Validation of SCIAMACHY total ozone: ESA/DLR V5(W) and IUP WFDOAS V2(W)

M. Weber, S. Dikty, J. P.Burrows, M. Coldewey-Egbers(1),

V. E. Fioletov(2), S. M. Frith(3), and D. Loyola(1)

Contact: weber@uni-bremen.de(1) DLR Oberpfaffenhofen(2) Environment Canada(3) NASA GSFC

SQWG Meeting, Bremen, Germany, 13-14 June 2013

The datasets

• ESA/DLR V5(W)• WFDOAS V2m(W)

– with V7 L1 m-factor• WFDOAS V2(W)

– without V7 L1 m-factor

Correlative datasets

• WOUDC database (brewer/dobson/filter)– monthly mean zonal mean

data (Fioletov et al. 2002)– Daily station averages

(collocated data)

• SBUV merged data V8.6– Monthly mean zonal mean

data (Frith et al., 2012)

Bias and drifts of SCIA WFDOAS wrt GOME

Drift (%/decade) Bias (% in 2002)

w/o m-factors

with m-factors

Bias and drifts of SCIA WFDOAS wrt GOME

• GOME stable over a 16 year period

• m-factors (Bramstedt et al., 2009 mainly reduces the drifts at low latitudes, little changes above 50°

• however, the drift and bias pattern looks a bit more complicated (e.g. some seasonal effects)

Drift (%/decade) Bias (% in 2002)

with m-factors

Zonal mean comparisons with WOUDC

• ESA/DLR higher than WFDOAS (~1.5%), but both in very good agreement with WOUDC (within ~1-2%, ~3-6 DU)

• Small (negative) drift evident in ESA/DLR and WFDOAS with m-factor wrt to WOUDC

• no systematic drifts between ESA and WFDm

Zonal mean comparisons with SBUV V8.6

• Very good agreement with SBUV merged for both WFD V2m and ESA V5 (within 2%)

• at polar latitudes (high SZA) negative biases in ESA/DLR

• gradient in the bias between SCIA and SBUV from tropics to high latitudes (bias decreases)

• weak positive drift with time in the tropics

Collocation with ground data

• Collocation criteria: – 300 km– distance weighted SCIA averages (within

collocation radius)

• Separate comparison with dobsons and brewers

– Seasonal cycle in differences to Dobson generally larger than to brewers

– constant T in ground retrievals– temperature sensitivity lower in brewers

Example: comparison with Brewer at Hohenpeissenberg, Germany (47°N)

ESA/DLR

WFD(m)

WFD

Station-by-station comparison

• x

WFDm: -0.7% WFDm: 0%

ESA: +0.5% ESA: +1.0%

Dependence by SZA

• x

WFDm-brewer WFDm-dobson

ESA-brewer ESA-dobson

• Little SZA dependence• SZA dependence in Dobson comparison related to seasonal variations (T issues)

Combined ozone and SZA dependency: ESA V5

• Low illumination conditions: high ozone and/or high SZA: – Bias to ground increases (straylight issues with both ground and satellite

data)• Special conditions: ozone hole conditions (very low ozone):

– Ground data tend to underestimate by up to 4% (Bernhard et al., 2005)

Combined ozone and SZA dependency: WFDOAS V2

• Low illumination conditions: high ozone and high SZA• Specual conditions: ozone hole conditions (very low ozone

Summary & Conclusion

• Very good agreement between SCIAMACHY (ESA & IUP) and WOUDC & SBUV merged (mostly within 1%)

• Some issues with ESA/DLR at polar latitudes (low bias)• Small differences in bias and seasonal patterns (ESA/DLR, WFDOAS) in

differences to SBUV and WOUDC are the result of slightly differing settings (different scalings of Bogumil cross-sections, choice of ozone profile climatology, different algorithm approach, and so on)

• The m-factor approach for L1 V7 successfully removes the drift in SCIAMACHY total ozone data (still some issues in the first year of the data record)

• WFDOAS V2 with m-factor agrees better than ESA V5, with the new GTO merged dataset (based upon GODFIT, Lerot et al. 2014, Chiou et al., 2013)

• RECOMMENDATION: GODFIT as the future ESA V6 will be an improvement over SGP 5 (see also Lerot et al. 2014)

APPENDIX

DOAS total ozone retrieval and ozone temperature• DOAS satellite retrievals (OMI,

GOMEs, SCIAMACHY)

– 325-335 nm (WFDOAS: 326.6-334.5 nm)

• U Bremen retrieval: Weighting function DOAS (Coldewey-Egbers et al., 2005, Weber et al., 2005, Lee et al., 2008)

– scalar temperature shift in the a-priori temperature profile

– effective ozone temperature TO3

• Both total ozone and temperature depend on ozone cross-section choice

Radiation transfer modelColdewey-Egbers et al., 2005

Weighting function DOAS

retrieved total ozone

retrievedozone temperature

Ozone and temperature terms in WFDOAS equation

– Anti-correlation between ozone and ozone temperature term

– Depending on fitting window size and position correlation ranges between r = -0.4 and -0.6

Coldewey-Egbers et al., 2005

GOME

WFDOAS total ozone data sets & cross-section used

• WFDOAS applied to GOME (1995-2011), SCIAMACHY (2002-2012), and GOME-2 (since 2006)– GOME1/ERS : Burrows et al. 1999 (GOME FM), shift: +0.017 nm– SCIAMACHY/ENVISAT: Bogumil et al., 2003 (SCIA FM), scaled 5.3%, shift: +0.008 nm– GOME2/METOP A: Burrows et al., 1999, convolved, shift: +0.017nm

• agreement to within 1% with WOUDC brewer and dobsons• Nevertheless: use of a single cross-section data for all instruments are needed to better understand calibration differences between instruments

merged WFDOAS data record (Weber et al. 2011, 2012 )

Satellite vs ground