Articles | Volume 15, issue 22
Geosci. Model Dev., 15, 8295–8323, 2022
https://doi.org/10.5194/gmd-15-8295-2022

Special issue: The Lagrangian particle dispersion model FLEXPART

Geosci. Model Dev., 15, 8295–8323, 2022
https://doi.org/10.5194/gmd-15-8295-2022
Model evaluation paper
18 Nov 2022
Model evaluation paper | 18 Nov 2022

A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions

Martin Vojta et al.

Data sets

Multi-laboratory compilation of atmospheric sulfure hexafluoride data for the period 1983-2017; obspack_sf6_1_v2.1.1_2018-08-17 NOAA Carbon Cycle Group ObsPack Team https://doi.org/10.25925/20180817

Model code and software

Supplementary for Vojta et al., 2022, GMD Martin Vojta https://doi.org/10.25365/phaidra.339

FLEXPART 8-CTM-1.1: Atmospheric Lagrangian Particle Dispersion Model for global tracer transport (8-CTM-1.1) Stephan Henne, Dominik Brunner, Christine Groot Zwaaftink, and Andreas Stohl https://doi.org/10.5281/zenodo.1249190

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Short summary
In light of recent global warming, we aim to improve methods for modeling greenhouse gas emissions in order to support the successful implementation of the Paris Agreement. In this study, we investigate certain aspects of a Bayesian inversion method that uses computer simulations and atmospheric observations to improve estimates of greenhouse gas emissions. We explore method limitations, discuss problems, and suggest improvements.