The atmospheric hydrological cycle and climate feedbacks: recent advances Richard P. Allan Department of Meteorology, University of Reading Thanks to Brian.

The atmospheric hydrological cycle and climate feedbacks: recent advances

Richard P. AllanDepartment of Meteorology, University of Reading

Thanks to Brian Soden and Viju John

http://www.met.reading.ac.uk/~sgs02rpa r.p.allan@reading.ac.uk

Introduction

“Observational records and climate projections provide abundant evidence that freshwater resources are vulnerable and have the potential to be strongly impacted by climate change, with wide-ranging consequences for human societies and ecosystems.” IPCC (2008) Climate Change and Water

• Increased Precipitation• More Intense Rainfall• More droughts• Wet regions get wetter, dry

regions get drier?• Regional projections??

Precipitation Change (%)

Climate model projections (IPCC 2007)

Precipitation Intensity

Dry Days

Range of cloud feedback

Uncertainty in strength of cloud feedback

Water vapour and T-lapse rate

ALLCloud Surface reflection

Total range

Str

engt

h of

Fee

dbac

k (W

m-2/o C

)

Hawkins and Sutton (2010) Clim. Dyn.See IPCC (2007)

How should the water cycle respond to climate change?

See discussion in: Allen & Ingram (2002) Nature; Trenberth et al. (2003) BAMS

Hawkins and Sutton (2010) Clim. Dyn.

Allen and Ingram (2002) Nature

How should the water cycle respond to climate change?

7%/K 3%/K

NCAS-Climate Talk 15th January 2010 Trenberth et al. (2009) BAMS

Physical basis: energy balance

NCAS-Climate Talk 15th January 2010

Rad

iativ

e co

olin

g, c

lear

(W

m-2K

-1)

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 and Ingram (2002) Nature, Stephens & Ellis (2008) J. Clim

Allan (2009) J. Clim

NCAS-Climate Talk 15th January 2010

CC Wind Ts-To RHo

Muted Evaporation changes in models are explained by small changes in Boundary Layer:1) declining wind stress2) reduced surface temperature lapse rate (Ts-To)3) increased surface relative humidity (RHo)

Richter and Xie (2008) JGR

Evaporation

Current changes in tropical ocean column water vapour

Low level water vapour strongly constrained by Clausius Clapeyron relationship (~7%/K)

Changing observing systems applied to reanalyses cause spurious variability (e.g. ERA Interim)

John et al. (2009)

models

Wat

er V

apou

r (m

m)

Physical basis: water vapour

• Clausius-Clapeyron– Low-level water vapour (~7%/K)

– Intensification of rainfall– Moisture transport– Enhanced P-E patterns

See Held and Soden (2006) J Clim

Extreme PrecipitationPhysical basis: water vapour

1979-2002

• Low-level moisture rises with warming at ~7%/K due to Clausius Clapeyron

• Large-scale rainfall fuelled by moisture convergence– e.g. Trenberth et al. (2003) BAMS

Intensification of rainfall

• Extra latent heating:– Offsets some of extra condensation

/stabilises atmosphere? (O’Gorman and Schneider, 2009 PNAS)

– Invigorates storms? (Lenderink and van Meijgaard (2010) Environ. Res. Lett)

Contrasting precipitation response expected

Pre

cipi

tatio

n Heavy rain follows moisture (~7%/K)

Mean Precipitation linked to

radiation balance (~3%/K)

Light Precipitation (-?%/K)

Temperature For discussion: Trenberth et al. (2003) Bull. Americ. Meteorol. Soc; Allen & Ingram (2002) Nature

Models ΔP [IPCC 2007 WGI]

Is there a contrasting precipitation response in wet and dry regions?

Rainy season: wetter

Dry season: drier Chou et al. (2007) GRL

Precip trends, 0-30oN

The Rich Get Richer?

First argument:P ~ Mq.

So if P constrained to rise more slowly than q, this implies reduced M

P~Mq

Consequences: Circulation response

First argument:P ~ Mq.

So if P constrained to rise more slowly than q, this implies reduced M

Second argument:ω=Q/σ.

