A hidden semi-Markov model for characterising regime shifts in ocean density variability
Economou, T; Menary, M
Date: 26 August 2019
Journal
Journal of the Royal Statistical Society: Series C
Publisher
Wiley / Royal Statistical Society
Publisher DOI
Abstract
Societally important decadal predictions of temperature and precipitation over
Europe are largely affected by variability in the North Atlantic Ocean. Within
this region, the Labrador Sea is of particular importance due its link between
surface-driven density variability and the Atlantic Meridional Overturning Circulation (AMOC). ...
Societally important decadal predictions of temperature and precipitation over
Europe are largely affected by variability in the North Atlantic Ocean. Within
this region, the Labrador Sea is of particular importance due its link between
surface-driven density variability and the Atlantic Meridional Overturning Circulation (AMOC). Using physical justifications, we propose a statistical model
to describe the temporal variability of ocean density in terms of salinity-driven
and temperature-driven density. This is a hidden semi-Markov model that allows for either a salinity-driven or a temperature-driven ocean density regime,
such that the persistence in each regime is governed probabilistically by a semiMarkov chain. The model is fitted in the Bayesian framework, and a reversible
MCMC algorithm is proposed to deal with a single-regime scenario. The model
is first applied to a reanalysis data set, where model checking measures are also
proposed. Then it is applied to data from 43 climate models to investigate
whether and how ocean density variability differs between them and also the
reanalysis data. Parameter estimates relating to the mean holding time for each
regime are used to establish a link between regime behaviour and the AMOC.
Mathematics and Statistics
Faculty of Environment, Science and Economy
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