Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

Characterization of uncertainties in atmospheric trace gas inversions using hierarchical Bayesian methods

We present a hierarchical Bayesian method for atmospheric trace gas inversions. This method is used to estimate emissions of trace gases as well as "hyper-parameters" that characterize the probability density functions (PDFs) of the a priori emissions and model-measurement covariances. By...

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Bibliographic Details
Main Authors: Rigby, M. (Author), Zammit-Mangion, A. (Author), Manning, Alistair J. (Author), Fraser, P. J. (Author), Harth, C. M. (Author), Kim, K.-R (Author), Krummel, P. B. (Author), Li, S. (Author), O'Doherty, Simon (Author), Park, S. (Author), Salameh, P. K. (Author), Steele, L. P. (Author), Weiss, R. F. (Author), Ganesan, Anita Lakshmi (Contributor), Prinn, Ronald G. (Contributor), Muhle, Jens (Author)
Other Authors: Massachusetts Institute of Technology. Center for Global Change Science (Contributor)
Format: Article
Language:English
Published: Copernicus GmbH, 2014-06-16T19:06:05Z.
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