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Climate sensitivity and variability with models extending into the middle atmosphere

Climate sensitivity and variability with models extending into the middle atmosphere. F. Sassi National Center for Atmospheric Research Climate and Global Dynamics. The impact of the middle atmosphere on tropospheric climate: The climate sensitivity.

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Climate sensitivity and variability with models extending into the middle atmosphere

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  1. Climate sensitivity and variability with models extending into the middle atmosphere F. Sassi National Center for Atmospheric Research Climate and Global Dynamics

  2. The impact of the middle atmosphere on tropospheric climate:The climate sensitivity • Climate sensitivity (CS) is a broadly used tool to determine the models response to different forcing (increase of GHGs, solar variability, aerosols, etc.) • CS is defined as the equilibrium change of global surface temperature following a doubling of CO2. • Gregory et al (2004) have defined a simple method to calculate CS based on linear regression analysis between the change of net heat flux at the TOA and the change of global surface temperature using an atmospheric model coupled to a SOM. • This method has been used recently by Kiehl et al (2006) to calculate the CS of the CCSM3.

  3. The impact of the middle atmosphere on tropospheric climate:The simulations • Run WACCM and CAM in similar configurations: • CAM3 + SOM, present day CO2 • CAM3 + SOM, 2xCO2 • WACCM3 + SOM, present day CO2, full chemistry • WACCM3 + SOM, 2xCO2, full chemistry • Although by and large the physical parameterization that turn CAM into WACCM are relevant only above the stratopause, WACCM is not exactly identical to CAM: • Efficiency parameter for orographic gravity waves

  4. Climate Sensitivity CAM/ CS=2.2 WACCM/ CS=2.1

  5. Surface Temperature ANN

  6. Surface Albedo ANN • Both models predict an Arctic reduction of albedo ( surfarce warming  less sea ice) in the doubled CO2 scenario. • The Arctic changes are greater in CAM than in WACCM. • These changes have a seasonal cycle (not shown), being more pronounced in DJF. • Implications for ocean circulation?

  7. DJF Sea Level Pressure • Both models predict a reduction of sea level pressure over the Arctic. • As before, changes are larger and more ubiquitous in CAM than in WACCM. • Note that sea level pressure over the north Atlantic is shallower in WACCM than in CAM.

  8. 1x CO2 Momentum Forcing

  9. DJF Zonal Mean Zonal Wind • As the strength of the polar vortex decreases, the sea level pressure is expected to decrease: stronger westward drag in the stratosphere stronger mean meridional circulation  mass redistribution between polar and low latitudes. • This similar to the Polvani and Kushner mechanism.

  10. Redistribution of mass in the vertical column • The sea level pressure change WACCM – CAM poleward of 60N is ~ 230 Pa  a total mass redistribution of ~ 8E14 Kg. • About 50% of that mass change occurs in the stratosphere. Approx. location of tropopause at high latitudes

  11. DJF Zonal Mean Temperature • Both models produce an increase of temperature in the troposphere and a decrease in the lower stratosphere. • Upper tropical tropospheric warming is larger in CAM. • Tropical middle stratospheric cooling is larger in WACCM.

  12. EPD Difference

  13. NH Annular Modes • Use daily data of geopotential interpolated to standard pressure levels. • Take only data northward of 20N, zonally averaged. • Calculate the composite annual cycle and the anomalies against it. • Obtain the leading zonal mean pattern (EOF-1) from the WACCM 1x simulation. • Project the pattern on the time series ( PC). • Stratospheric influence on the troposphere: • Calculate lag correlation of all points vrs 10 hPa and near surface • Calculate composite of stratospheric weak and strong jet events.

  14. Correlation with near surface events • Correlation with near surface events is amplified in CAM at lag zero: Near 1 hPa, the re-analysis show a correlation less than 0.1, while it is > 0.25 in CAM. • WACCM is much closer to the re-analysis. • Both models overestimate the tropospheric correlation. ERA40 Christiansen 2005

  15. Correlation with stratospheric events • Downward progression of stratospheric anomalies is quite similar between the two models in the stratosphere. • In the troposphere, there is no downward progression in CAM/WACCM. ERA40 Christiansen 2005

  16. Composite of weak stratospheric vortex events • Both models show a relatively long persistence of the anomalies in the lower stratosphere. This is consistent with longer newtonian relaxation rate. • The WACCM simulations show that tropospheric anomalies lead the stratospheric events. This is a realistic feature that is not reproduce in the CAM. • Downward influence of stratospheric events on the troposphere wanes rapidly in CAM. WACCM suggests longer time scales.

  17. CONCLUSIONS • Globally averaged measures of climate change are identical in both CAM and WACCM  the presence of a well resolved middle atmosphere is irrelevant to metrics like CS. • Regional metrics can be different in the two models: surface temperature, sea ice, sea level pressure, zonal mean temperature. By and large, the signatures of change are amplified in CAM compared to WACCM. • By and large, stratosphere-troposphere coupling is more realistic in WACCM than in CAM.

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