lst and em retrievals from seviri onboard meteosat...

Ministério da Ciência, Tecnologia e Ensino Superior Instituto de Meteorologia, I. P. Rua C – Aeroporto de Lisboa 1749-077 Lisboa – Portugal Tel.: (351) 21 844 7000 Fax: (351) 21 840 2370 e-mail: [email protected] URL: http://www.meteo.pt

à frente do nosso tempo

LST and EM retrievals from SEVIRI onboard Meteosat:

Algorithms, uncertainties, and validation

Sandra C. Freitas, Isabel F. Trigo, José Bioucas Dias,

Frank Göttsche, Folke Olesen



The LandS AF

Land S urfac e E mis s ivity

A lg orithm & E rrors

Land S urfac e Temperature

A lg orithm & E rrors

In-s itu Va lidation

LS T & LS E Produc t C harac teris tic s

Outline



AIM → Develop techniques that allow an effective use of MSG and EPS data related to:

• LAND

• LAND-ATMOSPHERE Interactions

• BIOSPHERIC Applications

Provide Products

+

User Support

FMI

LandSAF



Surface Radiation Budget

LST ↓ LongWave FluxAlbedo ↓ ShortWave Flux

Surface Water Balance

Snow Cover

Evapotranspiration

Vegetation

Fraction Veg Cover

LAI

FAPAR

Wild Fires

Fire Detection

Fire Radiative Power

Fire Risk (Europe)

SEVIRI/MeteosatAVHRR, ASCAT/MetOp

LandSAF - Products



02 03 04 05 06 07 08 10 11 12 13 14 15 16 17 18 19 20010099

Meteosat-8 (MSG-1)

Meteosat-10 (MSG-3)

MetOp-BMeteosat-11

(MSG-4) MTG-1

MetOp-C

Meteosat-9 (MSG-2)

MetOp-A

Initial Operations Phase Feb 2005

Continuous Development & Operations PhaseMar 2007

Chronogram

LandSAF


à frente do nosso tempoLSE – Algorithm

Fraction of Vegetation Cover

)1( FVCFVC bgvegeff −+= εεε

Vegetation Cover Method [Caselles et al.]

Effective LSE →

Trigo, I. F. et al. (2008) in IEEE Trans. Geosci. Remote Sens., 46.

)1(4 FVCFVCdd eff −= εε

• Each IR channel / Broad Band

• Each Land-Cover Classes (IGBP classification)

• Using spectral library values + SEVIRI response functions

Associated Uncertainties →

Excess emissivity due to multiple internal reflections

Simplification of equation


à frente do nosso tempoLSE – Algorithm

Trigo, I. F. et al. (2008) in IEEE Trans. Geosci. Remote Sens., 46.

Error Bars

( ) ( )( ) ( )( )[ ] 212222 1 effbgvegbgvegeff dFVCFVCFVC εδεεδεδεδε +−+−+=

Vegetation / baresoil variability within each Land-Cover class

FVC Uncertainty

Em

issi

vity

[.]

FVC=0 FVC=0.7



Wavelength [µm]

Split-Window

Channels

SEVIRI channels & LST

Desert Areas

Evergreen Forest

High variability of EM

Solar Contamination



• Generalised Split-Window → 10.8µ m and 12.0µ m

Trained using CLEAR SKY synthetic SEVIRI/MSG data

LST - Algorithm

CTT

BBBTT

AAALST +−∆+−+++∆+−+=2

)1

(2

)1

( 0.128.102321

0.128.102321 ε

εε

εε

εε

ε

ECMWF fcGSW parameters depend on:

1. total column water vapour2. viewing angle

( )0.128.10 __2

1IRIR LSELSE +=ε

LST depends explicitly on LSE IR10.8 & IR12.0:

0.128.10 __ IRIR LSELSE −=∆ε



4

2

0

-2

-4

4

2

0

-2

-4

4

2

0

-2

-4LS

T_E

rror

s (K

)

~ NADIR Zenith Ang ~ 40º Zenith Ang ~ 75º

0 1.5 3 4.5 (cm) 0 1.5 3 4.5 (cm) 0 1.5 3 4.5 (cm)

TCWV

Algorithm uncertainty increases with view angle & water vapour, i.e., with optical path.

LST – Algorithm Uncertainty

• Generalised Split-Window

Verified against independent dataset ( ~ 15 700 profiles).

• Assuming well known inputs ↔ without errors



Errors Bars

22

2

2

2

2 LSTf

X

fS

j jX

i iLST ji

∆+

∂∂+

∂∂= ∑∑ θσ

θσ

LST – Error Propagation

Implicit input variables↓

TCWV (uncertainty on ECMWF fc) & View angle

Algorithm uncertainty↓

Retrieval conditions

Explicit input variables↓

Sensor noise & Emissivity



22

2

2

2

2 LSTf

X

fS

j jX

i iLST ji

∆+

∂∂+

∂∂= ∑∑ θσ

θσ

EMISSIVITY

LST Error (K)

SENSOR NOISE

LST Error (K)

LST – Error Propagation

Errors Bars

WATER VAPOUR

LST Error (K)

DRY

MOIST


à frente do nosso tempoSEVIRI LST vs In-situ data

Validation Site

Gobabeb – Namibia

- Homogeneous & dry region

- large gravel plains

CErrorBar

CRMSEo

o

9.2

1.1

==

Sep 2008

CErrorBar

CRMSEo

o

7.2

4.1

==

Nov 2008

CErrorBar

CRMSEo

o

5.2

1.2

==

Jan 2009

CErrorBar

CRMSEo

o

4.2

7.1

==

Mar 2009

0 20 40 60

SEVIRI LST (°C)

60

40

20

0

In-s

itu

LS

T (

°C)

0 20 40 60

SEVIRI LST (°C)

60

40

20

0

In-s

itu

LS

T (

°C)

RMSE < Monthly Average of ErrorBar

Main source of errors:

uncertainty on bare ground Emissivity

Higher Discrepancies

SEVIRI LST << In-situ LST

↑Clouds Contamination or

Shadows



Maskout (SLST > 4K)

LST LST Error Bars

LST - Product Characteristics

Dry regions & ↑ uncertainty on EM

Moist regions &/or ↑ View Angle

Good coverage↑ View Angle

↓ Water Vapour


à frente do nosso tempoLST - Product Characteristics

Dissemination via Eumetcast and Web

Generation Frequency - 15 min

clear sky pixels ...

over land ...

Available since

Europe – Feb 2005

Full disk – Jul 2005

http://landsaf.meteo.pt

LST LST Error Bars



EM 3.9µm

EM 10.8µm

EM 8.7µm

EM 12.0µmEM 3 – 14µm

Dissemination upon request

Generation Frequency – daily

LSE & Error Bars

over land ...

Available since Jan 2008

LSE – Product Characteristics


lst and em retrievals from seviri onboard meteosat...

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