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Roeland van Oss Ronald van der A and Johan de Haan, Robert Voors, Robert Spurr. Retrieval of Ozone Profiles from GOME ( and SCIAMACHY , and OMI, and GOME2 ). Content. Algorithm outline Current issues Validation Application: Data assimilation Tropospheric ozone column.
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Roeland van Oss Ronald van der A and Johan de Haan, Robert Voors, Robert Spurr Retrieval of Ozone Profiles from GOME (and SCIAMACHY, and OMI, and GOME2)
Content • Algorithm outline • Current issues • Validation • Application: • Data assimilation • Tropospheric ozone column
Algorithm outline Basic elements • On-line radiative transfer model: LIDORTA • Inversion: Optimal Estimation • Level 1 improvements 4 instruments: • GOME (ESA CHEOPS) • GOME2 (EUMETSAT O3MSAF) • OMI (National funding) • SCIAMACHY (…)
LIDORTA • LIDORT, Linearized discrete ordinates model (Spurr et al, 2000): radiances & derivatives • > LIDORTA: tailored for ozone profile retrieval Task for development: as fast as possible, but within required accuracy
LIDORTA …simulating radiance I • Geophysical • Pressure • Temperature • Trace gasses • Aerosol • Clouds • Surface • Optical • absorption • scattering
LIDORTA …and derivatives dI/dX • Geophysical • Pressure • Temperature • Trace gasses (X) • Aerosol • Clouds • Surface • Optical • d(absorption)/dX • d(scattering)/dX
LIDORTA: improving speed • Minimum number of streams (angular resolution) • allowing analytic solutions • Minimum number of atmospheric layers • 40 layers required • Separate single scattering with 40 layers • LIDORTA only for multiple scattered: 20 layers enough • Minimum number of calls to LIDORTA (number of wavelengths) • Sparse sampling for slow varying parts of spectrum (< 310 nm)
Optimal Estimation .. Following Rodgers (2000)
Level 1 improvements • Wavelength recalibration (van Geffen & van Oss, 2003) • Improved correction for polarization sensitivity of GOME (Schutgens & Stammes, 2003) • Radiometric recalibration (van der A et al. 2002) Varying in time (degradation) fixed in time
Current issues • LIDORT(A) does not treat POLARIZATION • Up to 10% error • Solved with look-up table • LIDORT(A) does not treat Raman scattering • “de Haan” approach (similar to TOGOMI/total ozone) • LIDORT(A) does treat sphericity of atmosphere • Accounting for high solar angles • Accounting for high viewing angles (GOME-2, OMI)
Validation Ozone profile Working Group BIRA & RIVM contributions
Applications of ozone profile retrieval at KNMI • Data assimilation (Arjo Segers) • Retrieval of global tropospheric ozone fields (Ronald van der A en Michiel van Weele)
High-res model profile estimate Averaging kernel O3 Data assimilation Data assimilation of ozone profiles using averaging kernels GOME measurement Low-res retrieved profile Low-res model profile
Data assimilation of profiles Intrusion of ozone rich air from the Arctic over Europe at a height of 150 hPa. April 12, 2000, 11h00
Retrieving tropospheric ozone columns • Processing of ozone profiles, averaging kernels and error covariance matrices • Comparison O3 profiles and sondes to determine realistic measurement errors • Data assimilation of ozone profiles, averaging kernels and error covariances provides accurate stratospheric ozone column. • Total column derived with TOGOMI • Cloud filtering using FRESCO Tropospheric column = (Total column) – (stratospheric ozone column)
Advantages of this method • GOME profiles are very accurate (nadir gives high spatial resolution) • Use of averaging kernels and data assimilation gives a realistic split-up between troposphere and stratosphere • Several definitions of tropopause possible • Global coverage ( southern hemisphere is sparsely covered with ground observations)
Example global tropospheric ozone product September 2000 Mean tropospheric ozone vmr (ppb) below 300 hPa