The Orbiting Carbon Observatory (OCO) strives for trace gas observations with unprecedented accuracy and precision. This requires a retrieval algorithm with many major improvements over existing retrieval software in the representation of the transfer of solar radiation through the atmosphere and instrument, such as full multiple-scattering calculation for each iteration step and correction for effects of polarization. In addition, the software allows retrieval of space-based and ground-based observations, so that potential algorithmic biases can be minimized for validation experiments. Furthermore, due to the flexible architecture of the software, spectra of existing similar instruments can be analyzed, which facilitates early testing using real space-based observations.
The primary purpose of the retrieval algorithm is to derive estimates of the column averaged atmospheric CO2 dry air mole fraction, XCO2, and other Level 2 data products from the spectra returned by the OCO-2 mission. XCO2 is defined as the ratio of the column abundances of CO2 and the column abundance of dry air.
This software retrieves a set of atmospheric/surface/instrument parameters from a simultaneous fit to spectra from multiple absorption bands. The software uses an iterative, non-linear retrieval technique (optimal estimation). After the retrieval process has converged, the software performs an error analysis. The products of the software include all quantities needed to understand the information content of the measurement, its uncertainty, and its dependence on interfering atmospheric properties.
The software provides a flexible, efficient, and accurate tool to retrieve the atmospheric composition from near-infrared spectra. Its unique features are:
- Spectra from ground-based or space-based measurement with arbitrary observation geometry can be analyzed.
- The retrieved parameters can be chosen from a large set of atmospheric (e.g., volume mixing ratio of gases or aerosol optical depth), surface (e.g., Lambertian reflection), and instrument (e.g., spectral shift or instrument line shape parameters) parameters.
- The software uses an accurate, state-of-the-art, multiple-scattering radiative transfer code combined with an efficient polarization approximation to simulate measured spectra.
- The software enables fast and highly accurate simulations of broad spectral ranges by an optional parallelization of the frequency processing in the radiative transfer model.
This work was done by James McDuffie, Mike M. Smyth, Vijay Natraj, and Edwin Sarkissian of Caltech; Robert Spurr of RT Solutions Inc.; and Christopher O’Dell of the Colorado State University for NASA’s Jet Propulsion Laboratory.
The software used in this innovation is available for commercial licensing. Please contact Dan Broderick at
This Brief includes a Technical Support Package (TSP).
The OCO-2 Level 2 Retrieval Algorithm
(reference NPO-49044) is currently available for download from the TSP library.
Don't have an account?
Overview
The document is a Technical Support Package for the OCO-2 Level 2 Retrieval Algorithm, developed by NASA's Jet Propulsion Laboratory (JPL) under a contract with the National Aeronautics and Space Administration (NASA). It serves as a comprehensive guide to the algorithm used for retrieving atmospheric carbon dioxide (CO2) data from the OCO-2 satellite, which is crucial for understanding global carbon cycles and climate change.
The document outlines the objectives and measurement approach of the OCO-2 mission, emphasizing its role in monitoring greenhouse gases. It details the algorithm's structure, including the forward model that simulates radiative transfer processes, which are essential for interpreting the satellite's observations. The forward model incorporates various optical properties, solar spectrum models, and instrument characteristics to accurately quantify gas concentrations in the atmosphere.
Key components of the algorithm include the handling of multiple scattering contributions and the sensitivity of the retrieval process to changes in gas abundances, particularly for gases like O2 and CO2 that exhibit rapid absorption variations at near-infrared (NIR) wavelengths. The document highlights the challenges posed by the narrow vibration-rotation lines of these gases, which require high spectral resolving power for accurate measurements.
The document also discusses the importance of the state vector, which represents the atmospheric conditions being analyzed, and the inverse method used to derive gas concentrations from the observed data. It includes sections on error analysis, covariance matrices, and the correlation of CO2 measurements with other atmospheric parameters.
Additionally, the document provides a history of revisions and updates to the algorithm, ensuring that users are aware of the latest developments and improvements. It emphasizes the collaborative nature of the research and the technological advancements achieved through the OCO-2 mission.
Overall, this Technical Support Package serves as a vital resource for researchers and practitioners in the field of atmospheric science, providing detailed insights into the methodologies and technologies employed in the OCO-2 mission to enhance our understanding of carbon dynamics and their implications for climate change.
