© University of Reading [email protected] Chapman Conference on Atmospheric Water Vapor...

© University of Reading 2008 [email protected] Conference on

Atmospheric Water Vapor and Its Role in Climate

Tropospheric Water Vapour and the Hydrological Cycle

Richard Allan

University of Reading, UK



Tony Slingo1950-2008



How does water vapour impact climate change?

– Amount of warming– Changes in water cycle



A Satellite perspective



Spectral cooling rate (H2O, CO2, O3) Clough & Iacono (1995) JGR

K d-1 (cm-1)-1

MLS



Climate sensitivity and water vapour feedback = ─



Climate sensitivity and water vapour feedback

0.2 Wm-2%-1

= ─Kernals: Soden et al. (2008)




0.2 Wm-2%-1 7%K-1

= ─




0.2 Wm-2%-1 7%K-1

λBB~ -4σT3 ~ -3.2 Wm-2K-1

λWV~(0.2)(7)=1.4 Wm-2K-1

= ─

λWV+λBB~1.4 - 3.2 = -1.8 Wm-2K-1



• Low level moisture over the ocean seems to behave…

• Does moisture really vary with temperature at ~ 7%/K?

• Do models capture the essential relationships?

- Land, upper troposphere?

- Reanalyses, surface measurements or satellite data?

How does moisture respond to warming?



Does moisture rise at 7%/K over land?

Specific humidity trend correlation (left) and time series (right)

Willett et al. (2007) Nature; Willet et al. (2008) J Clim

But some contradictory results (e.g., Wang et al. (2008) GRL)

Land Ocean



Is moisture at higher levels constrained by Clausius Clapeyron?

Soden et al. (2005) Science

Moi

sten

ing

Trend in water vapour radiance channels: 1983-2004

Observations

Model

Constant RH model

Constant water vapour model



Is the mean state important?• Models appear to

overestimate water vapour– Pierce et al. (2006) GRL;

John and Soden (2006) GRL– But not for microwave data?

[Brogniez and Pierrehumbert (2007) GRL]

• This does not appear to affect feedback strength– Held and Soden (2006),

John and Soden (2006)• What about the

hydrological cycle?– Inaccurate mean state?

Pierce et al. (2006)

GRL



Soden et al. (2002) Science; Forster/Collins (2004) Clim Dyn; Harries/Futyan (2006) GRL

What time-scales do different processes operate on?



Bates and Jackson (2001) GRL

Trends in UTH (above)

Sensitivity of OLR to UTH (right)



Reduction in UTH with warming

Lindzen (1990) BAMS

Minschwaner et al. (2006) J Clim

Mitchell et al. (1987) QJRMS



Moistening processes: diurnal cycle (SEVIRI)

Condensation Evaporation

Convergence Divergence

DryingMoistening

Evaporation

UTH tendency

Divergence

Sohn et al.(2008)JGR

See also Soden et al. (2004) GRL



Evaporation cannot explain moistening

John and Soden (2006) GRL; Luo and Rossow (2004)

350

250

180

120

90

63

45

30

g m-3



Cloud feedback: a more complex problem

Non-trivial relationship between cloud and temperature

Response of cloud to warming is highly uncertain

• Depends on:– Type of cloud– Height of cloud– Time of day/year– Surface characteristics



Spread in cloud feedback in models appears to relate to tropical low altitude clouds

IPCC (2007), after Sandrine Bony and colleagues



Is cloud feedback an indirect forcing?

• • Clouds respond to – direct forcing from CO2

– Climate response to ∆SST

• • Does cloud feedback uncertainty stem from direct response rather than climate feedback response?

Andrews and Forster (2008) GRL (above); Gregory and Webb (2008) J Clim



How should precipitation respond to climate change?

Allen and Ingram (2002) Nature





Surface Temperature (K)

Models simulate robust response of clear-sky radiation to warming (~2 Wm-2K-1) and a resulting increase in precipitation to balance (~2%K-1) e.g., Allen & Ingram, 2002; Lambert & Webb (2008) GRL



• But moisture observed & predicted to increase at greater rate ~7%K-1

• Thus convective rainfall expected to increase at a faster rate than mean precipitation (e.g. Trenberth et al. 2003 BAMS)

1979-2002



Intensification of heaviest rainfall with warming

Allan and Soden (2008) Science



Contrasting precipitation response expectedP

reci

pita

tion

Heavy rain follows moisture (~7%/K)

Mean Precipitation linked to

radiation balance (~3%/K)

Light Precipitation (-?%/K)

Temperature e.g. see Held and Soden (2006) J. Clim



IPCC 2007 WGI

Mean projected precipitation changes



Contrasting precipitation response in ascending and descending portions of the tropical circulation

GPCP Models

ascent

descent

Allan and Soden (2007) GRL

Pre

cipi

tatio

n ch

ange

(m

m/d

ay)



Could changes in aerosol be driving recent changes in the hydrological cycle?

