1 / 30

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

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)

whitney
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 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

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

  3. 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

  4. 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.

  5. MFG / MVIRI (VIS band) M4 M3 M2 M7 M5 M6

  6. BACKGROUND Calibration target location Desert targets X Sea search areas 

  7. 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.

  8. BRIGHT DESERT TARGET DESCRIPTION POLDER observations ATSR2 observations Bright sandstone spectra from the ASTER spectral data base

  9. BRIGHT DESERT TARGET DESCRIPTION Example of surface BRF over one target

  10. BRIGHT DESERT TARGET DESCRIPTION Simulated spectral radiance over one target

  11. BRIGHT DESERT TARGET DESCRIPTION Error contribution of each parameter over one desert target Atmosphere Surface

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. VERIFICATION (2) Spectral bands Spectral response of the radiometric bands used in the comparion. SEVIRI ATSR-2SeaWiFSMERISVGT

  18. VERIFICATION (3) Comparison between observation and simulation Monthly mean relative bias averaged over all targets: Relative bias Bias error Monthly mean weighted relative bias

  19. VERIFICATION (3) Monthly mean relative difference (bias + std. dev.) between simulations and observations over all targets

  20. 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

  21. MFG / MVIRI RESULTS

  22. 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

  23. 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

  24. METEOSAT-4 RESULTS Calibration failed due to Pinatubo eruption

  25. METEOSAT-5 RESULTS The loss of transmittance depends on the wavelength Desert Sea

  26. MSG / SEVIRI RESULTS

  27. SSCC Drift Pre-launch Level 1.5 value

  28. 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!

  29. 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

More Related