Key ingredients in global hydrological response to external forcing
Response to warming
=> Increased horizontal moisture fluxes
=> Poleward expansion of the subtropics
Response to differential warming of the 2 hemispheres
=> tropical rainbelts move to warmer hemisphere
Percentage change in precipitation by end of 21st century:
PCMDI-AR4 archive
White areas =>
less than two thirds of the models agree on the sign of the change
PCMDI/IPCC
% increase in midlatitude maximum in poleward
flux of vapor vs global mean temperature
Precipitation and evaporation
“Aqua_planet” climate model
(no seasons, no land surface)
Instantaneous precip (lat,lon)
Time means
One can see effects of poleward shift of midlatitude circulation
And increase(!) in strength of Hadley cell
Equilibrium 2x
21st century A1B
20th century
r2=0.72
r2=0.85
Sarah Kang, Princeton
Aqua planet/slab ocean
Model A: Frierson et al 2006 -- idealized moist GCM
(no clouds -- water water vapor feedback)
Model B: AM2
Idealized GCM with different convection schemes
A parameter in the convection scheme
is varied continuously in each model
Idealized GCM: Modified Betts-Miller
relative humidity to which one relaxes
when convecting
AM2: Relaxed Arakawa Schubert
minimum allowed entrainment rate
Compensation at equator
AM2
Idealized GCM
AM2
AM2
IGCM
IGCM
IGCM
AM2
For the idealized GCM:
A simple energy balance model with
diffusion of moist static energy,
fitting the diffusivity to the symmetric control,
predicts compensation of 20-30%
The tropical precipitation response is determined by
1) The degree of compensation
2) The gross moist stability
Increasing RH decreases gross moist stability but not
compensation
Solid: idealized GCM precip response at 7S
Dashed: fit assuming degree of compensation
and gross moist stability
Increasing
RH
Fraction of rain in ITCZ that falls as “large-scale” precip in AM2
Latitude of precip max
=> Interesting benchmark for GCMs
Compensation at equator
In AM2
Degree of compensation strongly dependent on
Entrainment limiter
Why?
Cloud feedback and water vapor feedback
Single realization of CM2
(greenhouse gases; aerosols, solar, volcanoes, land use)
Mean of 8-member ensemble
Range of SRES scenarios
Sahel summer rain: (1980-2000) minus (1960-1940)
(mm/month)
8 member
ensemble
Observed annual mean
precipitation trend 1950-2000
Simulated annual mean
precipitation trend in CM2 1950-2000
+2K SST perturbation: annual mean precip
GFDL
CM2
NCAR
CCSM
QUMP: 129 different mixed layer models
(courtesy of Matthew Collins, Hadley Center)
% Sahel precip response to 2xCO2
CM2.0
Ind
NA
Regress: P(%) = I * Ind + N * NA
= U * Ind + N * (NA – Ind)
(U=I–N)
Ind => Stabilization of troposphere?
NA => ITCZ displacement? Moisture supply?
Regressing observed rainfall vs observed Ind and NA =>
P = - 0.12 Ind + 0.38 (NA - Ind)
Observed evolution of Ind and NA - Ind, 11yr running means
1954
1940
1919
1975
1985
SW override experiments (Jian Lu)
Want to study how change in absorbed SW at surface affects precip
But: take two realizations of same model and override absorbed SW
of one with the absorbed SW from the other => big difference
So: change in precip dP due to 2K increase in SST =
dP due to change in SST with fixed uncorrelated SW (small)
+dP due to change in uncorrelated SW
(wrong sign)
+dP due to difference in effects of correlation at different SSTs
+ dSST; fixed uncorr SW
+ Decorrelation at 2K
+ d(uncorr SW); fixed SST
- Decorrelation in cntrl