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Applications of space-borne Carbon- monoxide measurements in Atmospheric Chemistry and Air Quality Maarten Krol, Wageningen University / SRON / IMAU Jos.

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Presentation on theme: "Applications of space-borne Carbon- monoxide measurements in Atmospheric Chemistry and Air Quality Maarten Krol, Wageningen University / SRON / IMAU Jos."— Presentation transcript:

1 Applications of space-borne Carbon- monoxide measurements in Atmospheric Chemistry and Air Quality Maarten Krol, Wageningen University / SRON / IMAU Jos 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 Emission Catagory Tg/yearUncertainty Fossil + BioFuel % Tropical Fires 17070% Savanna Fires 26870% Extra-Tropical Fires 2970% Biogenic 16060% Oxidation (NMHC)73460% Oxidation (CH 4 )79620% Total2748 Stavrakou & Muller, 2006 Main Sink: oxidation by the OH radical

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

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

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

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

8 de Laat et al., JGR, 2007

9 Error estimate: x10 18 #/cm 2

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

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

14 Remarks on modelling: 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)

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

16 TRANSCOM meeting: 2-6 June 2008, Utrecht Conclusions 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


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