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
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”
Koster et al, Science 2004
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:
Observations from savanna site at
the start of the 1990 wet season
(Gash et al)
– large evaporation rates
direct from soil
– low sensible heat flux
– low surface temperature
Does daily surface variability matter in a
GCM?
Power spectra of simulated rainfall in HadAM3
Variations in surface fluxes on
short timescales feed-back on
simulated rainfall.
Taylor and Clark, QJRMS (2001)
Impact of soil moisture on afternoon
convection
12 June 2000 22:15
In this single case, extent of convective system influenced by soil
moisture…
Convection “avoids” wet soil
Meteosat 7 TIR
Polarisation ratio TMI
Wet soil
13 June
Results from 108 cases
Cold cloud extent 13 June
• 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)
Taylor and Ellis, GRL 2006
• Suggests a negative soil moisture –
precipitation feedback for initiating
storms (cf Taylor and Lebel 1998)
• Potential mechanisms?
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
Meteosat thermal infra-red
17:00 UTC 31 July
Initiating storm
00:00 UTC 1 Aug
12:00 UTC 1 Aug
Niamey
Global View
Flight over storm track 18 hours later
1000 km
Storm track
Flight track
Polarisation ratio anomalies from TRMM
Spatial resolution ~ 50 km
Land Surface Temperature Anomalies
500 km
Extract mean diurnal cycle to obtain Land Surface Temperature Anomaly (LSTA)
Red contours show
overnight storm from
cloud top temperature
Cold (wet)
Warm (dry)
White: no data (cloud or river)
Aircraft data within planetary boundary layer (PBL)
PBL temperature
according to
ECMWF forecast
model
Land surface
temperature
anomaly
(satellite)
Observed PBL
temperature
PBL gradient due to
vegetation feature
Wettest soils
Generally very good correlation between satellite surface data and
PBL at fine scale: weak heating from wet soil>cool PBL
Aircraft data within planetary boundary layer (PBL)
Similar story for specific humidity
High values above wet surface
Vertical profile data (dropsondes)
X
Pressure
Wet soil
Dry soil
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: lifting condensation level
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.
Land surface temperature anomaly
Low level wind vectors
Analysis suggests that soil moisture patterns strong enough to induce sea-breeze
type circulations. Can they cause further storms on more favourable days?
A wet case study: 31 July 2006
wet
dry
wet
Had similar flight planned previous afternoon…
Very dry surface bounded by wet areas
Storm initiation during flight
System developed very rapidly over dry soil as we approached.
Storm initiation
Clouds over dry soil
Due to convective inhibition or convergent winds?
Shading: land surface temperature (red=dry)
Contours: cloud from visible channel
Early evolution of storm
Storm develops along wet-dry surface contrast
Signature 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
Atmospheric
warming
Satellite
soil moisture
Surface
heating
(W/m2)
• Intraseasonal
variability in West
African rainfall
– Large-scale
wetting/drying 15 day
cycle
T 925hPa (ECMWF)
Cause and effect: lagged relationships
Composite data based on surface wetting
TMI wetness
ERA40 Temperature anomalies
Satellite cold cloud
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
Shading: surface heating
Contours: 925hPa Temperature
Convective
scale
feedbacks
Rain gauge data from HAPEX-Sahel
20 July 1992
22 July 1992
• 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)
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
10 km
14 km
21 km
Strong impact of patch
on simulated rainfall
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
Cool
Warm
Screened TIR anomalies are well-organised at large
scale (~1-2000 km) in N. Sahel
Synoptic Scale Surface Variability
Day
Black lines: cold cloud
•
Longitude
Alternate warm (dry) and
cool (wet) surface anomalies
travel westwards across the
Sahel
Cool surface features
appear after rain
Impact of Synoptic Surface
Variability on Atmosphere?
1000 km
Anomaly
Southerlies
Produced composite “hotspot”
from 2000 wet season to assess
feedback of surface on
atmosphere.
Observational analyses suggest:
TIR [C]
Northerlies
Degrees longitude
higher atmospheric
temperatures
lower surface pressure
vortex develops
subsequent cold cloud (rainfall)
modulated
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)
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