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OPERATIONAL VICARIOUS CALIBRATION OF MFG/MVIRI AND MSG/SEVIRI SOLAR CHANNELS PowerPoint Presentation
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OPERATIONAL VICARIOUS CALIBRATION OF MFG/MVIRI AND MSG/SEVIRI SOLAR CHANNELS. Y. Govaerts. yves.govaerts@eumetsat.int EUMETSAT : www.eumetsat.int European Organization for the Exploitation of Meteorological Satellites. GLOBAL SPACE-BASED INTER-CALIBRATION SYSTEM (GSICS)

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slide1

OPERATIONAL VICARIOUS CALIBRATION OF MFG/MVIRI AND MSG/SEVIRI SOLAR CHANNELS

Y. Govaerts

yves.govaerts@eumetsat.int

EUMETSAT : www.eumetsat.int

European Organization for the Exploitation of Meteorological Satellites

GLOBAL SPACE-BASED INTER-CALIBRATION SYSTEM (GSICS)

1st Meeting of GSICS Data Working Group (GDWG-I) and

2nd Meeting of GSICS Research Working Group (GRWG-II)

12-14 June 2007

slide2

OUTLINE

  • Calibration algorithm / quality indicator
  • Accuracy assessment
  • Meteosat First Generation (MVIRI) results
  • Meteosat Second Generation (SEVIRI) results
  • Conclusions
slide3

METEOSAT MISSION STATUS

75

80

85

90

95

00

05

10

15

Met-1

Met-2

Met-3

Met-4

Met-5

0

63

E

Met-6

RAPID SCAN

Met-7

Met-8

Met-9

Met-10

Met-11

Pre-operational

VIS 6 bits

Operational

VIS 8 bits

MSG

10 bits

25 years of archive

+40 years of data

slide4

BACKGROUND

  • No 0nboard calibration
  • Theindependent calibration referencerelies onsimulated TOA radiancesgenerated in the 0.3 - 1.8 µm interval over bright desert and sea targets (only forconsistency check).
  • The characteristics of bright deserts are:
    • radiometrically stable+
    • limited atmospheric effects+
    • no good surface characterisation–
    • (work performed prior to 2000, ie, TERRA/ENVISAT era)

Govaerts, Y.M., and Clerici, M. (2004) Evaluation of radiative transfer simulations over bright desert calibration sites, IEEE Transactions on Geoscience and Remote Sensing, 42, 176--187.

Govaerts, Y.M., Clerici, M., and Clerbaux, N. (2004) Operational Calibration of the Meteosat Radiometer VIS Band, IEEE Transactions on Geoscience and Remote Sensing, 42, 1900-1914.

background
BACKGROUND

Calibration target location

Desert targets X

Sea search areas 

bright desert target description
BRIGHT DESERT TARGET DESCRIPTION
  • Each target is characterised by 6 state variables p:
  • 3 state variables () of the surface BRF model (Hapke)
  • Total aerosol amount (TOMS AI, AERONET)
  • Total column water vapour (ECMWF)
  • Total column ozone (TOMS)
  • Each variable is estimated with an associated error p.
slide8

BRIGHT DESERT TARGET DESCRIPTION

POLDER observations

ATSR2 observations

Bright sandstone spectra from the ASTER spectral data base

slide9

BRIGHT DESERT TARGET DESCRIPTION

Example of surface BRF over one target

slide10

BRIGHT DESERT TARGET DESCRIPTION

Simulated spectral radiance over one target

slide11

BRIGHT DESERT TARGET DESCRIPTION

Error contribution of each parameter over one desert target

Atmosphere

Surface

principle 1
PRINCIPLE (1)
  • Operational vicarious calibration method for MFG and MSG solar channels based on simulated radiances over stable bright desert targets and sea surfaces for verification purposes;
  • Many observations are used to reduce non-systematic errors;
  • Includes complex quality control mechanism to assess the reliability of the results;
  • Provides an estimate of the derived calibration coefficient uncertainty.
slide13

PRINCIPLE (2)

