O'Brien D.

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O'Brien
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  • Article
    Precision requirements for space-based XCO2 data
    (American Geophysical Union, 2007-05-26) Miller, C. E. ; Crisp, D. ; DeCola, P. L. ; Olsen, S. C. ; Randerson, James T. ; Michalak, Anna M. ; Alkhaled, A. ; Rayner, Peter ; Jacob, Daniel J. ; Suntharalingam, Parvadha ; Jones, D. B. A. ; Denning, A. S. ; Nicholls, M. E. ; Doney, Scott C. ; Pawson, S. ; Boesch, H. ; Connor, B. J. ; Fung, Inez Y. ; O'Brien, D. ; Salawitch, R. J. ; Sander, S. P. ; Sen, B. ; Tans, Pieter P. ; Toon, G. C. ; Wennberg, Paul O. ; Wofsy, Steven C. ; Yung, Y. L. ; Law, R. M.
    Precision requirements are determined for space-based column-averaged CO2 dry air mole fraction (XCO2) data. These requirements result from an assessment of spatial and temporal gradients in XCO2, the relationship between XCO2 precision and surface CO2 flux uncertainties inferred from inversions of the XCO2 data, and the effects of XCO2 biases on the fidelity of CO2 flux inversions. Observational system simulation experiments and synthesis inversion modeling demonstrate that the Orbiting Carbon Observatory mission design and sampling strategy provide the means to achieve these XCO2 data precision requirements.
  • Article
    Carbon source/sink information provided by column CO2 measurements from the Orbiting Carbon Observatory
    (Copernicus Publications on behalf of the European Geosciences Union, 2010-05-03) Baker, David F. ; Bosch, H. ; Doney, Scott C. ; O'Brien, D. ; Schimel, David S.
    We quantify how well column-integrated CO2 measurements from the Orbiting Carbon Observatory (OCO) should be able to constrain surface CO2 fluxes, given the presence of various error sources. We use variational data assimilation to optimize weekly fluxes at a 2°×5° resolution (lat/lon) using simulated data averaged across each model grid box overflight (typically every ~33 s). Grid-scale simulations of this sort have been carried out before for OCO using simplified assumptions for the measurement error. Here, we more accurately describe the OCO measurements in two ways. First, we use new estimates of the single-sounding retrieval uncertainty and averaging kernel, both computed as a function of surface type, solar zenith angle, aerosol optical depth, and pointing mode (nadir vs. glint). Second, we collapse the information content of all valid retrievals from each grid box crossing into an equivalent multi-sounding measurement uncertainty, factoring in both time/space error correlations and data rejection due to clouds and thick aerosols. Finally, we examine the impact of three types of systematic errors: measurement biases due to aerosols, transport errors, and mistuning errors caused by assuming incorrect statistics. When only random measurement errors are considered, both nadir- and glint-mode data give error reductions over the land of ~45% for the weekly fluxes, and ~65% for seasonal fluxes. Systematic errors reduce both the magnitude and spatial extent of these improvements by about a factor of two, however. Improvements nearly as large are achieved over the ocean using glint-mode data, but are degraded even more by the systematic errors. Our ability to identify and remove systematic errors in both the column retrievals and atmospheric assimilations will thus be critical for maximizing the usefulness of the OCO data.