1. Algorithm improvements for Dutch OMI NO2 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 NO2 slant columns higher than GOME-2 & SCIAMACHY
(similar to findings N. Krotkov)
A difference of about 0.5x1015 molec/cm2 is expected due to difference in observation time
So what else is different?
Well a lot: fitting window, included reference spectra, polynomial degree, wavelength calibration approaches
OMI
GOME-2
SCIAMACHY
fit window [nm]
405 – 465
425 – 450
426.5 – 451.5
secondary trace gases
O3, H2O
O3, H2O, O2-O2
pseudo-absorbers
Ring
degree of polynomial 5 3 2
slant column processing *
KNMI / NASA
BIRA-IASB
*) Data assimilation, separation of tropospheric and stratospheric column,
and conversion to total columns for all at KNMI.

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
Now OMI slit function instead of parameterized broadened Gaussian
High-resolution solar spectrum from Kurucz but through updated OMI slit function
RMS of fit: %
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!
Now OMI slit function instead of parameterized broadened Gaussian
High-resolution solar spectrum from Kurucz but through updated OMI slit function
O2-O2: Thalman and Volkamer
LQW: Pope and Fry
RMS of fit: %
NO2 slant columns: -11%

5. Including liquid water
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.
All these processes are interacting on one another
Strong feature for clear water pixel !

6. Including LQW and O2-O2 improves the fit
More realistic ozone columns
Lowest RMS when including
both LQW and O2-O2
All these processes are interacting on one another
Including LQW and O2-O2 reduces NO2 SCDs by molec.cm-2

7. C. Improve λ-calibration window to map I to I0
Identify λ-calibration window that minimizes RMS/NO2 fit error
RMS of fit: %
NO2 slant columns: -13%
Now OMI slit function instead of parameterized broadened Gaussian
High-resolution solar spectrum from Kurucz but through updated OMI slit function
O2-O2: Thalman and Volkamer
LQW: Pope and Fry
Best results for nm
Previously: nm

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 nm and OMI window x 1015
Reduction of x 1015
Now OMI slit function instead of parameterized broadened Gaussian
High-resolution solar spectrum from Kurucz but through updated OMI slit function
O2-O2: Thalman and Volkamer
LQW: Pope and Fry

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
Differences in layering, emissions,

10. 2. Re-coupling worked (3° × 2°)
TM4-based
TM5-based
Differences in layering, emissions
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
Differences in layering, emissions
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
Differences in layering, emissions
Madrid
Madrid

13. 2. Updating to TM5 at 1° × 1° TM4-based 20-30 Oct 2004
Differences in layering, emissions
20-30 Oct 2004
Average tropospheric NO2
2°×3°: molec./cm2
1°×1°: molec./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
Differences in layering, emissions
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
Differences in layering, emissions
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
Credits: Russ Dickerson, Johan de Haan, Bram Maasakkers
Acknowledgment: Johan de Haan

17. 3. Corrections to O2-O2 cloud pressures
TM4-based
Differences in layering, emissions

18. 3. Impact on NO2 retrievals
TM4-based
Differences in layering, emissions
Higher clouds  more screening  lower AMFs

19. 3. Conclusions
Improved NO2 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 NO2 team from 2014 onwards:

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…