Subsidence (ω) induced by radiative cooling (Q) but the magnitude of ω depends on (Гd-Г) or static stability (σ).

If Г follows MALR increased σ. This offsets Q effect on ω.See Held & Soden (2006) and Zelinka & Hartmann (2010) JGR

P~Mq

Consequences: Circulation response

Models/observations achieve muted precipitation response by reducing strength of Walker circulation. Vecchi et al. (2006) Nature

P~Mq

Consequences: Circulation response

Pre

cip.

(%

)

Allan and Soden (2008) Science

Can we use observations to seek/confirm robust responses?

Tropical ocean precipitation

• dP/dSST:

GPCP: 10%/K (1988-2008)

AMIP: 3-11 %/K (1979-2001)

• dP/dt trend

GPCP: 1%/dec(1988-2008)

AMIP: 0.4-0.7%/dec(1979-2001)

(land+ocean)

SSM/I GPCP

Allan et al. (2010) Environ. Res. Lett.

Zhang et al. 2007 Nature

Detection of zonal trends over land

Contrasting precipitation response in wet and dry regions of the tropical circulation

Allan and Soden (2007); Allan et al. (2010) Environ. Res. Lett.

descent

ascentModelsObservations

Pre

cipi

tatio

n ch

ange

(%

)

Sensitivity to reanalysis dataset used to define wet/dry regions

Contrasting wet/dry precipitation responses

• Large uncertainty in magnitude of change: satellite datasets and models & time period

TRMM

GPCP Ascent Region Precipitation (mm/day)

John et al. (2009) GRL

• Robust response: wet regions become wetter at the expense of dry regions. Is this an artefact of the reanalyses?

Current trends in 30% wettest, 70% driest regions of tropical oceans

• Wet/dry trends remain– 1979-1987 GPCP

record may be suspect for dry region

– SSM/I dry region record: inhomogeneity 2000/01?

• GPCP trends 1988-2008

– Wet: 1.8%/decade– Dry: -2.6%/decade– Upper range of model

trend magnitudes

Models

DR

Y

WE

T

Allan et al. (2010) Environ. Res. Lett.

• Analyse daily rainfall over tropical oceans– SSM/I v6 satellite data, 1988-2008 (F08/11/13)– Climate model data (AMIP experiments)

• Create rainfall frequency distributions

• Calculate changes in the frequency of events in each intensity bin

• Does frequency of most intense rainfall rise with atmospheric warming?

Precipitation Extremes

Can we seek robust responses in precipitation extremes using satellite observations?

METHOD

Increases in the frequency of the heaviest rainfall with warming: daily data from models and microwave satellite data (SSM/I)

Reduced frequency Increased frequencyAllan and Soden (2008) Science; Allan et al. (2010) Environ. Res. Lett.

• Increase in intense rainfall with tropical ocean warming (close to Clausius Clapeyron)

• SSM/I satellite observations at upper range of model range

Turner and Slingo (2009) ASL: dependence on convection scheme?

Observational evidence of changes in intensity/duration (Zolina et al. 2010 GRL)

Links to physical mechanisms/relationships required (Haerter et al. 2010 GRL)

Yu and Weller (2007) BAMS

(Wentz et al. 2007, Science)

Are models underestimating current precipitation/evaporation responses?

• Could decadal fluctuations in atmospheric circulation be influencing current water cycle response?– Sohn and Park (2010) JGR

Walker circulation index (top) and sea level pressure anomalies (bottom) over equatorial Pacific (1948-2007)

Hadley circulation index over 15oS-30oN band

Could changes in aerosol influence decadal changes in the hydrological cycle? e.g. Wild et al. (2008) GRL

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

Mishchenko et al. (2007) Science

Andrews et al. (2009) J Climate

Is water cycle response sensitive to nature of radiative forcing?

How does the water cycle respond to ramp-down in CO2?

• CO2 forcing experiments

• Initial precip response supressed by CO2 forcing

• Stronger response after CO2 rampdown

HadCM3: Wu et al. (2010) GRL

CMIP3 coupled model ensemble mean: Andrews et al. (2010) Environ. Res. Lett.

