Dust Longwave Forcing from GERB and SEVIRI

Vincent Gimbert, H.E. Brindley, J.E. Harries

Imperial CollegeLondon

GIST 26, 03 May 2007, RAL, Abingdon

Thanks to Rainer Hollmann, Nicolas Clerbaux, Alessandro Ipe and Richard Allan, Andy Smith

Motivation

Use GERB and SEVIRI to measure TOA LW radiative forcing of Dust aerosols over the Sahara

Model Clear-sky TOA LW Radiances Using ECMWF Analyses to separate out effect of Dust from that of variable meteorology

Test the ECMWF model against observations and provide uncertainties in estimate of Dust forcing

Outline of Presentation

Method, measurements, model

March 2004: LW forcing of dust storm from GERB

Model comparison with Clearsky observations from GERB and SEVIRI IR Channels

Dust spectral forcing

Results from March 2006

Conclusion and future work

GERB LW radiance 200403 12 UTC

Strong OLR perturbation associated with dust event

Daytime SAFNWC Dust detection

RT modelling / GERB-SEVIRI data

Spectral Radiances modelled using MODTRAN 4 from 3.5 μm to ∞• Temperature, humidity, ozone from ECMWF analyses• Unity surface emissivity• 1 * 1 Degree resolution - 60/91 vertical levels• Spectral integration over appropriate instrument/channel response

Comparison with GERB and SEVIRI measurement• GERB L2 ARG• SEVIRI L1.5 Radiances (7 IR channels, 062,073,087,097,108,120,134)• 6-hourly 00:00, 06:00, 12:00, 18:00 (No GERB data at 00:00)• March 2004 and 2006

12:00 GERB - Model difference

GERB/model anomaly coincides with dust front on 3rd March 2004

Anomalies over clear sky as well

GERB and Model 12UTC through March

Cloud/dust free pixels

averages over dust

front region

(~10*10 deg square)

Over dust front (20040303) : LWRF ~ 20(+/- 3) W/m2

clearLLBias

BiasLLLWRF

LclearLdustLWRF

ECMWFGERB

ECMWFGERB

)(

• Model warm bias at 06 and 18

• Larger errors at 12 (larger Std Dev than 06 and 18)

• Use SEVIRI to test model...

Time dependence of clearsky errors

Time

Channel

00 UTC 06 UTC 12 UTC 18 UTC

IR_062

Mean (1σ), K

-1.67 (0.8)

-1.59 (0.6)

-1.51 (0.6)

-1.53 (0.6)

IR_073

Mean (1σ), K

0.95 (0.8) 0.95 (0.7) 2.05 (1.0) 1.34 (0.8)

SEVIRI/model Water Vapour channels WV 6.2 μm, High/mid atm WV 7.3μm, Mid/Low

Window channels

• Persistent model warm bias at night (σ~1-2K)• Daytime cold bias (~3K), σ~3.3K• Discrepancies over LAND• Same results from 10.8μm channel

The case of 8.7μm Channel

12.0μm

8.7μm

Night Day

• Strong SEVIRI/model differences in 8.7μm channel• Same pattern at all time steps• Surface emissivity?

• Assume emissivity (12.0μm)~1 and T(8.7 μm) ~T(12.0 μm)• Separate surface emissivity signal from 8.7 μm channel

Method useful for removing consistent biasNo a priori knowledge of surface spectral emissivity needed

Latitudinal dependence of Clearsky errors

• No dependance in WV channels

12.0μm: Surface Temperature 8.7μm: Emissivity + Tsurf

Dust LW Spectral forcing

No correction: unrealistic forcing, No uncertainties6.2um: non- physical7.3um: Negative at 12UTC…8.7um: Too high (emissivity bias)

March 2006 Dust event

EUMETSAT Dust RGB colour scheme

20060307 12UTC

EUMETSAT Dust RGB colour scheme

20060308 12UTC

March 2006 Dust event

Dust LW Spectral forcing

• Maximum forcing on 20060308• Similar spectral dependence as March 2004• Consistent with models

Conclusion and future work

Mean 200403 Dust storm OLR forcing: ~20W/m2 Diurnal cycle of Clear-sky GERB-model errors Good agreement in SEVIRI WV channels (small biases) Land Emissivity and Temperature Regional Biases in Window

Channels Very similar results for March 2004 and 2006: Dust Spectral Forcing

Future work: Validation at Niamey ARM site: Dust detection reliability Diurnal cycle of Tsurf Consistence of GERB-SEVIRI vs Model biases

Diurnal cycle of forcing

Daytime Conditional Bias

Model does not reproduce the range of GERB OLR at 12

Similar finding as Trigo and Viterbo (2003) with ECMWF model compared to MS7Window channel

We look at possible sources of errors at the surface