Characterizing OCO-2 XCO2 Variability for the Conterminous United States and Adjacent Ocean
Mitchell, Kayla, Environmental Sciences - Graduate School of Arts and Sciences, University of Virginia
Doney, Scott, AS-Environmental Sciences, University of Virginia
We use a geostatistical framework to analyze new, high resolution, column-averaged CO2 (XCO2) measurements from NASA’s Orbiting Carbon Observatory 2 (OCO-2) and provide a characterization of seasonal and sub-seasonal variability within XCO2 over the conterminous United States and adjacent ocean basins. Of particular interest are the differences between land and ocean XCO2 distributions, which are significant in CO2 at the surface. Surface measurement networks have shown that surface CO2 fluxes are greater and more variable over land. We investigate whether this contrast is reflected in XCO2, for which large-scale transport generally obscures local fluxes. We show land and ocean seasonal XCO2 variability is most divergent for the west coast and fairly smoothed across the east coast. Our results are mostly consistent with modeled XCO2, showing a mean increasing north-south meridional pattern and high seasonal variability over areas affected by boreal carbon fluxes. The western United States has strikingly lower seasonal amplitudes than the adjacent Pacific Ocean and eastern United States. Higher latitudes in the domain tend to have greater seasonal amplitudes, and the highest seasonal amplitudes are over the Canadian Shield. Our results suggest synoptic-scale XCO2 variance is driven primarily by advection across the mean meridional gradient, consistent with findings from the ground-based Total Carbon Column Observing Network (Keppel-Aleks et al., 2011). Synoptic-scale XCO2 variance is greater (almost doubled for the west coast) over land than ocean, and greatest over the northwest and northeast. The impact of instrument and algorithm noise as well as small spatial-scale geophysical signals are evaluated by averaging adjacent retrievals along-orbit and found to impart ~25% of the variability in XCO2 data analyzed. There are certain incongruencies between our results and modeled or observed XCO2 that prompt further investigation into the OCO-2 data as well as model representations of atmospheric transport and surface fluxes. Future work will focus on attributing the observed variability to real geophysical signals or residual bias in OCO-2 soundings. This analysis provides insight on real carbon cycle and atmosphere-driven XCO2 variations and may be used to improve modeling and satellite retrieval techniques.
MS (Master of Science)
co2 , xco2, atmospheric co2, carbon dioxide, satellite, variability, climate, geostatistics