Articles | Volume 9, issue 11
https://doi.org/10.5194/gmd-9-4297-2016
https://doi.org/10.5194/gmd-9-4297-2016
Development and technical paper
 | 
25 Nov 2016
Development and technical paper |  | 25 Nov 2016

LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

Ondřej Tichý, Václav Šmídl, Radek Hofman, and Andreas Stohl

Data sets

Least Square with Adaptive Prior Covariance (LS-APC) algorithm O. Tichý, V. Šmídl, R. Hofman, and A. Stohl http://www.utia.cz/linear_inversion_methods

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Short summary
Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. We formulate a probabilistic model, where a full Bayesian estimation allows estimation of all tuning parameters from the measurements. The proposed algorithm is tested and compared with the state-of-the-art method on data from the European Tracer Experiment (ETEX), where advantages of the new method are demonstrated.