Mechanisms of land-atmosphere in the Sahel

Christopher Taylor

Centre for Ecology and Hydrology, Wallingford, U.K.

Richard Ellis, Phil Harris (CEH)

Doug Parker (Leeds)

Outline

• Soil moisture - rainfall feedbacks on daily timescales

• Satellite analysis

• Aircraft observations (AMMA)– A dry case– A wet case

Soil moisture – rainfall feedbacks

Koster et al, Science 2004

Shows where climate models sensitive to soil moisture

Large “coupling strength” implies soil moisture has significant impact on precipitation i.e. feedback possible

Large variations between models - models don’t represent basic processes well.

Do we have observations to judge models by?

Focus on West African “hotspot”

How strong should coupling be?

• What are mechanisms?

• Are our parameterisations suitable?

Daily Variability in Surface Fluxes in Sahel

• Evaporation limited by soil moisture so fluxes very sensitive to rainfall

• For several days after rain:

– large evaporation rates direct from soil

– low sensible heat flux– low surface temperature

Observations from savanna site at the start of the 1990 wet season

(Gash et al)

Does daily surface variability matter in a GCM?

Variations in surface fluxes on short timescales feed-back on

simulated rainfall.

Taylor and Clark, QJRMS (2001)

Power spectra of simulated rainfall in HadAM3

Impact of soil moisture on afternoon convection

Wet soil

12 June 2000 22:15

Met

eosa

t 7

TIR

In this single case, extent of convective system influenced by soil moisture…

Convection “avoids” wet soil

13 June

Pol

aris

atio

n ra

tio T

MI

Results from 108 cases

• Over 50% cases similar to example shown

• 33% less cloud over wet soil than nearby drier zones

• Initiation over wet soil strongly suppressed (2% cases)

• Suggests a negative soil moisture – precipitation feedback for initiating storms (cf Taylor and Lebel 1998)

• Potential mechanisms?

Cold cloud extent 13 June

Taylor and Ellis, GRL 2006

Aircraft Observations:African Monsoon Multidisciplinary Analyses

Special Observing Period during 2006 Wet Season

Focussed observations at multiple ground sites and with 5 aircraft, including NERC/Met Office BAe146

5 week deployment in Niamey, Niger

A dry case study: 1 August 2006

17:00 UTC 31 July

NiameyInitiating storm

Met

eosa

t th

erm

al in

fra-

red

00:00 UTC 1 Aug

12:00 UTC 1 Aug

Global View

Flight over storm track 18 hours later

Polarisation ratio anomalies from TRMMSpatial resolution ~ 50 km

Storm track

Flight track

1000 km

Cold (wet) Warm (dry)

Storm track

Red contours show overnight storm from cloud top temperature

Land Surface Temperature Anomalies

Extract mean diurnal cycle to obtain Land Surface Temperature Anomaly (LSTA)

500

km

White: no data (cloud or river)

Aircraft data within planetary boundary layer (PBL)

Wettest soils

Observed PBL temperature

Generally very good correlation between satellite surface data and PBL at fine scale: weak heating from wet soil>cool PBL

PBL temperature according to

ECMWF forecast model

Land surface temperature

anomaly (satellite)

PBL gradient due to vegetation feature

Aircraft data within planetary boundary layer (PBL)

Similar story for specific humidityHigh values above wet surface

Vertical profile data (dropsondes)

Pre

ssur

e

PBL twice as deep over dry soil as wet, and markedly drier and cooler.

More inhibition to convection over wet soil.In fact, no significant convection on this

afternoon along track.

X

X

X: lifting condensation level

Wet soil

Dry soil

An impact on low level winds?If surface heating contrasts large enough, might expect

a sea-breeze type response…i.e. convergence over dry (hot) surfaces

So surface gradients ARE strong enough to induce circulations.

Low level wind vectors

Convergence

ConvergenceDivergence

DivergenceConvergence

Analysis suggests that soil moisture patterns strong enough to induce sea-breeze type circulations. Can they cause further storms on more favourable days?

