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Climate sensitivity and variability with models extending into the middle atmosphere

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Title: Climate sensitivity and variability with models extending into the middle atmosphere


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/ CS2.2
WACCM/ CS2.1
5
Climate Sensitivity
  • No significant changes of CS between CAM and
    WACCM.
  • CS is a gross measure of climate change. No
    change of CS between the two models reflects tiny
    changes in all globally averaged fields (not
    shown).
  • Regional effects?

6
Surface Temperature ANN
7
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?

8
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.

9
1x CO2 Momentum Forcing
10
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.

11
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
12
DJF 500 hPa Geopotential Height
  • Both models predict a thickening of the
    atmosphere due to warming associated with the
    doubling of CO2.
  • Model responses are different regionally CAM
    shows a wave-2 (roughly) pattern with atmospheric
    thickening occurring over the continents WACCM
    pattern is weaker.

13
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.

14
Cumulative precipitation DJF
15
1x CO2 Momentum Forcing
16
EPD Difference
17
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.

18
Leading EOF
19
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 gt 0.25 in CAM.
  • WACCM is much closer to the re-analysis.
  • Both models overestimate the tropospheric
    correlation.

ERA40
Christiansen 2005
20
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
21
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.

22
Composite of strong stratospheric vortex events
  • There is little distinction between before and
    after the events in the CAM.

23
Stratospheric warmings
Model Frequency of SSW (no./year)
CAM 1x 0.14 (0.03)
WACCM 1x 0.12 (0.03)
24
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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