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Stratosphere-Troposphere Dynamical Coupling and its relationship to Annular Variability of the Troposphere Michael Blackburn (1), Joanna D. Haigh (2),

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Presentation on theme: "Stratosphere-Troposphere Dynamical Coupling and its relationship to Annular Variability of the Troposphere Michael Blackburn (1), Joanna D. Haigh (2),"— Presentation transcript:

1 Stratosphere-Troposphere Dynamical Coupling and its relationship to Annular Variability of the Troposphere Michael 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. NTTG 3 June 2010

2 Outline Motivation – response to climate forcings Idealised stratospheric heating experiments equilibrium response spin-up ensembles – mechanisms unforced annular variability Dependence on tropospheric climatological basic state

3 Climate Change: annular response Lorenz & DeWeaver (2007) IPCC AR4 models minus A2 scenario (business as usual) Zonal mean zonal wind850hPa zonal wind Temperature change Yin (2005); Miller et al (2006);

4 © Imperial College LondonPage 4 Polar cap T trend ( )DJF u trend ( ) Comparing IPCC models with and without ozone recovery: With recovery Without recovery 21st century Ozone Recovery Son et al (2008), Science

5 Solar index regressions using reanalysis data Frame & Gray (2009) ECMWF reanalyses (ERA-40) Multiple regression, inc. solar 10.7cm flux Observed stratospheric temperature signal solar max - solar min Crooks & Gray (2005);

6 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,

7 Proposed mechanisms for solar response (1) ~1 Wm -2 variation, 0.08% of S 0 Total Solar IrradianceAmplification in solar UV Impact on ozone: Haigh (1994) Spectral data from Lean (2000)

8 Proposed mechanisms for solar response (2) Modulation of planetary waves; impact on Brewer-Dobson circulation, Kodera & Kuroda (2002) Planetary wave impact on polar vortex. Solar: Gray et al (2001) Interaction with QBO (Holton-Tan) QBO eastQBO west Nov-Dec composites, u g, EP-flux

9 Simplified GCM - dynamical core model Control run zonal wind Control run temperature Relaxation Temperature Based on Hoskins & Simmons (1975) primitive equation model Spectral dynamics: T42 L15 Newtonian relaxation (Held-Suarez) Boundary layer friction (Rayleigh drag, σ > 0.7) No orography / forcing of planetary waves

10 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)

11 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

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

13 Poleward or equatorward shift of tropospheric jet dependent on stratospheric heating distribution 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) First recall storm-track diagnostics....

14 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 Eliassen & Palm (1961); Charney & Drazin (1961); Andrews & McIntyre (1976); Edmon et al (1980)

15 Eddy-feedback processes Ensemble spin-up response to stratospheric heating distributions in the 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

16 Response to forcing projects onto leading annular modes (2D phase space projection) EOF 1 (51.25%) EOF 2 (18.62%) Control Run Latitude (equator to pole) Height Leading Modes of Variability Sparrow et al (2009) Poleward Equatorward Narrower, Stronger Broader, Weaker PC1 Amplitude PC2 Amplitude E5 U5 C

17 Poleward jet migration Driven by upper-level momentum / EP-fluxes Low frequency variability - dynamics Sparrow et al (2009) Low frequency phase-space circulation Positive eddy feedback Leads to long timescales of variability Similarity to forced response High-PC1 composite

18 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


20 Possible causes of sensitivity Under investigation…. Not due to proximity of stratospheric heating to jet (equatorial and polar heating responses scale similarly) Suggested mechanisms: - proximity of sub-tropical critical line - wave refraction - baroclinic feedback Evidence for refraction feedback mechanism: - projection of eddy forcing onto wind response varies - responses differ from early in spin-up? Are different responses related to unforced variability?

21 © Imperial College LondonPage 21 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.

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

23 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 FDT references: Leith (1971); Ring & Plumb (2008) etc

24 © Imperial College LondonPage 24 Timescales of variability 1-point correlation maps of zonal wind anomalies wrt peak easterly response at 200hPa Mid-latitude jets: short timescale; propagating Low latitude jets: long timescale; stationary

25 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 Need to separate and characterise these distinct modes of variability

26 Conclusions Mechanism identified by which stratospheric change displaces the tropospheric jet and storm-track. Relevant to the tropospheric response to all stratospheric climate forcings. Dynamical mechanism is related to the slowest modes of annular variability. Forced response and variability are both driven by storm-track transient eddy feedback. Strength of eddy feedback depends on the latitude / width of the jet: - GCMs need realistic variability for correct forced response (FDT) - 2 types of annular variability in sGCM - under investigation

27 - Questions? - NTTG 3 June 2010


29 © Imperial College LondonPage 29 Diagnosing the cause of this change T REF T u E-P Flux – gives the direction of propagation of the eddies: Refractive Index: Changes in u, T etc Changes in n 2 changes in E-P Flux Changes in uv

30 © Imperial College LondonPage 30 The initial response (days 0 to 9) change due to: The initial response is a weakening of the upward E-P Flux around the tropopause and associated changes in horizontal eddy momentum flux. The refractive index shows it is the vertical temperature gradient/lowering of the tropopause that is the important initial trigger.

31 © Imperial College London Page 31 The later response (Feedback) (days 40 to 49) change due to:

32 © Imperial College London Page 32 The later response (Feedback) (days 40 to 49) E-P Flux Feedback : As the zonal wind starts to change in the troposphere it acts to change eddy propagation in such a way that acts to enhance the zonal wind anomalies.

33 © Imperial College LondonPage 33 Proposed mechanism Altered vertical temperature gradient Temperature, days 0 to 9, E5 - C Weakened upward E-P flux E-P Flux, days 0 to 9, E5 - C Change in horizontal eddy momentum flux uv, days 0 to 9, E5 - C Change in mean meridional circulation uv, days 0 to 9, E5 - C mmc, days 0 to 9, E5 - C Zonal wind accelerations in the troposphere. uv, days 20 to 29, E5 - C u, days 20 to 29, E5 - C E-P Flux, days 20 to 29, E5 - C u, days 20 to 29, E5 - C mmc, days 20 to 29, E5 - C

34 © Imperial College LondonPage 34 What controls the direction of jet shift? 0K 5K 0K E5 Equatorial heating (5K) U5 Uniform heating (5K) 10K Poleward shift Equatorward shift

35 DAYS 0–9 E5P10 E-P Flux

36 DAYS 20–29 E5P10

37 DAYS 40–49 E5P10 E-P Flux and


39 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


41 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

42 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

43 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

44 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

45 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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