© imperial college londonpage 1 estimating the saharan dust loading over a west african surface...

© Imperial College London

Estimating the Saharan dust loading over a west African surface site

GIST 26: May 2007


Outline

• Cloud and dust detection tools over land• Dust loading estimation

Existing methodologiesAccounting for meteorology

• Potential for direct radiative effect estimation• Caveats


Cloud, dust or clear?

For starters:Cloud

Combination of NWCSAF and RMIB cloud flagsDust

NWCSAF dust flag


Performance:

1. Assessed visually ‘by eye’ : subjective

2. Assessed through comparison with AERONET sites. If an AERONET retrieval has been made within 15 minutes of SEVIRI observation, site is assumed clear or ‘dusty’


Original NWC tests Blue: NWC cloud

8th March 2006: 1200 UTC

Red: RMIB cloud

Yellow: NWC dust


8th March 2006: 1200 UTC

10.8 m – 3.9 m test removed (cloud)

10.8 m – 12.0 m threshold made dependent on total column water vapour (dust)

RAE

DK AGBZ

IERDMN

DJ


SITE Lat/Lon Original (%) New (%)Agoufou 15.3 N, 1.5 W 77.2 77.2

Banizoumbou 13.5 N, 2.7 E 75.8 76.8

DMN Maine Soroa

13.2 N, 12.0 E 81.8 81.8

IER Cinzana 13.3 N, 5.9 W 74.4 87.8

Ras El Ain 31.7 N, 7.6 W 32.5 77.5

Dakar 14.4 N,17.0 W 71.0 87.0

D’jougou 9.8 N, 1.6 E 43.7 73.2

Successful classification

AERONET comparisons:

Total of 577 observations (4 months of data). 1200 UTC only


Dust Quantification

• Using visible info: problematic over desert

• Using IR info: better contrast (note time dep.) but dust properties poorly known

• BUT, previous attempts made with Meteosat IR channel: IDDI (Legrand et al.)• Determines a clear-sky reference image and relates (cloud-free) deviations from this to dust amount

• Main assumption - unchanging atmospheric conditions from reference state over time-window


Can we use a similar approach but take changing meteorology into account?

• Focus on one AERONET site (Banizoumbou, Niger), and one time-slot, 1200 UTC

• Meteorology from ECMWF analyses interpolated to site location

• Points only retained if identified as not cloudy or dusty (NWC and RMIB flags)

• Analysis performed through March-June 2006


Can we use a similar approach but take changing meteorology into account?

• ‘Clear-sky’ points identified using maximum TB108 value through a rolling time-window of set length TB108max

• Tsfc and TCWV values from ECMWF analyses retained for each point analysed

• Clear-sky values ‘corrected’ to the conditions on any given day using:

TB108clr = c1Tsfc + c2TCWV

Only requires relative variation in Tsfc and TCWV to be correct, not absolute values


Optimal window length?



Suggests site is never ‘clear’ and that a window of > 14 days is required

14 day window



28 day window


Fitting TB108clr

Perfect knowledge of Tsfc, TCWV

1 K (5 %) random error distribution applied to Tsfc (TCWV) values

Nadir view


ECMWF reliability?

ECMWF extracted Tsfc, and AMF auxiliary site air surface temperature values

Correlation = 0.85

ECMWF extracted TCWV, and retrieved values from MWR at main AMF site

Correlation = 0.98


Results

Dust signal, d = (TB108max+TB108clr) – TB108

Original: correlation = 0.67, rms = 0.36 Corrected: correlation = 0.88, rms = 0.23

28 day rolling window period


Estimating corresponding radiative effect…

• Could be done using identical approach? Use TB108max as a guide to identify ‘clear-sky’ OLR from GERB

• Include vertical information on temperature and water vapour content through deep layer relative humidities

• ‘Clear-sky’ OLR values ‘corrected’ to the conditions on any given day using:

OLRclr = c1Tsfc + c2ln(UTH/UTHmax) + c3 ln(LTH/LTHmax)

• Direct radiative effect of dust given by:

DRE = (OLRmax+ OLRclr) – OLR


For Banizoumbou

‘Correcting’ the ‘clear-sky’ OLR to account for changes in surface temperature and relative humidity isolates the dust effect on the OLR.

Essentially same idea as calculating clear sky OLR explicitly and subtracting from ‘dusty’ observation (see Vincent’s talk), but removes need for absolute accuracy in profiles etc. assuming relative variation is correct.

Direct radiative effect:

17 ± 5 W m-2 per unit 067


Conclusions/Caveats

Encouraging results over the sample site – what happens at other locations? Preliminary work suggests that if the surface type is similar (i.e. arid/semi-arid), the correlation between TB108 and aerosol optical depth is always improved with a correction applied. However this requires further detailed corroboration.

Issues:

Assessing the quality of ECMWF (or alternative) analyses in data sparse desert regions (or over other AERONET sites)

How to extend in time – quality of cloud/dust detection schemes/ availability of meteorological data/size of signal

Variations in dust layer height, surface emissivity, and …?

Quality of AERONET retrievals themselves?


Other sites? - preliminary

SITE No of points

range Original Corrected

Agoufou 34 0.15 – 4.08 0.87 0.91

Dakar 54 0.18 – 1.03 0.62 0.67

D’jougou 16 0.22 – 1.10 -0.33 -0.14

DMN Maine Soroa

29 0.22 – 4.05 0.79 0.83

IER Cinzana

40 0.20 – 1.85 0.46 0.56

Ras El Ain 27 0.06 – 0.69 0.22 0.20

© imperial college londonpage 1 estimating the saharan dust loading over a west african surface...

Documents