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Algorithm improvements for Dutch OMI NO 2 retrievals (towards v3.0) Folkert Boersma, Jos van Geffen, Bram Maasakkers, Henk Eskes, Jason Williams, and Pepijn.

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Presentation on theme: "Algorithm improvements for Dutch OMI NO 2 retrievals (towards v3.0) Folkert Boersma, Jos van Geffen, Bram Maasakkers, Henk Eskes, Jason Williams, and Pepijn."— Presentation transcript:

1 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

2 1. Spectral fitting (lead: Jos van Geffen) OMI NO 2 slant columns higher than GOME-2 & SCIAMACHY (similar to findings N. Krotkov) A difference of about 0.5x10 15 molec/cm 2 is expected due to difference in observation time OMIGOME-2SCIAMACHY fit window [nm]405 – – – secondary trace gasesO 3, H 2 OO 3, H 2 O, O 2 -O 2 pseudo-absorbersRing degree of polynomial532 slant column processing *KNMI / NASABIRA-IASB *) Data assimilation, separation of tropospheric and stratospheric column, and conversion to total columns for all at KNMI. 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 I 0 -corrected reference spectra New solar spectrum improves effective λ-calibration With old parameterized ITF RMS of fit: -17% NO 2 slant columns: -6% Other reference spectra otherwise identical to OMNO2A

4 B. Improve other reference spectra NO 2 : still Vandaele et al. [1998] but with new ITF O 3 :Bogumil et al. [2000] instead of obscure WMO-1975 H 2 O:HITRAN-2012 intead of HITRAN-2004 O 2 -O 2 :Now included! LQW:Now included! Stronger amplitude in new NO 2 cross section! RMS of fit: -30% NO 2 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 NO 2 fit is a good idea.

6 Including LQW and O 2 -O 2 improves the fit Lowest RMS when including both LQW and O 2 -O 2 Including LQW and O 2 -O 2 reduces NO 2 SCDs by molec.cm -2 More realistic ozone columns

7 C. Improve λ -calibration window to map I to I 0 Identify λ-calibration window that minimizes RMS/NO 2 fit error Best results for nm Previously: nm RMS of fit: -32% NO 2 slant columns: -13%

8 Summary of the spectral fitting improvements Reduction of x Statistical NO 2 fitting error reduces from 1.3 to 1.0 x Good consistency with QDOAS (thanks Isabelle De Smedt) Difference between nm and OMI window x 10 15

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 NO 2 columns a priori NO 2 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° 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 Bram Maasakkers, M.Sc

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

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

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

13 2. Updating to TM5 at 1° × 1° TM4-based Average tropospheric NO 2 2°×3°: molec./cm 2 1°×1°: molec./cm Oct 2004

14 2. Updating to TM5 at 1° × 1° TM4-based 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) 3x higher surface NO 2 for Barcelona in 1x1 vs. 3x2 Lower AMFs over hotspots

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

16 3. Systematic error in O 2 -O 2 cloud pressures Retrieved O 2 -O 2 slant column depends on atmospheric temperature profile LUT for O 2 -O 2 based on fixed AFGL mid-latitude summer T-profile O 2 -O 2 slant columns require T-correction since ‘true’ T-profile may differ strongly from mls-profile Acknowledgment: Johan de Haan

17 3. Corrections to O 2 -O 2 cloud pressures TM4-based

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

19 3. Conclusions Improved NO 2 slant columns are smaller by 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 NO 2 team from 2014 onwards:

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21 Differences between TM4 and TM5 Emissions TM4: POET 1997

22 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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