We provide quantitative estimates for the spatial variability of CO(2), crucial for assessing representativeness of observations. Spatial variability determines the mismatch between point observations and spatial averages simulated by models or observed from space-borne sensors. Such "representation errors'' must be properly specified in determining the leverage of observations to retrieve surface fluxes or to validate space-borne sensors. We empirically derive the spatial variability and representation errors for tropospheric CO2 over the North American continent and the Pacific Ocean, using in-situ observations from extensive aircraft missions. The spatial variability and representation error of CO2 is smaller over the Pacific than the co...
International audienceAtmospheric inversions inform us about the magnitude and variations of greenho...
We present an analysis framework and illustrate its potential to constrain terrestrial carbon fluxes...
Inverse modelling of carbon sources and sinks requires an accurate quality estimate of the modelling...
We provide quantitative estimates for the spatial variability of CO(2), crucial for assessing repres...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95625/1/grl24793.pd
We analyze the spatial variability of CO2 measurements from aircraft platforms, including extensive ...
air mole fraction (XCO2) will be used in inversion and data assimilation studies to improve the prec...
Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improv...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95294/1/jgrd14612.pd
Column CO2 observations from current and future remote sensing missions represent a major advancemen...
National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 (OCO-2) satellite prov...
National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite prov...
Estimates of CO<sub>2</sub> fluxes that are based on atmospheric measurements rely upon a meteorolog...
Inverse modelling of carbon sources and sinks requires an accurate estimate of the quality of the ob...
International audienceAtmospheric inversions inform us about the magnitude and variations of greenho...
We present an analysis framework and illustrate its potential to constrain terrestrial carbon fluxes...
Inverse modelling of carbon sources and sinks requires an accurate quality estimate of the modelling...
We provide quantitative estimates for the spatial variability of CO(2), crucial for assessing repres...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95625/1/grl24793.pd
We analyze the spatial variability of CO2 measurements from aircraft platforms, including extensive ...
air mole fraction (XCO2) will be used in inversion and data assimilation studies to improve the prec...
Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improv...
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95294/1/jgrd14612.pd
Column CO2 observations from current and future remote sensing missions represent a major advancemen...
National Aeronautics and Space Administration’s Orbiting Carbon Observatory-2 (OCO-2) satellite prov...
National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite prov...
Estimates of CO<sub>2</sub> fluxes that are based on atmospheric measurements rely upon a meteorolog...
Inverse modelling of carbon sources and sinks requires an accurate estimate of the quality of the ob...
International audienceAtmospheric inversions inform us about the magnitude and variations of greenho...
We present an analysis framework and illustrate its potential to constrain terrestrial carbon fluxes...
Inverse modelling of carbon sources and sinks requires an accurate quality estimate of the modelling...