HR: 1330h
AN: A52B-0781    [PDF]
TI: Can Satellite Measurements Represent Regional Scale CO$_{2}$ Variability?
AU: * Corbin, K
EM: kdcorbin@atmos.colostate.edu
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Denning, A S
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Prihodko, L
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AU: Nicholls, M
AF: Colorado State University, Department of Atmospheric Science, Fort Collins, CO 80523-1371 United States
AB: Due to their uniform spatial sampling and sheer data volume, CO$_{2}$ measurements from satellites have the potential to help identify sources and sinks at the regional scale. These satellite measurements can be used in inversion models to enhance our understanding of the carbon cycle; however, since inversion models use grid cells larger than the measurement footprint, it is essential that the measurements accurately represent the average concentration at the inversion model resolution. Using a five-day simulation of surface fluxes and atmospheric CO$_{2}$ concentration from the Regional Atmospheric Modeling System (RAMS) coupled to the Simple Biosphere Model (SiB2) centered around a tall tower validation site in Wisconsin, we investigated the representativeness of satellite measurements on the regional scale. Comparing the mean of 1-km-wide N-S swaths of simulated column mean CO$_{2}$ with the "true" domain-averaged column mean mixing ratio over the 38x38 km grid at 2 PM on each of the five days, we found 95% of the swaths had mean mixing ratios within 0.18 ppm of the true domain-averaged mixing ratio. A similar study on a larger 600x600 km domain with 16 km grid spacing yields 95% of the N-S swaths capture the domain average within 0.17 ppm. Although future work is necessary, these results indicate satellite measurements will be capable of representing regional scale CO$_{2}$ variations.
UR: http://biocycle.atmos.colostate.edu
DE: 0315 Biosphere/atmosphere interactions
DE: 0322 Constituent sources and sinks
DE: 1640 Remote sensing
DE: 3337 Numerical modeling and data assimilation
SC: Atmospheric Sciences [A]
MN: 2003 Fall Meeting