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On the assignment of prior errors in Bayesian inversions of CO 2 surface fluxes
Author(s) -
Chevallier Frédéric,
Viovy Nicolas,
Reichstein Markus,
Ciais Philippe
Publication year - 2006
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2006gl026496
Subject(s) - pointwise , covariance , bayesian probability , prior probability , eddy covariance , multivariate normal distribution , gaussian , inversion (geology) , mathematics , environmental science , statistics , multivariate statistics , geology , physics , mathematical analysis , ecology , paleontology , quantum mechanics , ecosystem , structural basin , biology
For the estimation of surface CO 2 fluxes from atmospheric concentration measurements, most often Bayesian approaches have been adopted. As with all Bayesian techniques the definition of prior probability distributions is a critical step in the analysis. However, practical considerations usually guide the definition of prior information rather than objective criterions. In this paper, in situ CO 2 flux pointwise measurements made by the eddy‐covariance technique are used to estimate the errors of prior fluxes provided by the prognostic carbon‐water‐energy model ORCHIDEE. The results contradict the usual convenient assumption of a multivariate Gaussian distribution. The errors of ORCHIDEE have a heavier‐tail distribution with a linear temporal dependency after the second lag day and no particular spatial structure. Such error distribution significantly complicates the inversion of CO 2 surface fluxes.