Impacts Of Atmospheric State On Differential Absorption Spectroscopy Retrievals Of Column XCO2 Mixing Ratios

Abstract:

This work assesses the impact of uncertainties in atmospheric state on laser absorption spectroscopy (LAS)-based retrievals of CO₂ column mixing ratios (XCO2). LAS estimates of column XCO₂ are normally derived from a combination of observed CO₂ differential optical depths (∆τ) and measured/estimated values of temperature, moisture and pressure along the viewing path. XCO₂ can be related to CO₂ ∆τ as
(see equation)
where Δτ_other represents residual observed ∆τ due to other species, ∆σ is the CO₂ differential absorption cross section, p_sfc is the surface pressure, q is the local specific humidity and λ_on/λ_off represent the observation on/off-line wavelengths. As shown by these equations, the accuracy of retrieved XCO₂ values depends on both the error characteristics of the observed ∆τ and the ability to accurately characterize P, T, and q along the observed path. In the case of global space-based monitoring systems it is often not possible to provide collocated in situ measurements of the ancillary quantities for all observations. Therefore, retrievals often rely on collocated remotely sensed data or values derived from Numerical Weather Predictions (NWP) models to describe the atmospheric state. 
A radiative transfer (RT)-based simulation framework, combined with representative global upper-air observations and matched NWP profiles, was used to assess the impact of model differences in vertical T, vertical moisture, and p_sfc on estimates of column CO₂ and O₂ concentrations. These analyses focus on characterizing these errors for several CO₂ features in the 1.57- and 2.05-µm region, and representative O₂ features near 0.76 and 1.27 µm. The results provide a set of signal-to-noise metrics that characterize the errors in retrieved values associated with uncertainties in knowledge of the atmospheric state, and provide a method for selecting optimal differential line pairs to minimize the impact of this noise term. These metrics may help define the instrument requirements needed to meet the objectives of the proposed Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) satellite mission, and have provided information to facilitate the design, development, and assessment of the NASA Langley Research Center’s ASCENDS CarbonHawk Experiment Simulator (ACES).