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Diagnosing stratospheric contribution to climate change in the CMIP5 models

Diagnosing stratospheric contribution to climate change in the CMIP5 models. Alexey Karpechko & Elisa Manzini. Contributions from many people, most importantly: James Anstey, Seok -Woo Son , Paolo Davini, Giuseppe Zappa, Natalia Calvo, Steven Hardiman , and others….

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Diagnosing stratospheric contribution to climate change in the CMIP5 models

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  1. Diagnosing stratospheric contribution to climatechange in the CMIP5 models Alexey Karpechko & Elisa Manzini

  2. Contributions from many people, most importantly: James Anstey, Seok-Woo Son, Paolo Davini, Giuseppe Zappa, Natalia Calvo, Steven Hardiman, and others…

  3. Stratosphere and climate change The atmosphere will change in response to GHG emissions The stratosphere will change too How will the stratosphere change? And what are the implications of stratospheric changes for tropospheric climate change?

  4. Arctic polar vortex changes -> ? In the Northern Hemisphere future changes in the Arctic polar vortex remain poorly understood, although a convergence of model results is appearing. • Equatorward shift of the polar night jet • Seems to be the most common response to doubling CO2 in stratosphere-resolving models • but • …not reproduced by all models • Large decadal variability may mask the forced signal (Butchartet al. 2000) Sigmond et al (2004)

  5. Arctic polar vortex changes • There seems to be a systematic difference between high-top (stratosphere-resolving) and low-top models • Low-top models typically simulate strengthening of zonal winds throughout the polar stratosphere but… • Not necessarily → a high-top is not needed to simulate weakening of the polar winds: ECHAM5, U, 2xCO2, JFM Scaifeet al (2011)

  6. Arctic polar vortex changes: Impacts on the troposphere • Positive vs negative response of the Northern Annular Mode • Spread of the results (Shindell et al. 1999; Fyfe et al 1999; Gillett et al. 2003; Sigmond et al. 2008, 2010; Scaife et al. 2011, Karpechko and Manzini 2012) • Likely related to changes in polar stratospheric winds (weaken or strengthen) • Future weakening of the polar stratospheric winds drives the NAM towards negative phase • (But there are other factor influencing future NAM changes) Karpechko and Manzini (2012)

  7. Future Arctic polar vortex changes Equatorward shift of the Arctic polar night jet seems to be the most common response to GHG increases in stratosphere-resolving models Large interannual and decadal variability Lack of understanding of the mechanisms Up-down or down-up influence? Impacts on future surface climate remain unclear

  8. CMIP5 models What do CMIP5 climate simulations say about future changes in the Arctic wintertime polar vortex and its implications for surface climate change?

  9. CMIP3/IPCC AR4 models High top models: the lid is above the stratopause Low top models: the lid is below the stratopause Low tops dominate based on Cordero and Forster (2007)

  10. CMIP5/IPCC AR5 models from Charlton-Perez et al (2013) High tops dominate

  11. Data • 24 CMIP5 models • 10 Low-tops, 13 High-tops, 1 intermediate (1 hPa) • Historical and rcp 8.5 simulations • Monthly mean sea level pressure (SLP), zonal mean U and T • 42 simulations for SLP and U • 7 models with more than 1 simulation • 24 simulations for T • One simulation per model only • Focus on DJF mean (unless otherwise mentioned) • Difference between 2060-2099 mean and 1961-2000 mean 22.4.2013 11

  12. CMIP5 zonal wind changes Multi-model mean change • ~70% models simulate weakening polar stratospheric winds • Large spread among individual models • Largest spread is around 70°N and 10hPa • Why spread? • What are its implications for surface climate? Intermodel standard deviation (σ) • Define stratospheric winds (SUA) index: • (-1∙ΔU)

  13. CMIP5 vs CMIP3 models • 1%CO2 experiment in CMIP3&CMIP5 • the period 101-140 minus the period 1-40 • DJF • CMIP5: Zonal winds weaken north 70N • CMIP3: Zonal winds strengthen through the stratosphere 22.4.2013 13 13

  14. CMIP5 zonaltemeparture changes Multi-model mean change • Largest intermodel spreads in: • Polar stratosphere (SUA index) • Upper tropical troposphere (tropical warming) • Lower high latitude troposphere (Arctic amplification) • Is the stratospheric spread related to those in the troposphere? • Or is it not? Intermodel standard deviation (σ)

  15. 1. Impact of tropical warming on tropospheric dynamics: 30oS EQ 30oN 60oN 90oN

