Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian appro...
Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields
About this item
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Author / Creator
Publisher
Katlenburg-Lindau: Copernicus GmbH
Journal title
Language
English
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Publication information
Publisher
Katlenburg-Lindau: Copernicus GmbH
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Scope and Contents
Contents
We present a method to infer spatially and spatio-temporally correlated emissions of greenhouse gases from atmospheric measurements and a chemical transport model.
The method allows fast computation of spatial emissions using a hierarchical Bayesian framework as an alternative to Markov chain Monte Carlo algorithms.
The spatial emissions foll...
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Full title
Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_1b399999827d44a480356dd37e05732d
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_1b399999827d44a480356dd37e05732d
Other Identifiers
ISSN
1991-9603,1991-959X,1991-962X
E-ISSN
1991-9603,1991-962X
DOI
10.5194/gmd-13-2095-2020
