IPCC Workshop on Climate Sensitivity, Paris, July 2004 Exploiting observations of water vapour to...

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IPCC Workshop on Climate Sensitivity, Paris, July 2004

                                                                              

Exploiting observations of water vapour to investigate simulations of water vapour

feedback processes

Richard Allan, Tony SlingoEnvironmental Systems Science Centre, University of Reading

Mark RingerHadley Centre, Met Office

IPCC Workshop on Climate Sensitivity, Paris, July 2004

INTRODUCTION

– How does water (vapour/liquid/ice) respond to global warming?» Cruicial for Climate Sensitivity

– Direct feedback: water vapour» Fundamental test of models

» Can we determine water vapour feedback from observations of present day climate?

» Can we use reanalyses?

» do results link into present day changes in cloudiness?

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Previous studies

Observational determination of water vapour feedback (e.g. Raval and Ramanathan 1989; Cess 1989; Soden et al. 2002; Forster & Collins 2004)

Theoretical/ Modelling studies

(e.g. Manabe and Wetherald 1967; Held and Soden 2000; Ingram 2002, Minschwaner and Dessler 2004)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Climate sensitivity

Ts~Q,

=-1/(BB +WV ++Cld+….),

WV~-(OLR/wv)(wv/Ts)

WV Cld

Theory, Measurement

Observations

IPCC Workshop on Climate Sensitivity, Paris, July 2004

OLRc/wv

theoretical calculations

IPCC Workshop on Climate Sensitivity, Paris, July 2004

OLR Sensitivity to Water Vapour

IPCC Workshop on Climate Sensitivity, Paris, July 2004

wv/Ts

Theoretical basis (Clausius Clapeyron) wv/Ts ~ 6 - 7.5%K-1 (Wentz&Schabel

2000)

Can only measure dwv/dTs

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Interannual variability of Column Water vapour (Allan et al. 2003, QJRMS, p.3371)

1980 1985 1990 1995 See also Soden (2000) J.Clim 13

SST

CWV

IPCC Workshop on Climate Sensitivity, Paris, July 2004

CWV Sensitivity to SST

dCWV/dTs = 3.5 kgm-2 K-1 for HadAM3 and Satellite Microwave Observations (SMMR, SSM/I) over tropical oceans

Corresponds to ~9%K-1 in agreement with Wentz & Schabel (2000) who analysed observed trends

But what about moisture away from the marine Boundary Layer?

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Can we use reanalyses?

Reanalyses are currently unsuitable for detection of subtle trends associated with water vapour feedbacksAllan et al. 2004, JGR, accepted

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Observations of clear-sky OLR and the greenhouse

parameter

Clear-sky OLR sensitive to Ts and RH dOLRc/dTs as proxy for water vapour

feedback e.g. Cess et al. (1990) – agreement

between climate model dOLRc/dTs

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Observed and modelled changes in OLRc: ENSO

Soden (2000): ERBS vs AMIP multi model ensemble

– Tropics, AMIP I 2

0

-2 1983 1985 1987 1989

dOLRc

(Wm-2)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Interannual monthly anomalies: tropical oceans

HadAM3 vs ERBS, ScaRaB and CERES

dga/dTs ~ 4 x 10-3 K-1 Raval and Ramanathan (1989) get ~3.4x10-3 K-1 spatially

ga=1-(OLRc/Ts4)

(Allan et al. 2003, QJRMS, p.3371)

1980 1985 1990 1995

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Does dOLRc/dTs indicate consistent water vapour

feedback?

Consider GFDL & HadAM3 AMIP experiments

Interannual variability

dOLRc/dTs ~ 2 Wm-2 K-1

BUT: differing height dependent Temperature and water vapour response

– (Allan, Ramaswamy, Slingo, JGR 2002)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Does dOLRc/dTs~2 Wm-2 K-1 indicate consistent water vapour

feedback?

Allan et al. 2002, JGR, 107(D17), 4329.

HadAM3

GFDL

dTa(p)/dTs dq(p)/dTs

HadAM3

GFDL

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Water vapour / T-lapse rate

Compensation between water vapour and temperature lapse rate feedback in models

– e.g. Colman (2003)

Sensitivity to convective parametrizations?

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Relative Humidity Feedback

(include main component of WV into BB ?)

Ts~Q,

=-1/(BB +RH +Cld+….),

RH~-(OLR/RH)(wv/RH)

BB: constant RH,

Theory, Measurement

Observations

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Evaluation of upper tropospheric humidity feedback in HadAM3

6.7 m cloud cleared radiance sensitive to upper tropospheric Relative Humidity

Explicitly simulate 6.7 m radiance in HadAM3

Modified “satellite-like” clear-sky diagnostics

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Sensitivity of OLRc to UTH

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Interannual monthly anomalies of 6.7 micron radiance: HadAM3 vs HIRS (tropical

oceans)

(Allan et al. 2003, QJRMS, p.3371)

Small changes in T_6.7 (or RH) in model and obs (dUTH/dTs ~ 0 ?)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

(+additional forcings)

(Allan et al. 2003, QJRMS, p.3371)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Small changes in RH but apparently larger changes in tropical cloudiness? (Wielicki et al, 2002)

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Following: Wielicki et al. (2002); Allan & Slingo (2002)

+Altitude and orbit corrections (40S-40N)

Clear LW

LW

SW

IPCC Workshop on Climate Sensitivity, Paris, July 2004

- Even considering the latest corrections to the ERBS WFOV data, models still appear to underestimate the variation of tropical mean cloudiness

- This is despite the apparent agreement between models and observations that tropical mean Relative Humidity varies only slightly on a decadal time-scale

IPCC Workshop on Climate Sensitivity, Paris, July 2004

Summary reanalyses not yet suitable for analysis of climate sensitivity Climate model captures:

– low-level water vapour changes

» Sensitivity: dCWV/dTs~3.5 kgm-2 K-1

– Decadal variation in clear-sky OLR

» Sensitivity: dOLRc/dTs~2 Wm-2 K-1

– Small decadal changes in free-tropospheric RH

» Sensitivity: dOLRc/dRH ~ – 0.5 to –1 Wm-2 %-1

» dRH/dTs ~ 0 % K-1

– But satellite data suggests larger variation in radiation budget due to cloud compared to models