Algorithm overview

(Meteosat)

SEVIRI

L1.5/2.0

5-10 days

of Data

ECMWF

CLIMATE

Target

Identification

Pixel

Extraction

RTM

Bright stable desert targets

Sea surfaces (verification)

QC

Calibration

QI

principle 3

Rd

Rs

K0

Ks

Kd

PRINCIPLE (3)

If the response of the instrument is linear and the characterisation of the spectral response () accurate,the estimated calibration coefficients Cf should be the same over different target types, whatever the spectral shape of R()

Desert

Sea

principle 4

SIM. RADIANCE

K’0

K0

COUNT

PRINCIPLE (4)

Used of the daily cycle variations to retrieve the offset value

Same viewing angle, different illumination angles

slide16

VERIFICATION (1)

Desert target evaluation concept

Calibration estimation is based on the comparison between calibrated observations acquired by polar orbiting instruments and simulation of these observations.

p, p

p, p

Simulation

Observation

slide17

VERIFICATION (2)

Spectral bands

Spectral response of the radiometric bands used in the comparion.

SEVIRI ATSR-2SeaWiFSMERISVGT

slide18

VERIFICATION (3)

Comparison between observation and simulation

Monthly mean relative bias averaged over all targets:

Relative bias

Bias error

Monthly mean

weighted relative bias

slide19

VERIFICATION (3)

Monthly mean relative difference (bias + std. dev.) between simulations and observations over all targets

slide20
The accuracy of the calibration reference (i.e., simulated radiances) is estimated with the comparison between calibrated observations acquired by polar orbiting instruments and simulation of these observations.

VERIFICATION (4)

Relative bias (OBS - SIM)/SIM in percent

The uncertainty on the bias estimation is about 3%

No significant difference

Observations higher than SEVIRI calibration reference

Observations lower than SEVIRI calibration reference

slide22

METEOSAT-7 RESULTS

Estimated calibration error

Target characterisation error : 4.1%

SSR error contribution : 3.8%

Random error : 1.6%

Total calibration error : 6%

The SSR error should increase in time

slide23

METEOSAT-7 RESULTS

Difference wrt to CERES

CERES - SEVIRI/HRVIS : -1.5%

Total calibration error : 4.5%

SSR error contribution : 2.2%

CERES - MVIRI/VIS : +3%

Total calibration error : 6%

SSR error contribution : 3.8%

There is 3% difference between CERES-cross calibration and our calibration

slide24

METEOSAT-4 RESULTS

Calibration failed due to Pinatubo eruption

slide25

METEOSAT-5 RESULTS

The loss of transmittance depends on the wavelength

Desert

Sea

slide27

SSCC Drift

Pre-launch

Level 1.5 value

slide28

Cross-calibration with TRMM/VIRS (NASA)

8% difference

c = R / K: our calibration reference is too low!

Nguyen, L., Doelling, D.R., Minnis, P.J., and Ayers, J.K. (2004) Rapid technique to cross-calibrate satellite imager visible channels, in Proceedings of 49th SPIE, Earth Observing Systems IX, Denver, CO,August 2-6, 2004, 227-235.

Rayleigh calibration over sea (LOA, J.-M. Nicolas)

1% to -4% difference

c = R / K: our calibration reference is too high/low!

J.-M. Nicolas, P.-Y. Deschamps, O. Hagolle, In-flight absolute calibration of the visible channel of Meteosat Second Generation using Rayleigh Scattering over oceans, Proceedings of the 1st MSG RAO Workshop, ESA SP-452, 2000

Cross-calibration with CERES (IRMB, N. Clerbaux)

1.5% difference

c = R / K: our calibration reference is too high!

conclusions
CONCLUSIONS
  • All solar channels onboard MFG and MSG are routinely and consistently calibrated.
  • Our calibration reference (bright desert TOA simulated radiance) might be 2-3% too low w.r.t. instruments on ESA platforms.
  • An advanced Quality Control has been implemented to reject unreliable results.
  • Possible room for improvements