  16. 1. Impact of tropical warming on tropospheric dynamics: STRONGER SUBTROPICAL WESTERLY JET 30oS EQ 30oN 60oN 90oN

  17. 2. Impact of polar amplification on tropospheric dynamics: 30oS EQ 30oN 60oN 90oN

  18. 2. Impact of polar amplification on tropospheric dynamics: WEAKER WINDS AT HIGH LATS 30oS EQ 30oN 60oN 90oN

  19. 3. A stratospheric pathway? 30oS EQ 30oN 60oN 90oN

  20. 3. A stratospheric pathway? 30oS EQ 30oN 60oN 90oN

  21. 3. A stratospheric pathway? 30oS EQ 30oN 60oN 90oN

  22. 3. A stratospheric pathway? 30oS EQ 30oN 60oN 90oN

  23. 1. Separating a stratosphere-congruent signal

  24. Approach Yj(φ,p) – T, U, or SLP change in j-th model between 2060-2099 and 1961-2000 X1j– tropical warming index ( change between 2060-2099 and 1961-2000) X2j– polar amplification index ( change between 2060-2099 and 1961-2000) X3j– stratospheric change index ( change between 2060-2099 and 1961-2000) All indices are normalized and have zero mean and unity standard deviation. Index correlation matrix: Tropics Arctic SUA Indices correlate Tropics Arctic SUA

  25. Approach A multiple regression is not used because of correlation between indices. A step-by-step regression is applied instead: 1. 2. 3. X2j– is calculated on residuals after the 1stregression X3j– is calculated on residuals after the 2ndregression The stratosphere-congruent part (a3 regression coefficient) does not change between the approaches because the SUA index doesnot correlate with the other indices.

  26. Zonal temperatures Multi-model mean change (Y) Tropical warming (X1) Polar amplification (X2) SUA index (X3) Regressions σ2(ε1)/σ 2(Y) σ2(ε2)/σ 2(Y) σ2(ε)/σ 2(Y) σ(Y)

  27. Zonal winds Multi-model mean change (Y) Tropical warming (X1) Polar amplification (X2) SUA index (X3) Regressions σ2(ε1)/σ 2(Y) σ2(ε2)/σ 2(Y) σ2(ε)/σ 2(Y) σ(Y)

  28. Sea level pressure Multi-model mean change (Y) Tropical warming (X1) Polar amplification (X2) SUA index (X3) Regressions σ(Y) σ2(ε1)/σ 2(Y) σ2(ε2)/σ 2(Y) σ2(ε)/σ 2(Y)

  29. High tops vs low tops • Different climate sensitivity in high-tops and low tops • => different Arctic SLP response • The reason is not clear • No evidences that different climate sensitivity is related to different stratospheric parts • There are evidences that the difference is NOT related to startosphericparts: • Similar climate sensitivity in high/low versions of the same model figure by S.-W. Son

  30. 2. Internal variability?

  31. Intra- vsintermodel spread ANOVA test for SUA index: Intermodel variance: 18.2 m2/s2 Mean intramodelvariance: 3.6 m2/s2 F-statistics: 5.1 Intermodel spread dominates (-1)∙ The intermodel spread in SUA index is unlikely explainable by internal variability

  32. 3. Up-downordown-upinfluence?

  33. Lagged correlation between changes at different altitudes NAM changes at the end of winter (February) Correlated with zonal wind changes at different altitudes and in different months Remove the tropical warming signal

  34. Lagged correlations NAM in February correlates better with stratospheric wind changes in previous months, rather than with tropospheric ones Downward influence

  35. Summary (1) • ~70% of CMIP5 models simulate weakening of the Arctic stratospheric winds in winter (equatorward shift of the polar night jet) • (Almost all CMIP3 models simulate strengthening of the stratospheric winds) • Spread of the polar stratospheric wind changes among individual models is large • Multiple realizations available for some models show much smaller spread around their respective means • This suggests that internal variability unlikely explains the intermodel spread in the Arctic stratospheric wind changes

  36. Summary (2) • The intermodel spread in stratospheric wind changes is not related to model climate sensitivity (i.e. tropical warming or polar amplification) • There is a strong coupling between zonal wind changes and sea level pressure changes: • A considerable inter-model spread in sea level pressure change is associated with the inter-model spread in the Arctic winter stratospheric change • Weakening of the Arctic stratospheric winds corresponds to a shift towards more negative NAM • (But overall future NAM change depends also on climate sensitivity) • Lagged correlations suggest that changes in stratospheric winds influence tropospheric changes (downward influence)

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