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This work assesses the impact of uncertainties in atmospheric state knowledge on retrievals of carbon dioxide column amounts ( XC O 2 ) from laser differential absorption spectroscopy (LAS) measurements. LAS estimates of XC O 2 columns are normally derived not only from differential absorption observations but also from measured or prior knowledge of atmospheric state that includes temperature, moisture, and pressure along the viewing path. In the case of global space-based monitoring systems, it is often difficult if not impossible to provide collocated in situ measurements of atmospheric state for all observations, so retrievals often rely on collocated remote-sensed data or values derived from numerical weather prediction (NWP) models to describe the atmospheric state. A radiative transfer-based simulation framework, combined with representative global upper-air observations and matched NWP profiles, was used to assess the impact of model differences on estimates of column C O 2 and O 2 concentrations. These analyses focus on characterizing these errors for LAS measurements of C O 2 in the 1.57 - μ m region and of O 2 in the 1.27 - μ m region. The results provide a set of signal-to-noise metrics that characterize the errors in retrieved values associated with uncertainties in atmospheric state and provide a method for selecting optimal differential absorption line pairs to minimize the impact of these noise terms.

Impact of atmospheric state uncertainties on retrieved XCO2columns from laser differential absorption spectroscopy measurements

Impact of atmospheric state uncertainties on retrieved XCO₂columns from laser differential absorption spectroscopy measurements