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High‐resolution reconstruction of a tracer dispersion event: application to ETEX
Author(s) -
Bocquet Marc
Publication year - 2007
Publication title -
quarterly journal of the royal meteorological society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.744
H-Index - 143
eISSN - 1477-870X
pISSN - 0035-9009
DOI - 10.1002/qj.64
Subject(s) - tracer , data assimilation , computer science , gaussian , prior probability , algorithm , event (particle physics) , principle of maximum entropy , environmental science , remote sensing , meteorology , data mining , geology , artificial intelligence , physics , bayesian probability , quantum mechanics , nuclear physics
In a previous two‐part paper, new methods for reconstructing the source of an atmospheric tracer at regional scale were developed. Specifically, the ‘maximum entropy on the mean’ (MEM) method was extended to large (though linear) data assimilation problems. Tests using twin experiments and a limited subset of the data from the European Tracer Experiment (ETEX) were performed. Although temporal reconstruction knowing the location of the source was satisfying, a full three‐dimensional reconstruction with real data was still out of reach. In this paper, using the MEM method and some of its refinements, a reconstruction using all ETEX‐I measurements at a resolution of 1.125 × 1.125 × 1 h is shown to be possible. This allows for a reconstruction of the full dispersion event. The MEM retrieval of the tracer plume using what is believed to be a good prior is then compared to retrievals using other priors, including Gaussian priors. Eventually, a reconstruction using all data sequentially in time (rather than all together) is obtained. This helps define what a maximum‐entropy filter applied to sequential data assimilation of a linear tracer should be able to do, with a view to an efficient emergency response in case of an accidental release of pollutant. Copyright © 2007 Royal Meteorological Society