SOLCLI Meeting 22 October 2009 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

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

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

Circulation changes over the 11-year cycle Multiple regression analysis of NCEP/NCAR reanalysis, DJF, 1979-2002 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)

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 TR(lat,height) (2) Boundary layer friction (Rayleigh drag) (1) Hoskins & Simmons (1975) (2) Held & Suarez (1994) Experiments / analysis: Equilibrium response to perturbations to stratospheric TR (Haigh et al, 2005) Spin-up ensembles: 200 x 50-day run (Simpson et al, 2009) Annular variability in control run (Sparrow et al, 2009)

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

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

Equilibrium Response Zonal mean Temperature E5 U5 P10 Control zonal wind E5 case gives a similar response in the troposphere to that seen over the solar cycle Zonal mean zonal wind E5 U5 P10

Ensemble spin-up Experiments 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 5K 0K 4.5K 0.5K Simpson et al (2009)

Eliassen-Palm flux 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

Eddy-feedback processes Ensemble spin-up response to stratospheric heating distributions in an idealised model (Simpson et al, 2009) 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: δT_ref Tropopause [qy] trigger Refraction feedback amplifies tropospheric anomalies Baroclinicity feedback moves wave source 11

Refractive Index We can use the refractive index to see what’s 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. Eddy phase speed Zonal wind

TR1 TR2 TR3 TR4 TR5 E5 - CONTROL There is a dependence of the magnitude of the response to stratospheric heating on the jet latitude/width Page 13 © Imperial College London

E5 dependence on tropospheric basic state Decreasing baroclinicity Increasing baroclinicity TR1 TR2 TR3 TR4 TR5 Change to reference temperature TR u Climatological zonal wind E5δu E5 zonal wind response NOTE: THERE IS 1 BLANK BOX HIDING TEXT ON THE RIGHT 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)

NOTE: THERE ARE 2 BLANK BOXES HIDING EP-FLUX PLOTS ON THE RIGHT (CONTROL & ANOMALY)

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 qy=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

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. Page 17 © Imperial College London

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

NOTE: THERE IS 1 BLANK BOX HIDING PLOTS ON THE RIGHT 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

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

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

NOTE: THERE IS 1 BLANK BOX HIDING TEXT ON THE RIGHT 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

SOLCLI Meeting 22 October 2009 - Thank you - SOLCLI Meeting 22 October 2009

Reconstructed low-frequency sector composite winds at 240 hPa

Climate Change: annular response Temperature change IPCC AR4 models 2080-2099 minus 1980-1999 A2 scenario (“business as usual”) Zonal mean zonal wind 850hPa zonal wind Lorenz & DeWeaver (2007)

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

Sarah Sparrow1,2, Mike Blackburn2 and Joanna Haigh1 Modes of Annular Variability in the Atmosphere and Eddy-Zonal Flow Interactions Sarah Sparrow1,2, Mike Blackburn2 and Joanna Haigh1 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

Leading Modes of Variability Control Run EOF 1 (51.25%) EOF 2 (18.62%) Height → Latitude (equator to pole) → 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.

Phase Space Trajectories Unfiltered Periods Longer than 30 Days Low Pass Filter Periods Shorter than 30 Days High Pass Filter PC1 → PC2 → 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.

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

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

Empirical Mode Decomposition: Phase Space Tc = 4.96 ± 0.05 days Tc = 8.0 ± 0.3 days Tc = 20.3 ± 0.8 days Tc = 39 ± 2 days Tc = 78 ± 5 days Tc = 198 ± 19 days

Transformed Eulerian Mean Momentum Budget – + ω 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.

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

Phase angle lagged correlation – + ω Phase Space Angle Lag → Mode 2 Mode 4 240 hPa 967 hPa Correlation → Consideration of the phase lag between the zonal wind anomalies and .F at low levels, together with each mode’s 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.

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

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

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.