cloud feedback katinka nov 7,2011 *photo taken by paquita zuidema in maldives
TRANSCRIPT
Cloud FeedbackKatinka
Nov 7,2011
*Photo taken by Paquita Zuidema in Maldives
• Feedbacks
• How to estimate feedbacks
• On cloud changes: Thermodynamics & Dynamics
Outline:
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:
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:
When the system returns to equilibrium:
Climate sensitivity parameter, i.e. FEEDBACKS(regulate radiative damping)
Climate Sensitivity:
Transient radiative imbalance at TOA
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
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)
1. CRF (cloud forcing analysis)
2. PRP (partial radiative perturbation)
3. Radiative Kernels
How to estimate feedbacks:
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)
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
“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
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).
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
=
W
R
sdT
dW
*B.Soden
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?
R.K.
CRF
Clouds mask other FB
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
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
*Soden JC08
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.