined by wind anomalies Larger effect near critical lines phase offset Refractive Index and EP-flux (single composite) High FrequencyLow Frequency Eddies propagate towards high refractive index

40 Eddy feedback processes Refractive Index determined by wind anomalies Eddies propagate towards high refractive index Resulting EP-flux divergence drives zonal wind changes (phase offset) Eddy source lags baroclinicity (zonal wind anomalies) by 2-4 days Latitude Height Latitude Height Latitude Height Latitude Height Latitude Height High Frequency Low Frequency

41 Conclusions Annular variability at different timescales in a Newtonian forced AGCM: –Equatorward migration of anomalies at high frequencies –Poleward migration at low frequencies For all timescales the jet migration is driven by the eddies at upper levels and conveyed to lower levels by the residual circulation. Evidence for two feedback processes: Eddy source responds to low-level baroclinicity, with lag 2-4 days: –High frequency flow is so strongly eddy driven that wind anomalies almost out of phase with wave source. –Low frequency wind anomalies and eddy source are almost in phase. Wind anomalies dominate refractive index, leading to positive eddy feedback via EP-flux divergence. Direction of propagation from relative phases of wave source/sink and wave refraction.

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