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)

Research Question

How can satellite measurements help to improve our knowledge on the CO budget?

Emission Catagory Tg/year Uncertainty

Fossil + BioFuel 571 35-60%

Tropical Fires 170 70%

Savanna Fires 268 70%

Extra-Tropical Fires 29 70%

Biogenic 160 60%

Oxidation (NMHC) 734 60%

Oxidation (CH4) 796 20%

Total 2748

Stavrakou & Muller, 2006

Main Sink: oxidation by the OH radical

De Laat et al. GRL 2006

IMLM v6.3September 2003-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!

Gloudemans et al. GRL 2006

1: Sampling model:at right place & time

2: Inaccurate measurementsget smaller weight

Biomass burningTracer studies

Considerable contributionfrom longe-range transporte.g. from South America

“Excess” CO column

de Laat et al., JGR, 2007

Improved Biomass Burning estimates

de Laat et al., JGR, 2007

Error estimate: 0.05-0.1x1018 #/cm2

SCIAMACHY CO over oceans

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

Modeled distribution consistent with SCIAMACHY observations

TM4 on average too low (NH) Measurements over clouds!

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)

Available techniques

Ensemble Kalman Filter (e.g. CarbonTracker)

4D-VAR (e.g. talk Ilse Aben, ECMWF) Application to CO underway...

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