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Algorithm improvements for Dutch OMI NO 2 retrievals (towards v3.0)

Algorithm improvements for Dutch OMI NO 2 retrievals (towards v3.0). Folkert Boersma , Jos van Geffen, Bram Maasakkers , Henk Eskes , Jason Williams, and Pepijn Veefkind. 1 . Spectral fitting (lead: Jos van Geffen) . OMI NO 2 slant columns higher than GOME-2 & SCIAMACHY

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Algorithm improvements for Dutch OMI NO 2 retrievals (towards v3.0)

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  1. Algorithm improvements for Dutch OMI NO2 retrievals (towards v3.0) Folkert Boersma, Jos van Geffen, Bram Maasakkers, HenkEskes, Jason Williams, and PepijnVeefkind

  2. 1. Spectral fitting (lead: Jos van Geffen) OMI NO2 slant columns higher than GOME-2 & SCIAMACHY (similar to findings N. Krotkov) A difference of about 0.5x1015molec/cm2 is expected due to difference in observation time So what else is different?

  3. A. Improve solar reference spectrum Update of high-resolution solar spectrum: - better representation of OMI ITF (measured) - better Ring-spectrum and I0-corrected reference spectra New solar spectrum improves effective λ-calibration With old parameterized ITF RMS of fit: -17% NO2 slant columns: -6% Other reference spectra otherwise identical to OMNO2A

  4. B. Improve other reference spectra NO2: still Vandaele et al. [1998] but with new ITF O3: Bogumil et al. [2000] instead of obscure WMO-1975 H2O: HITRAN-2012 intead of HITRAN-2004 O2-O2: Now included! LQW: Now included! Stronger amplitude in new NO2 cross section! RMS of fit: -30% NO2 slant columns: -11%

  5. Including liquid water Strong feature for clear water pixel ! Fit results for cloudy pixels are not affected much when including liquid water absorption. Including liquid water absorption in the NO2 fit is a good idea.

  6. Including LQW and O2-O2 improves the fit Lowest RMS when including both LQW and O2-O2 More realistic ozone columns Including LQW and O2-O2 reduces NO2 SCDs by 0.3 1015 molec.cm-2

  7. C. Improve λ-calibration window to map I to I0 Identify λ-calibration window that minimizes RMS/NO2 fit error Best results for 409-428 nm Previously: 408-423 nm RMS of fit: -32% NO2 slant columns: -13%

  8. Summary of the spectral fitting improvements • Statistical NO2 fitting error reduces from 1.3 to 1.0 x 1015 • Good consistency with QDOAS (thanks Isabelle De Smedt) • Difference between 425-450 nm and OMI window 0.2-0.4 x 1015 Reduction of 1.0-1.3 x 1015

  9. 2. A new framework for DOMINO retrievals • The 3-D Tracer Model is at the heart of DOMINO retrieval for: • data assimilation to estimate stratospheric NO2 columns • a priori NO2 profile shapes input to AMF • temperature corrections • DOMINO v1 and v2: based on TM4 with 3° × 2° • DOMINO v3: based on TM5 on 1° × 1° Bram Maasakkers, M.Sc • Motivation for re-coupling: • TM4 no longer supported/developed • TM5 v3.0 is a benchmarked (Huijnen et al., 2010) model • Allows 1° × 1° • Employs up-to-date emission inventories more representative for the OMI-era

  10. 2. Re-coupling worked (3° ×2°) TM5-based TM4-based White areas: negatives With new TM5: 27% fewer negatives 20-30 Oct 2004

  11. 2. Re-coupling worked (3° ×2°) Lower emissions in TM5 TM4-based Fewer negatives in TM5-based retrieval 20-30 Oct 2004

  12. 2. Updating to TM5 at 1° ×1° We improve the retrieval by using TM5 a priori profiles at 1o×1o instead of 3o×2o Better resolved a priori profile shapes lead to a better understanding of pollution gradients observed from space TM4-based Madrid Madrid

  13. 2. Updating to TM5 at 1° ×1° TM4-based 20-30 Oct 2004 Average tropospheric NO2 2°×3°: 0.31 1015molec./cm2 1°×1°: 0.31 1015molec./cm2

  14. 2. Updating to TM5 at 1° ×1° Sharper contrast between urban and rural profile shapes will resolve some of the previously found underestimations over hotspot regions (Ma et al., 2013; Shaiganfar et al., 2011) TM4-based Lower AMFs over hotspots 3x higher surface NO2 for Barcelona in 1x1 vs. 3x2

  15. 2. DOMINO with TM5 at 1° ×1° vs. at 3° ×2° Barcelona +22% TM4-based Some of the urban-rural contrast is indeed a consequence of the coarse a priori profiles

  16. 3. Systematic error in O2-O2 cloud pressures • Retrieved O2-O2 slant column depends on atmospheric temperature profile • LUT for O2-O2 based on fixed AFGL mid-latitude summer T-profile • O2-O2 slant columns require T-correction since • ‘true’ T-profile may differ strongly from mls-profile Acknowledgment: Johan de Haan

  17. 3. Corrections to O2-O2 cloud pressures TM4-based

  18. 3. Impact on NO2 retrievals TM4-based Higher clouds  more screening  lower AMFs

  19. 3. Conclusions • Improved NO2 slant columns are smaller by 1.0-1.3 1015 molec.cm-2 with 30% lower fitting residuals • Coupled DOMINO to TM5 v3: 27% fewer negatives • Improved resolution for a priori profile leads to increases over hotspots (+20%) and stronger contrast urban-rural • Temperature-correction for cloud pressures relevant over polluted areas (TROP)OMI NO2 team from 2014 onwards:

  20. Differences between TM4 and TM5 Emissions TM4: POET 1997

  21. Integrate over pressure, not altitude Express number density O2 as a function of pressure and temperature Retrieved slant column will depend on 1/T, but LUT slant columns do not…

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