Land

sur

face

tem

pera

ture

ano

mal

y

A wet case study: 31 July 2006

Had similar flight planned previous afternoon…Very dry surface bounded by wet areas

wet

wet

dry

Storm initiation during flight

System developed very rapidly over dry soil as we approached.

Aircraft track

Storm initiation

Due to convective inhibition or convergent winds?

Clouds over dry soil

Early evolution of storm S

hadi

ng:

land

sur

face

tem

pera

ture

(re

d=dr

y)C

onto

urs:

clo

ud f

rom

vis

ible

cha

nnel

Storm develops along wet-dry surface contrastSignature of triggering by circulation rather than thermodynamic profiles

Current work in AMMA

• Quantifying surface fluxes (ALMIP)– Best available met forcing– Surface flux obs to calibrate models– Assimilation of LST data

• Feedbacks on convective initiation– Role of circulations and/or thermodynamic profiles

• MCS feedbacks– Sign and strength of feedback– Key space scales

• Intraseasonal feedbacks– Wet/dry spells

• Interannual memory– vegetation

• Observational diagnostics to test atmospheric models

Hombori Tondo (Mali) from UK BAe146.Photo: Doug Parker

Soil moisture and monsoon dynamics

• Intraseasonal variability in West African rainfall– Large-scale

wetting/drying 15 day cycle

• Cause and effect?

Satellite soil moistureSurface heating (W/m2)Atmospheric warming

T 925hPa (ECMWF)

Cause and effect: lagged relationshipsComposite data based on surface wetting

TMI wetness

Satellite cold cloud

ERA40 Temperature anomalies

Additional daytime cooling at 925hPa day 0 and day 1 - shows soil moisture leads to cooling in ECMWF analyses

Wet v Dry Spells• During wet spells, “cool

high” develops across Sahel

• Dynamic response to soil moisture consistent with forcing of variability

• Studentship with UEA looking at feedbacks in GCM

Shading: surface heatingContours: 925hPa Temperature

Convective scale feedbacks

• From observations, found tendency of rain within squall lines to be heavier in locations that have been recently wetted

• Linked to a positive feedback between soil moisture and rainfall at scales of only 10 - 15 km (Taylor and Lebel, MWR 1998)

20 July 1992 22 July 1992Rain gauge data from HAPEX-Sahel

Modelling Impact of Moisture Anomalies on Convection

Used cloud-resolving model (RAMS) to assess impact of humidity on cloud-scale dynamics within squall line. Run large ensembles.

Introduce wet patch of additional 1g/kg in lowest 1km

Strong impact of patch on simulated rainfall

10 km14 km

21 km

Impact sensitive to patch length scale

Unexpected sensitivity of feedbacks to length scale, convection sensitive to fine scale variability

(Clark et al 2003 QJRMS, 2004 JHMet)

Synoptic Scale Surface Variability

Screened TIR anomalies are well-organised at large scale (~1-2000 km) in N. Sahel

WarmCool

Synoptic Scale Surface Variability• Alternate warm (dry)

and cool (wet) surface anomalies travel westwards across the Sahel

Longitude

Day Bla

ck lin

es:

cold

clo

ud

Cool surface features appear after rain

TIR [C]

Impact of Synoptic Surface Variability on Atmosphere?

Degrees longitude

An

om

aly

Produced composite “hotspot” from 2000 wet season to assess feedback of surface on atmosphere.

1000 km

higher atmospheric temperatureslower surface pressurevortex develops

Southerlies

Northerlies

subsequent cold cloud (rainfall) modulated

Observational analyses suggest:

Taylor et al QJRMS 2005

Identifying Wet Soil From Satellite

• Several possibilities for detecting soil moisture from space

• Passive microwave (10.65 GHz) from TRMM Microwave Imager to infer wet soil (high evaporation) after recent rain

Rainfall (bars) and TRMM polarisation ratio (asterisks) in Banizoumbou region (Niger)

Soi

l dry

ing

afte

r ra

in

Rainfall data courtesy of T. Lebel (IRD)

Thermal Data

Meteosat Second Generation provides data every 15 mins at high spatial resolution (~3 km)

Land surface temperature products produced by LandSAF in near real time