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SSAG Data and Algorithm Subgroup, 10-11 February 2004, Brussels Summary of data product and algorithm development at KNMI Ronald van der A, Juan Acarreta,

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Presentation on theme: "SSAG Data and Algorithm Subgroup, 10-11 February 2004, Brussels Summary of data product and algorithm development at KNMI Ronald van der A, Juan Acarreta,"— Presentation transcript:

1 SSAG Data and Algorithm Subgroup, February 2004, Brussels Summary of data product and algorithm development at KNMI Ronald van der A, Juan Acarreta, Folkert Boersma, Henk Eskes, Martin de Graaf, Piet Stammes, Gijs Tilstra

2 SSAG Data and Algorithm Subgroup, February 2004, Brussels Calibration and retrieval algorithm development Polarisation-correction In-flight radiometric calibration PMD imaging tool (by Martin de Graaf) on SCIAVALIG website >Toolswww.sciamachy-validation.org LIDORT model extension to near-IR (Rob Spurr, Roeland van Oss, and Albert Goede) Absorbing aerosol index Cloud phase index Total ozone Tropospheric NO 2

3 SSAG Data and Algorithm Subgroup, February 2004, Brussels Determining U from Q based on Rayleigh single scattering theory The approximation  ( ) =  ss so U( ) = Q ( ) tan 2  ss is accurate for all POLDER wavelengths (443, 670, 865 nm) and scene types to an accuracy of  in U (1  ). The PMD-45 measurement by SCIAMACHY – which is currently uncertain – is therefore not needed. The assumption  ( ) =  ss is now used in the new 0-1 processor. (work by Gijs Tilstra)

4 SSAG Data and Algorithm Subgroup, February 2004, Brussels In-flight radiometric calibration - reflectance correction UV: Comparison of SCIAMACHY with DAK over cloudfree Sahara. VIS/near-IR: Comparison of SCIAMACHY with MERIS over large parts of orbits 2509 and Preliminary SCIAMACHY reflectance correction table (error ±0.05): wavelength (nm) correction factor

5 SSAG Data and Algorithm Subgroup, February 2004, Brussels Various correction factors for SCIAMACHY reflectance (work by Juan Acarreta)

6 SSAG Data and Algorithm Subgroup, February 2004, Brussels Parabola fit of reflectance correction factor: f( ) = a 0 + a 1 /( - 0 ) + a 2 /( - 0 ) 2 0 =240 nm, a 0 =1.3002, a 1 = , a 2 =4210.6

7 SSAG Data and Algorithm Subgroup, February 2004, Brussels Interpretation The reflectance correction factor resembles the spectral behaviour of the inverse BSDF of a diffuser: Correction( )  1/BSDF( ). (see e.g. spectral behaviour of GOME-2 diffusers). If the correction factor has to correct for the effect of a diffuser, either internal or external to SCIAMACHY during OPTEC, then the correction factor is expected to be a continuous and spectrally smooth function in the range nm.

8 SSAG Data and Algorithm Subgroup, February 2004, Brussels Absorbing Aerosol Index algorithm applied to GOME, validated with EP/TOMS Necessary for SCIAMACHY is improved radiometric calibration! (work by Martin de Graaf)

9 SSAG Data and Algorithm Subgroup, February 2004, Brussels Cloud phase algorithm for SCIAMACHY using the spectral slope at 1.67 micron (work by Juan Acarreta)

10 SSAG Data and Algorithm Subgroup, February 2004, Brussels Cloud phase index validation Cloud phase Index: CPI= 100 x (R(1.70) – R(1.64))/R(1.64) CPI = 0-20: clear scenes + water clouds CPI > 20: ice clouds Validated with MODIS cirrus reflectance. (work by Juan Acarreta)

11 Total ozone column from TOSOMI Based on the OMI-DOAS operational algorithm (Pepijn Veefkind) Implementations for GOME (TOGOMI - Pieter Valks) and Sciamachy (TOSOMI - Henk Eskes and Ronald van der A) Innovations compared to GOME Fast Delivery, vs 3: New treatment of Raman scattering (Johan de Haan) Empirical air-mass factor approach TOMS v8 ozone profile data base AMF computed with DAK (spherical corrections, polarization) Now also forecasted ozone fields up to one week ahead.

12 TOSOMI 0.32 example

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14 SSAG Data and Algorithm Subgroup, February 2004, Brussels SCIAMACHY total ozone from TEMIS was part of the Envisat News item on behalf of the 10,000-th orbit on 28 January ’04

15 Validation TOSOMI Comparison with assimilation and Brewers: good comparisons Brewer / Dobson no obvious seasonality small rms improvements at high SZA, snow (Raman)... despite problems Sciamachy calibration (level-1b). Validation with data assimilation has been important in the development of the retrieval code.

16 SSAG Data and Algorithm Subgroup, February 2004, Brussels Tropospheric NO 2 Assimilation of NO 2 slant column in a CTM model, and derivation of tropospheric column from the model. For more results on global and regional tropospheric NO 2, see the TEMIS website: (work by Folkert Boersma)

17 SSAG Data and Algorithm Subgroup, February 2004, Brussels RESERVE SHEETS

18 SSAG Data and Algorithm Subgroup, February 2004, Brussels CLOUDS 885

19 SSAG Data and Algorithm Subgroup, February 2004, Brussels MIXED 442

20 SSAG Data and Algorithm Subgroup, February 2004, Brussels SAHARA 885

21 Typical fit R(MERIS) vs. R(SCIA) at 665 nm

22 SSAG Data and Algorithm Subgroup, February 2004, Brussels SCIAMACHY O2 A-band measurement vs. FRESCO model for Sahara and high cloud

23 TOSOMI 0.31: SZA dependence, SH


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