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Climate forcing, adjustment and feedback Christopher S. Bretherton Atmospheric Sciences and Applied Mathematics University of Washington with help from.

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Presentation on theme: "Climate forcing, adjustment and feedback Christopher S. Bretherton Atmospheric Sciences and Applied Mathematics University of Washington with help from."— Presentation transcript:

1 Climate forcing, adjustment and feedback Christopher S. Bretherton Atmospheric Sciences and Applied Mathematics University of Washington with help from Matt Wyant Photo courtesy Rob Wood Motivation: Mechanisms of PBL cloud response to climate change

2 The climate sensitivity problem 2xCO 2 IPCC models match 20C climate, but vary on 21C warming 3xCO 2 2.5- 4.3°C IPCC 2007 Aerosols partly cancel GHGs

3 Climate feedbacks: a simple view C dΔT/dt = N = G – λ -1 ΔT, λ = λ 0 -1 (1-f) G (2xCO 2 ) ~ 4 W m -2 λ 0 -1 ~ 3.3 W m -2 K -1 f ~ 0.6 ± 0.1 (water vapor+LR, snow/ice, clouds) C ~ 3.3x10 8 J m -2 K -1 for 100 m deep ocean mixed layer covering ¾ of the planet  ΔT eq = G/λ ~ 3 K t eq = C/λ ~ 8 yrs ΔCO 2 ΔTΔT Δatm Δsurf f

4 Complications to the simple view Multiple response timescales internal atmospheric adjustment (days-weeks) land surface physical adjustment (weeks-months) ocean mixed-layer (yrs-decades) biological/carbon-cycle (decades-100s yrs) deep ocean/thermohaline (100s-1000s yrs) ice sheets (100s-1000s yrs)  Scope of feedback analysis depends on the timescale GHGs and aerosols don’t just change climate through their effects on global average surface ΔT

5 Linear scaling of gross climate change with ΔT For a given model, many aspects of climate change do scale with ΔT in IPCC scenario runs. IPCC 2007

6 However, not all perturbations fit this mold Seasonal cycle (large changes in hemispheric T with little change in global-mean T) ENSO Aerosol forcing (mainly in NH, so induces hemispheric cooling anomaly)  Thus, even global-mean changes in clouds, rainfall, etc. may scale differently with ΔT for these perturbations than in greenhouse warming scenarios.

7 Example: Response to step increase in CO 2 Traditional AGCM climate sensitivity method: 1.Run AGCM to equilibrium over climatological SSTs 2.Calculate implied net energy flux (Qflux) into the ocean 3.Construct a slab ocean model with this Qflux and climatological ocean mixed layer depth 4.Suddenly double CO 2 and run AGCM+SOM to equilibrium (20-50 yrs). Mean surface air temperature increase ΔT eq is the climate sensitivity ΔT t Net Rad ΔT

8 Transient evolution of such runs also relevant ΔT G = log(CO 2 increase) slow CO 2 increase 2xCO 2 SOM

9 Fast response of clouds to radiative changes Transient behavior of coupled GCM runs in which CO 2 is suddenly doubled shows a quick response of the clouds before the climate warms which explains some of the ultimate 2xCO 2 cloud feedback. Quick increase in SWCF (less cloud) after 2xCO 2. Gregory and Webb 2008

10 Adjustment cartoon time years weeks AdjustmentTemperature feedback

11 Cloud adjustment to step 2xCO 2 is significant Suggests quick decrease in both low and (to lesser extent) high cloud. Fast adjustments are about 20% of equilibrated cloud response to 2xCO 2. After subtracting them out, the T-modulated cloud feedback remains positive in all models and exhibits somewhat reduced spread. Geographical pattern is fairly complex and model-dependent Physical mechanism? (Andrews and Forster 2008)

12  CO 2 cloud response in superparameterized GCM Superparameterization - a climate model with a small cloud-resolving (large-eddy simulation) model in place of the normal physical parameterizations in every grid column. Computationally expensive, but may simulate turbulent clouds (especially deep convection) more realistically. SP-CAM (Khairoutdinov and Randall 2005) uses 2D CRMs with 32x30 gridpoints, Δx = 4 km and Δz ~ 200 m in PBL. Investigate low cloud response to instantaneous 4xCO 2 increase with fixed SST.

13 4xCO 2 fixed SST experiment with SP-CAM 2½ year integrations are used with the first ½ year discarded...short, but results hold in each of the 2 years. Radiative Heating Cloud ΔSWCF = 0.7 W m -2 ∆4xCO 2 4xCO 2  ~10 W m -2 more LWdown at low cloud top.  Less PBL radiative cooling, less turbulence  Shallower inversion, less boundary layer cloud less PBL-top cooling LTS cold SST warm SST

14 …something we weren’t expecting… Land heats up due to enhanced greenhouse effect despite fixed SST

15 The result… with 4xCO 2 but fixed SST

16 Quantitatively… Over land: More rain, clouds, ascent Over ocean: Less rain, clouds, ascent Over full tropics: Less atmos. radiative cooling, thinner low cld

17 Conclusion CO 2 increase causes fast as well as temperature- mediated adjustment that significantly affect clouds and land/ocean interaction. A careful analysis of GHG feedbacks on temperature needs to account for this adjustment as part of the forcing. This appears to make cloud feedbacks less positive. In thinking about climate forcing and feedback it is critical to keep in mind the timescale of interest and whether a given control parameter (e.g. global mean surface ΔT) adequately characterizes the evolving system.

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19 Fixed Anvil Temperature (FAT) hypothesis Substantial clear-sky radiative cooling requires water vapor Upper tropospheric water vapor is temperature-limited. Clear-sky radiative cooling is weak for T < 200 K.  Convective anvil tops will occur near T = 200 K, regardless of surface temperature. Hartmann and Larson 2002 AR4 models, A1B scenario (Zelinka and Hartmann 2010)

20 Vertical cloud profile changes with  T s Kuang and Hartmann 2007: Radiative-convective equilibrium over fixed SST in a cloud-resolving model (CRM). Entire cloud profile above the freezing level rises 350 m/K SST when plotted vs. z but collapses when plotted vs. T. GCMs do similarly (Zelinka and Hartmann 2010).


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