1Department of Atmospheric & Oceanic Science, University of Maryland, 3433 Computer & Space Sciences Bldg, College Park, MD, USA
2Joint Center for Earth Systems Technology, University of Maryland Baltimore County, Baltimore, MD, USA
3Universities Space Research Association, 10211 Wincopin Circle, Columbia, MD 21044, USA
4Norwegian Institute of Air Research, Instituttveien 18, Kjeller 2027, Norway
5CNRM-GAME, Météo-France and CNRS, UMR3589, Toulouse, France
6Laboratoire d'Aérologie, Université de Toulouse, CNRS, UMR5560, Toulouse, France
7Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Abstract. This study tests a novel methodology to add value to satellite data sets. This methodology, data fusion, is similar to data assimilation, except that the background model-based field is replaced by a satellite data set, in this case AIRS (Atmospheric Infrared Sounder) carbon monoxide (CO) measurements. The observational information comes from CO measurements with lower spatial coverage than AIRS, namely, from TES (Tropospheric Emission Spectrometer) and MLS (Microwave Limb Sounder). We show that combining these data sets with data fusion uses the higher spectral resolution of TES to extend AIRS CO observational sensitivity to the lower troposphere, a region especially important for air quality studies. We also show that combined CO measurements from AIRS and MLS provide enhanced information in the UTLS (upper troposphere/lower stratosphere) region compared to each product individually. The combined AIRS–TES and AIRS–MLS CO products are validated against DACOM (differential absorption mid-IR diode laser spectrometer) in situ CO measurements from the INTEX-B (Intercontinental Chemical Transport Experiment: MILAGRO and Pacific phases) field campaign and in situ data from HIPPO (HIAPER Pole-to-Pole Observations) flights. The data fusion results show improved sensitivities in the lower and upper troposphere (20–30% and above 20%, respectively) as compared with AIRS-only version 5 CO retrievals, and improved daily coverage compared with TES and MLS CO data.