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.