Cloud Feedback Katinka Nov 7,2011
description
Transcript of Cloud Feedback Katinka Nov 7,2011
![Page 1: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/1.jpg)
Cloud FeedbackKatinka
Nov 7,2011
*Photo taken by Paquita Zuidema in Maldives
![Page 2: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/2.jpg)
• Feedbacks
• How to estimate feedbacks
• On cloud changes: Thermodynamics & Dynamics
Outline:
![Page 3: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/3.jpg)
Forcing vs. Feedback:
Forcing = process external to the system
Feedback = process internal to the system
e.g.: CO2 is an “external” forcing of climate change, but CO2 “internal” variations have occurred naturally in past.
In climate models:
![Page 4: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/4.jpg)
RADIATIVE BALANCE AT TOA
G = ext. forcing (e.g. CO2, change in solar constant)
G = G(R(T))
Transient radiative imbalanceat TOA
Radiative damping(i.e. feedbacks)
Feedbacks:
![Page 5: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/5.jpg)
When the system returns to equilibrium:
Climate sensitivity parameter, i.e. FEEDBACKS(regulate radiative damping)
Climate Sensitivity:
Transient radiative imbalance at TOA
![Page 6: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/6.jpg)
Climate Sensitivity:equilibrium change in global mean surface temperature (DT) that results from a specified change in radiative forcing (DG)
+3.6(T+lapse rate)
-1.6 -0.4 -0.3 W m-2 K-1
+ 4 W m-2
λ > 0 -> NEGATIVE feedback
λ < 0 -> POSITIVE feedback
![Page 7: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/7.jpg)
Computing Climate Sensitivity (i.e. ΔT) from models:
Inverse method Forward method
In: ΔT (+2K/-2K)
AGCM (prescribed SST)
Out: ΔR
In: ΔR (2xCO2)
AOGCM
Out: ΔT
(Cess 88, Soden 04)
![Page 8: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/8.jpg)
1. CRF (cloud forcing analysis)
2. PRP (partial radiative perturbation)
3. Radiative Kernels
How to estimate feedbacks:
![Page 9: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/9.jpg)
1. CRF (cloud forcing analysis) *Refs: Cess JGR90, Cess JGR96, Bony JC06
Water vapor+sfc albedo+Temp.(i.e. doesn’t separate feedbacks)
Change in radiative impact of clouds
Major criticism: CRF can be negative, but cloud feedback positive, best e.g: *Bony JC06
Big upside: can be directly compared against observations (e.g. Bony GRL05)
![Page 10: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/10.jpg)
2. PRP (partial radiative perturbation) *Refs: Soden et al JC08, Soden et al JC04, Wetherald and Manabe JAS 88
F=OLRQ=SWμ=geographical position, time of the day, time of the year
Net TOA FLUX
The total perturbation can be written in terms of the PRP (partial radiative perturbations):
Feedback Parameter(for each variable X: w,T,c,a)
“offline” Radiative Transfer
Climate Model output
![Page 11: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/11.jpg)
“offline calculations” , i.e. radiative response (only radiation code):
The FB of each variable is estimated by changing only that variable in the radiation model and computing the resulting net perturbation at TOA -> all R(..) involve an offline radiative transfer simulation.
Feedback Parameter(for each variable X: w,T,c,a)
“offline” Radiative Transfer
Climate Model output
EXAMPLE (Soden JC04): Use “inverse method”, i.e. +/- 2 K exp.
CB -> from B = + 2K, all others are from A = – 2K note: need 2 GCM simulations
![Page 12: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/12.jpg)
Cloud FeedBack is calculated as a residual *Ref: Soden JC08
wB -> from B = + 2K, all others from A = – 2K 1. need 2 + 1 GCM simulations2. R has to be run for each time step
PRP:with decorrelation
(primes)
Radiative Kernel:
3. PRP evolves in Radiative Kernels:
-> perturbation at each level: doesn’t perturb correlations. Small compared to wB(t)-wA(t).
![Page 13: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/13.jpg)
Water Vapor Feedback using Kernels
Water Vapor Kernel (from RT code) Water Vapor Response to 2xCO2 (from GCM)
x
Water Vapor Feedback = Kernel x Response
=
WR
sdTdW
*B.Soden
![Page 14: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/14.jpg)
Cloud FeedBack is calculated as a residual *Ref: Soden JC08
Issue: Uncertainty in experiments with change in radiative forcing (e.g. CO2)… why not use CRF?
![Page 15: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/15.jpg)
R.K.
CRF
Clouds mask other FB
![Page 16: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/16.jpg)
W/m2/K/100 mb
Total sky
Clear sky
Water vapor Kernel (zonal mean annual mean)
What are the “masking” effect of clouds we need to correct for?
*Soden JC08
![Page 17: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/17.jpg)
Alternative to CF: “Adjusted” CRF *Ref: Soden JC08
dR at TOA can be written in two ways:
CLOUD FEEDBACK:
To be included in exp in which there are forcing changes
Corrections to masking effects of clouds on other FB
![Page 18: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/18.jpg)
*Soden JC08
![Page 19: Cloud Feedback Katinka Nov 7,2011](https://reader033.fdocuments.us/reader033/viewer/2022051518/568164f8550346895dd76612/html5/thumbnails/19.jpg)
References:
• Cess R.D. and G.L. Potter, 1988: A Methodology for Understanding and Intercomparing Atmospheric Climate Feedback Processes in General Circulation Models. J.Gehopys.Res.
• Cess R.D. et al., 1990: Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res.
• Cess R.D. et al., 1996: Cloud feedback in atmospheric general circulation models: An update. J.Geophys.Res.
• Soden B. et al. 2004: On the Use of Cloud Forcing to Estimate Cloud Feedback. Letters. J.Clim.
• Soden B. and I. Held, 2006: An Assessment of Climate Feedbacks in Coupled Ocean–Atmosphere Models. J.Clim.
• Soden B. et al. 2008: Quantifying Climate Feedbacks Using Radiative Kernels. J.Clim.• Bony S. et al.,2006: How Well Do We Understand and Evaluate Climate Change
Feedback Processes? Review article. J.Clim.