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Comparison of SCIAMACHY NRT Ozone Columns with GOME Assimilated Ozone Fields

Comparison of SCIAMACHY NRT Ozone Columns with GOME Assimilated Ozone Fields. Henk Eskes, Jan Fokke Meirink, Ankie Piters Royal Netherlands Meteorological Institute, De Bilt. GOME ozone data assimilation. TM3DAM: • ECMWF meteo, second moment advection,

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Comparison of SCIAMACHY NRT Ozone Columns with GOME Assimilated Ozone Fields

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  1. Comparison of SCIAMACHY NRT Ozone Columns with GOME Assimilated Ozone Fields Henk Eskes, Jan Fokke Meirink, Ankie Piters Royal Netherlands Meteorological Institute, De Bilt

  2. GOME ozone data assimilation TM3DAM: • ECMWF meteo, second moment advection, • Gas-phase + heterogeneous chemistry parametrization • Detailed forecast error modelling • KNMI GOME Fast Delivery ozone columns Internet User Service: • 5-day ozone forecast • GOME ozone data bases www.knmi.nl/gome_fd

  3. SCIAMACHY Validation strategy TM3DAM: • Monitoring of Sciamachy ozone columns • SCIA observation minus forecast • Using GOME validation results (D. Balis, J.C. Lambert) Observation minus forecast: • Check on Gaussian statistics • Bias and standard deviation • Dependence on: * latitude, latitude-longitude maps * time * viewing angle * spatial resolution * solar zenith angle * … * cloud parameters

  4. OmF: SCIA vs assimilated GOME Scia NRT Processor 3.53 25/10 to 6/11 (GOME bias corrected)

  5. OmF: latitude dependence Scia NRT Processor 3.53 25/10 to 6/11 (GOME bias corrected)

  6. OmF: distribution Scia NRT Processor 3.53 25/10 to 6/11 (GOME bias corrected) SZA < 60 degree GOME OmF, rms=8DU, Gaussian

  7. Ozone: viewing-angle dependence Scia NRT Processor 3.53 25/10 to 6/11 0.5 sec 1 sec 0.25 sec

  8. OmF: viewing-angle dependence 0.5 sec integr.time Scia NRT Processor 3.53 25/10 to 6/11 GOME bias corr.

  9. CONCLUSIONS: SCIAMACHY NRT total ozone: • Negative bias 20-25 DU Solution: use SCIAMACHY FM ozone cross-sections • Viewing-angle dependence Solution: correct viewing angle • Still biases, especially high Solar Zenith Angles, seasonality Advice: upgrade processor to GOME GDP 3.0 Polarization, realistic cloud information • RMS (noise) very promising: comparable to / better than GOME Validation with data assimilation - OmF differences • Good statistics, to detect subtle effects Small biases, noise statisitics, correlations, jumps in time …

  10. Validation support Validation tools: Sciamachy validation web page: www.sciamachy-validation.org ACVT-MASI activity: Submission of assimilation ozone profiles to NILU

  11. www.sciamachy-validation.org

  12. Faraday www.sciamachy-validation.org

  13. www.sciamachy-validation.org

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