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Open AccessArticle

Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission

Department of Physics & Astronomy, University of Leicester, University Road, Leicester LE1 7RH, UK
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO 80523, USA
BC Consulting Limited, Alexandra 9320, New Zealand
Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
Author to whom correspondence should be addressed.
Remote Sens. 2011, 3(2), 270-304;
Received: 7 December 2010 / Revised: 8 February 2011 / Accepted: 9 February 2011 / Published: 14 February 2011
(This article belongs to the Special Issue Atmospheric Remote Sensing)
The global characteristics of retrievals of the column-averaged CO2 dry air mole fraction, XCO2, from shortwave infrared observations has been studied using the expected measurement performance of the NASA Orbiting Carbon Observatory-2 (OCO-2) mission. This study focuses on XCO2 retrieval precision and averaging kernels and their sensitivity to key parameters such as solar zenith angle (SZA), surface pressure, surface type and aerosol optical depth (AOD), for both nadir and sunglint observing modes. Realistic simulations have been carried out and the single sounding retrieval errors for XCO2 have been derived from the formal retrieval error covariance matrix under the assumption that the retrieval has converged to the correct answer and that the forward model can adequately describe the measurement. Thus, the retrieval errors presented in this study represent an estimate of the retrieval precision. For nadir observations, we find single-sounding retrieval errors with values typically less than 1 part per million (ppm) over most land surfaces for SZAs less than 70° and up to 2.5 ppm for larger SZAs. Larger errors are found over snow/ice and ocean surfaces due to their low albedo in the spectral regions of the CO2 absorption bands and, for ocean, also in the O2 A band. For sunglint observations, errors over the ocean are significantly smaller than in nadir mode with values in the range of 0.3 to 0.6 ppm for small SZAs which can decrease to values as small as 0.15 for the largest SZAs. The vertical sensitivity of the retrieval that is represented by the column averaging kernel peaks near the surface and exhibits values near unity throughout most of the troposphere for most anticipated scenes. Nadir observations over dark ocean or snow/ice surfaces and observations with large AOD and large SZA show a decreased sensitivity to near-surface CO2. All simulations are carried out for a mid-latitude summer atmospheric profile, a given aerosol type and vertical distribution, a constant windspeed for ocean sunglint and by excluding the presence of thin cirrus clouds. The impact of these parameters on averaging kernels and XCO2 retrieval errors are studied with sensitivity studies. Systematic biases in retrieved XCO2, as can be introduced by uncertainties in the spectroscopic parameters, instrument calibration or deficiencies in the retrieval algorithm itself, are not included in this study. The presented error estimates will therefore only describe the true retrieval errors once systematic biases are eliminated. It is expected that it will be possible to retrieve XCO2 for cloud free observations and for low AOD (here less than 0.3 for the wavelength region of the O2 A band) with sufficient accuracy for improving CO2 surface flux estimates and we find that on average 18% to 21% of all observations are sufficiently cloud-free with only few areas suffering from the presence of persistent clouds or high AOD. This results typically in tens of useful observations per 16 day ground track repeat cycle at a 1° × 1° resolution. Averaging observations acquired along ~1° intervals for individual ground tracks will significantly reduce the random component of the errors of the XCO2 average product for ingestion into data assimilation/inverse models. If biases in the XCO2 retrieval of the order of a few tenth ppm can be successfully removed by validation or by bias-correction in the flux inversion, then it can be expected that OCO-2 XCO2 data can lead to tremendous improvements in estimates of CO2 surface-atmosphere fluxes. View Full-Text
Keywords: trace gases; remote sensing; inverse theory trace gases; remote sensing; inverse theory
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Boesch, H.; Baker, D.; Connor, B.; Crisp, D.; Miller, C. Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission. Remote Sens. 2011, 3, 270-304.

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