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Enhancing Carbon Dioxide Budget Understanding through Satellite Carbon Monoxide Measurements

This study explores how space-borne satellite measurements of carbon monoxide (CO) contribute to atmospheric chemistry and air quality improvement. Key research focuses on the CO budget, emphasizing the primary sink of CO through oxidation by the hydroxyl (OH) radical. Utilizing data from SCIAMACHY and TROPOMI, the analysis reveals the effects of biomass burning and long-range transport, highlighting the significance of accurate measurements. The research also underscores the need for advanced modeling and data assimilation techniques to effectively incorporate satellite data and improve emission estimates.

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Enhancing Carbon Dioxide Budget Understanding through Satellite Carbon Monoxide Measurements

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  1. Applications of space-borne Carbon-monoxide measurements in Atmospheric Chemistry and Air QualityMaarten Krol, Wageningen University / SRON / IMAUJos de Laat (KNMI) & Annemieke Gloudemans & Ilse Aben (SRON) Jan Fokke Meirink (IMAU/KNMI) & Guido van der Werf (VU)

  2. Research Question How can satellite measurements help to improve our knowledge on the CO budget?

  3. Main Sink: oxidation by the OH radical Stavrakou & Muller, 2006

  4. SCIAMACHY CO • NIR (like TROPOMI) • Surface Sensitivity • Large Noise Errors: • Ice on detector • Weak Lines • Low NIR Albedo Averaging reduces noise related errors! IMLM v6.3 September 2003- August 2004 De Laat et al. GRL 2006 De Laat et al. GRL 2006

  5. Biomass burning Tracer studies 1: Sampling model: at right place & time 2: Inaccurate measurements get smaller weight Gloudemans et al. GRL 2006

  6. “Excess” CO column Considerable contribution from longe-range transport e.g. from South America

  7. Improved Biomass Burning estimates de Laat et al., JGR, 2007

  8. de Laat et al., JGR, 2007

  9. Error estimate: 0.05-0.1x1018 #/cm2

  10. IMLM 7.3 • September 2003 - December 2005 • Over Land: CC < 20% • Over Ocean: Cloud top > 800 hPa • TM4 vs. SCIAMACHY SCIAMACHY CO over oceans

  11. Modeled distribution consistent with SCIAMACHY observations • TM4 on average too low (NH) • Measurements over clouds!

  12. Models needed for quantitative analysis • Data-assimilation: • estimate “uncertain parameters” (emissions, initial composition) • satellite applications: must ingest large amounts of data (SCIAMACHY, TES, MOPITT) • All data sources have their own errors and biases: bias correction is required (e.g. ECMWF) Remarks on modelling:

  13. Ensemble Kalman Filter (e.g. CarbonTracker) • 4D-VAR (e.g. talk Ilse Aben, ECMWF) • Application to CO underway... Available techniques

  14. Development of models and assimilation techniques important for quantitative use satellite data • SCIAMACHY CO: promising development • Sensitivity down to Earth surface • TROPOMI CO: higher resolution, more cloudfree pixels, 5x better sensitivity Conclusions TRANSCOM meeting: 2-6 June 2008, Utrecht

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