Emmanuel Hanert

Prof. Dr. Emmanuel Hanert

orcid

Research Focus & Metrics

Academic Career Length

25Years (2002-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 February 2019 in Frontiers in Marine Science
Verified
Journal Article
Open access
PDF file
BFBaylor Fox-Kemper
Baylor Fox-Kemper
AAAlistair Adcroft
Alistair Adcroft
CBClaus W. Böning
Claus W. Böning
ECEric P. Chassignet
Eric P. Chassignet
ECEnrique Curchitser
Enrique Curchitser
SYStephen G. Yeager
Stephen G. Yeager
We revisit the challenges and prospects for ocean circulation models following Griffies et al. (2010). Over the past decade, ocean circulation models evolved through improved understanding, numerics, spatial discretization, grid configurations, parameterizations, data assimilation, environmental monitoring, and process-level observations and modeling. Important large scale applications over the last decade are simulations of the Southern Ocean, the Meridional Overturning Circulation and its variability, and regional sea level change. Submesoscale variability is now routinely resolved in process models and permitted in a few global models, and submesoscale effects are parameterized in most global models. The scales where nonhydrostatic effects become important are beginning to be resolved in regional and process models. Coupling to sea ice, ice shelves, and high-resolution atmospheric models has stimulated new ideas and driven improvements in numerics. Observations have provided insight into turbulence and mixing around the globe and its consequences are assessed through perturbed physics models. Relatedly, parameterizations of the mixing and overturning processes in boundary layers and the ocean interior have improved. New diagnostics being used for evaluating models alongside present and novel observations are briefly referenced. The overall goal is summarizing new developments in ocean modeling, including: how new and existing observations can be used, what modeling challenges remain, and how simulations can be used to support observations.

1 January 2014 in Ecological Modelling
Verified
Journal Article
Closed access
CTChristopher J. Thomas
Christopher J. Thomas
JLJonathan Lambrechts
Jonathan Lambrechts
EWEric Wolanski
Eric Wolanski
VTVincent Traag
Vincent Traag
VBVincent D. Blondel
Vincent D. Blondel
EHEmmanuel Hanert
Emmanuel Hanert

1 August 2008 in Estuarine, Coastal and Shelf Science
Verified
Journal Article
Closed access
JLJonathan Lambrechts
Jonathan Lambrechts
EHEmmanuel Hanert
Emmanuel Hanert
Eric DeleersnijderEric Deleersnijder
Eric Deleersnijder
PBPaul-Emile Bernard
Paul-Emile Bernard
VLVincent Legat
Vincent Legat
EWEric Wolanski
Eric Wolanski

1 January 2005 in Ocean Modelling
Verified
Journal Article
Closed access
EHEmmanuel Hanert
Emmanuel Hanert
DRDaniel Y. Le Roux
Daniel Y. Le Roux
VLVincent Legat
Vincent Legat
Eric DeleersnijderEric Deleersnijder
Eric Deleersnijder

1 June 2011 in Journal of Theoretical Biology
Verified
Journal Article
Closed access
EHEmmanuel Hanert
Emmanuel Hanert
ESEva Schumacher
Eva Schumacher
Eric DeleersnijderEric Deleersnijder
Eric Deleersnijder

1 December 2020 in Frontiers in Marine Science
Verified
Journal Article
Open access
PDF file
TDThomas Dobbelaere
Thomas Dobbelaere
EMErinn M. Muller
Erinn M. Muller
LGLewis J. Gramer
Lewis J. Gramer
DHDaniel M. Holstein
Daniel M. Holstein
EHEmmanuel Hanert
Emmanuel Hanert
For the last six years, the Florida Reef Tract (FRT) has been experiencing an outbreak of the Stony Coral Tissue Loss Disease (SCTLD). First reported off the coast of Miami-Dade County in 2014, the SCTLD has since spread throughout the entire FRT with the exception of the Dry Tortugas. However, the causative agent for this outbreak is currently unknown. Here we show how a high-resolution bio-physical model coupled with a modified patch Susceptible-Infectious-Removed epidemic model can characterize the potential causative agent(s) of the disease and its vector. In the present study, the agent is assumed to be transported within composite material (e.g., coral mucus, dying tissues, and/or resuspended sediments) driven by currents and potentially persisting in the water column for extended periods of time. In this framework, our simulations suggest that the SCTLD is likely to be propagated within neutrally buoyant material driven by mean barotropic currents. Calibration of our model parameters with field data shows that corals are diseased within a mean transmission time of 6.45 days, with a basic reproduction number slightly above 1. Furthermore, the propagation speed of the disease through the FRT is shown to occur for a well-defined range of values of a disease threshold, defined as the fraction of diseased corals that causes an exponential growth of the disease in the reef site. Our results present a new connectivity-based approach to understand the spread of the SCTLD through the FRT. Such a method can provide a valuable complement to field observations and lab experiments to support the management of the epidemic as well as the identification of its causative agent.