Séminaire LATMOS

jeudi 10 septembre 11H
tour 45 ou 46, 4ème étage, salle 411

Carbon Monoxide Data Assimilation for Atmospheric Composition and Climate
Science: Evaluating Performance with Current and Future Observations

Jérôme Barré1, David Edwards1, Helen Worden1, Avelino Arellano2, Benjamin
Gaubert1, Arlindo Da Silva3, Jeffrey Anderson4

1 NCAR, Atmospheric Chemistry Observation and Modeling Laboratory,
Boulder, CO, USA
2 University of Arizona, Tucson, AZ, USA
3 NASA Goddard Space Flight Center, Greenbelt, MD, USA
4 NCAR, Institute for Mathematics Applied to Geo-sciences, Boulder, CO, USA

Current satellite observations of tropospheric composition made from low
Earth orbit provide at best one or two measurements each day at any given
location. Comparisons of Terra/MOPITT carbon monoxide (CO) and IASI/Metop
CO observation assimilations will be presented. We use the DART Ensemble
Adjustment Kalman Filter to assimilate observations in the CAM-Chem global
chemistry-climate model. Data assimilation impacts due to both different
instrument capabilities (i.e. vertical sensitivity and global coverage)
will be discussed. Coverage is global but sparse, often with large
uncertainties in individual measurements that limit examination of local
and regional atmospheric composition over short time periods. This has
hindered the operational uptake of these data for monitoring air quality
and population exposure, and for initializing and evaluating chemical
weather forecasts. By the end of the current decade there are planned
geostationary Earth orbit (GEO) satellite missions for atmospheric
composition over North America, East Asia and Europe with additional
missions proposed. Together, these present the possibility of a
constellation of geostationary platforms to achieve continuous
time-resolved high-density observations of continental domains for mapping
pollutant sources and variability on diurnal and local scales. We describe
Observing System Simulation Experiments (OSSEs) to evaluate the
contributions of these GEO missions to improve knowledge of near-surface
air pollution due to intercontinental long-range transport and quantify
chemical precursor emissions. Our approach uses an efficient computational
method to sample a high-resolution global GEOS-5 chemistry Nature Run over
each geographical region of the GEO constellation. The demonstration
carbon monoxide (CO) observation simulator, which will be expanded to
other chemical pollutants, currently produces multispectral retrievals
(MOPITT-like) and captures realistic scene-dependent variation in
measurement vertical sensitivity and cloud cover. The impact of observing
over each region is evaluated independently. Winter and summer cases
studies are investigated i.e. where emissions, cloud cover and CO lifetime
significantly change.