A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm

Laughner, J. L., Roche, S., Kiel, M., Toon, G. C., Wunch, D., et al. (2023). A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm. Atmospheric Measurement Techniques, doi:https://doi.org/10.5194/amt-16-1121-2023

Title A new algorithm to generate a priori trace gas profiles for the GGG2020 retrieval algorithm
Genre Article
Author(s) J. L. Laughner, S. Roche, M. Kiel, G. C. Toon, D. Wunch, B. C. Baier, S. Biraud, H. Chen, R. Kivi, T. Laemmel, K. McKain, P. Quéhé, C. Rousogenous, Britton Stephens, K. Walker, P. O. Wennberg
Abstract Optimal estimation retrievals of trace gas total columns require prior vertical profiles of the gases retrieved to drive the forward model and ensure the retrieval problem is mathematically well posed. For well-mixed gases, it is possible to derive accurate prior profiles using an algorithm that accounts for general patterns of atmospheric transport coupled with measured time series of the gases in questions. Here we describe the algorithm used to generate the prior profiles for GGG2020, a new version of the GGG retrieval that is used to analyze spectra from solar-viewing Fourier transform spectrometers, including the Total Carbon Column Observing Network (TCCON). A particular focus of this work is improving the accuracy of CO2, CH4, N2O, HF, and CO across the tropopause and into the lower stratosphere. We show that the revised priors agree well with independent in situ and space-based measurements and discuss the impact on the total column retrievals.
Publication Title Atmospheric Measurement Techniques
Publication Date Mar 7, 2023
Publisher's Version of Record https://doi.org/10.5194/amt-16-1121-2023
OpenSky Citable URL https://n2t.org/ark:/85065/d7nc654z
OpenSky Listing View on OpenSky
EOL Affiliations RAF

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