Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 3
Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1237-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-1237-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 3
Development and technical paper
 | 
08 Mar 2021
Development and technical paper |  | 08 Mar 2021

On the model uncertainties in Bayesian source reconstruction using an ensemble of weather predictions, the emission inverse modelling system FREAR v1.0, and the Lagrangian transport and dispersion model Flexpart v9.0.2

Pieter De Meutter, Ian Hoffman, and Kurt Ungar

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Latest update: 23 Nov 2024
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Short summary
Inverse atmospheric transport modelling is an important tool in several disciplines. However, the specification of atmospheric transport model error remains challenging. In this paper, we employ a state-of-the-art ensemble technique combined with a state-of-the-art Bayesian inference algorithm to infer point sources. Our research helps to fill the gap in our understanding of model error in the context of inverse atmospheric transport modelling.
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