Wielicki et al. (2002) Science; Wong et al. (2006) J. Clim; Loeb et al. (2007) J. Clim



Unanswered questions

• How does UTH really respond to warming?• Do we understand the upper tropospheric moistening processes?• Is moisture really constrained by Clausius Clapeyron over land?• What time-scales do feedbacks operate on?• Apparent discrepancy between observed and simulated changes

in precipitation– Is the satellite data at fault?

– Are aerosol changes short-circuiting the hydrological cycle?

– Could model physics/resolution be inadequate?

• Could subtle changes in the boundary layer be coupled with decadal swings in the hydrological cycle?

• How do clouds respond to forcing and feedback including changes in water vapour?



Extra Slides



Can we use reanalyses?

• Global coverage

• All levels of the troposphere

• Changes in observing system: spurious longer-term variability



Surface longwave radiation and the hydrological cycle

Hartmann & Michelsen (1993) J Climate

Water vapour (mm) Sur

face

LW

(W

m-2)



Schematic showing effect of changes in water vapour on surface, top of atmosphere and atmospheric radiation budgets

Longwave radiative cooling

Surface

Top of atmosphere

Atmosphere

Tro

posp

here W

ater

vap

our

feed

back

Hyd

rolo

gica

l

cy

cle



Changes in precipitation: “the rich get richer”?

precip trends

0-30oN

Rainy season: wetter

Dry season: drier

Chou et al. (2007) GRL



Are mean precipitation and evaporation changing following Clausius Clapeyron (7%/K), larger than the model estimates

Yu and Weller (2007) BAMS

(Wentz et al. 2007, Science)



Conclusions

• Free troposphere humidity crucial for water vapour and cloud feedback

• Low-level water vapour crucial for hydrological cycle

• Is cloud feedback a small indirect forcing?

• Are observed changes in the hydrological cycle real and if so do they cast doubt on model forcings/physics?



Calculating Feedback: kernels

Shell et al. (2007) J Clim; Soden et al. (2008) J. Clim

Cle

ar-s

ky

A

ll-sk

y



Model reproduces water vapour feedback response to Pinatubo eruption

Soden et al. (2002) Science; Forster and Collins (2004) Clim Dyn



Timescales of feedbacks

Wat

er V

apou

r (m

m)

6.7

μm

T (

K)

Surface T

(K)

Harries and Futyan (2006) GRL



Radiative Impact of Cloud

• Most of the water in the atmosphere is invisible vapour– Clouds are like the tip of the iceberg

• Clouds are water vapour with attitude

• Strong interaction with longwave and shortwave radiation (emission, absorption, scattering)



Interanual Variability:Response of water vapour & clear-sky LW radiation at the surface and TOA in models, reanalyses & observations

Water vapour

Surface clear LW Clear-sky OLR



Quantifying Feedbacks

Climate Sensitivity parameter

+

Black body feedback

x denotes feedback variable, e.g. cloud, water vapour, ice-albedo, etc

≈Black body feedback ~ -3.8 Wm-2K-1 assuming T=255 K

(using GCMs ~ -3.2 Wm-2K-1)



2xCO2 response + water vapour feedback

= ─

3.7 = ─ (-3.2+1.4) ∆T; ∆T ~ 2 K

So water vapour feedback approximately doubles no feedback temperature response to doubling of CO2

Including feedbacks from temperature lapse rate (negative), ice albedo (positive) and clouds (positive), models produce a best estimate ∆T ~ 3 K



Observations and cloud feedback



Changes in cloud from

ISCCP

• Decadal changes in ISCCP cloud relate to viewing artifacts due to changes in geo-stationary satellite coverage

• Cloud thickness/cloud fraction compensation

e.g. Norris (2005) JGR; Evan et al. (2007) GRL

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