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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 Veefkind. 1 . Spectral fitting (lead: Jos van Geffen) . OMI NO 2 slant columns higher than GOME-2 & SCIAMACHY - PowerPoint PPT Presentation
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Algorithm improvements for Dutch OMI NO2 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 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
OMI GOME-2 SCIAMACHYfit window [nm] 405 – 465 425 – 450 426.5 – 451.5secondary trace gases O3, H2O O3, H2O, O2-O2 O3, H2O, O2-O2
pseudo-absorbers Ring Ring Ringdegree of polynomial 5 3 2slant column processing * KNMI / NASA BIRA-IASB BIRA-IASB
*) Data assimilation, separation of tropospheric and stratospheric column, and conversion to total columns for all at KNMI.
So what else is different?
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
B. Improve other reference spectra
NO2: still Vandaele et al. [1998] but with new ITFO3: Bogumil et al. [2000] instead of obscure WMO-1975H2O: HITRAN-2012 intead of HITRAN-2004O2-O2: Now included!LQW: Now included! Stronger amplitude in new NO2 cross section!
RMS of fit: -30%NO2 slant columns: -11%
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.
Including LQW and O2-O2 improves the fit
Lowest RMS when including both LQW and O2-O2
Including LQW and O2-O2 reduces NO2 SCDs by 0.3 1015 molec.cm-2
More realistic ozone columns
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 nmPreviously: 408-423 nm
RMS of fit: -32%
NO2 slant columns: -13%
Summary of the spectral fitting improvements
Reduction of 1.0-1.3 x 1015
• 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
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°
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
2. Re-coupling worked (3° × 2°)
TM5-basedTM4-based
White areas: negatives
With new TM5: 27% fewer negatives
20-30 Oct 2004
2. Re-coupling worked (3° × 2°)
TM4-based
Fewer negatives in TM5-based retrieval
Lower emissions in TM5
20-30 Oct 2004
2. Updating to TM5 at 1° × 1°
TM4-based
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
Madrid Madrid
2. Updating to TM5 at 1° × 1°
TM4-based
Average tropospheric NO2 2°×3°: 0.31 1015 molec./cm2
1°×1°: 0.31 1015 molec./cm2
20-30 Oct 2004
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 NO2 for Barcelona in 1x1 vs. 3x2
Lower AMFs over hotspots
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%
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
3. Corrections to O2-O2 cloud pressures
TM4-based
3. Impact on NO2 retrievals
TM4-based
Higher clouds more screening lower AMFs
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:
Differences between TM4 and TM5
Emissions TM4: POET 1997
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…