Degree of hysteresis determined by forcing related fast responses and linked to ocean heat uptake

Forcing related fast responses

Andrews et al. (2010) GRL

Total Slow

• Surface/Atmospheric forcing determines “fast” adjustment of precipitation

• Robust slow response to T• Mechanisms described in Dong

et al. (2009) J. Clim

• CO2 physiological effect potentially substantial (Andrews et al. 2010 Clim. Dyn.; Dong et al. 2009 J. Clim)

• Hydrological Forcing:

HF=kdT-dAA-dSH

(Ming et al. 2010 GRL; also Andrews et al. 2010 GRL)

Pre

cip

itatio

n re

spo

nse

(%

/K)

One of the largest challenges remains improving predictability of

regional changes in the water cycle…Changes in circulation systems are crucial to regional changes in water resources and risk yet predictability is poor.

How will catchment-scale runoff and crucial local impacts and risk respond to warming?

What are the important land-surface and ocean-atmosphere feedbacks which determine the response?

Future work: Binning precipitation by regime

Vert

ical m

oti

on

(ω

) %

iles

ascen

t d

escen

t

Coldest Warmest

Precipitation (mm/day)

Warm convective

Sub tropics

*

* - mid-latitudes

Regime-dependent responses(a) P (mm/day); % area (b) Model–GPCP P (%) (c) 2080-99 – 1980-99 P (%/K); (d) ω

Vert

ical m

oti

on

(ω

)

perc

en

tile

s

ascen

t

descen

t

Models overestimate drizzle in tropics

Robust increases in precipitation for mid/high latitudes & convective tropics

Less rainfall in dry tropics. Reduced circulation.

• Global mean precipitation– Controlled by energy balance (~2-3%/K)– Water vapour and clear-sky radiative cooling

• Intense rainfall– Low-level moisture rises fuel intensification of rainfall (~7%/K)

• Wet/dry region responses– Contrasting wet/dry region responses (wet get wetter)– Moisture transport & water vapour/energy balance constraints

• Outstanding Issues– Regional responses – Aerosol and decadal variability– Links to Cloud Feedback– Observing System– Transient responses: fast adjustment to forcing

Conclusions

Extra Slides

A=0.4 (1-A)=0.6

dPw/dT=7%/K dPd/dT

dP/dT=3%/K

Assume wet region follows Clausius Clapeyron (7%/K) and mean precip follows radiation constraint (~3%/K)

Pw=6 mm/day Pd=1 mm/day

P=3 mm/day

Wet Dry

A is the wet region fractional area

P is precipitation

T is temperature

A=0.4 (1-A)=0.6

dPw/dT=7%/K dPd/dT

dP/dT=3%/K

Assume wet region follows Clausius Clapeyron (7%/K) and mean precip follows radiation constraint (~3%/K)

dP/dT= A(dPw/dT)+(1-A)(dPd/dT) dPd= (dP-AdPw)/(1-A)

Pw=6 mm/day Pd=1 mm/day

P=3 mm/day

Wet Dry

A Pw Pd dPd/dTs

(mm/day/K)

“

(%/K)

0.4

0.2

6

9

1

1.5

-0.1

-0.05

-10

-4.5

0.1 10.5 2.2 +0.02 +0.9

A is the wet region fractional area

P is precipitation

T is temperature

Trends in clear-sky radiation in coupled models

Clear-sky shortwave absorptionSurface net clear-sky longwave

Allan (2009) J. Clim

Precipitation in the Europe-Atlantic region (summer)

Dependence on NAO

Physical Basis: Moisture Transport

Cha

nge

in M

oist

ure

Tra

nspo

rt,

dF (

pg/d

ay)

If the flow field remains relatively constant, the moisture transport scales with low-level moisture.Model simulation

scaling

Held and Soden (2006) J Climate

Projected (top) and estimated (bottom)

changes in Precipitation minus Evaporation Δ(P-E)

Held and Soden (2006) J Climate

~

• Sample grid boxes:– 30% wettest– 70% driest

• Do wet/dry trends remain?

Avoid reanalyses in defining wet/dry regions

Allan et al. (2010) Environ. Res. Lett.