@article{fdi:010060873,
  title = {{D}ecadal predictability of the {A}tlantic meridional overturning circulation and climate in the {IPSL}-{CM}5{A}-{LR} model},
  author = {{P}ersechino, {A}. and {M}ignot, {J}uliette and {S}wingedouw, {D}. and {L}abetoulle, {S}. and {G}uilyardi, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study explores the decadal potential predictability of the {A}tlantic {M}eridional {O}verturning {C}irculation ({AMOC}) as represented in the {IPSL}-{CM}5{A}-{LR} model, along with the predictability of associated oceanic and atmospheric fields. {U}sing a 1000-year control run, we analyze the prognostic potential predictability ({PPP}) of the {AMOC} through ensembles of simulations with perturbed initial conditions. {B}ased on a measure of the ensemble spread, the modelled {AMOC} has an average predictive skill of 8 years, with some degree of dependence on the {AMOC} initial state. {D}iagnostic potential predictability of surface temperature and precipitation is also identified in the control run and compared to the {PPP}. {B}oth approaches clearly bring out the same regions exhibiting the highest predictive skill. {G}enerally, surface temperature has the highest skill up to 2 decades in the far {N}orth {A}tlantic ocean. {T}here are also weak signals over a few oceanic areas in the tropics and subtropics. {P}redictability over land is restricted to the coastal areas bordering oceanic predictable regions. {P}otential predictability at interannual and longer timescales is largely absent for precipitation in spite of weak signals identified mainly in the {N}ordic {S}eas. {R}egions of weak signals show some dependence on {AMOC} initial state. {A}ll the identified regions are closely linked to decadal {AMOC} fluctuations suggesting that the potential predictability of climate arises from the mechanisms controlling these fluctuations. {E}vidence for dependence on {AMOC} initial state also suggests that studying skills from case studies may prove more useful to understand predictability mechanisms than computing average skill from numerous start dates.},
  keywords = {{D}ecadal climate predictability ; {A}tlantic meridional overturning circulation ; {D}iagnostic and prognostic potential predictability ; {O}cean and climate dynamics ; {OCEAN} {ATLANTIQUE} ; {ZONE} {MERIDIONALE}},
  booktitle = {{P}resentation and analysis of the {IPSL} and {CNRM} climate models used in {CMIP}5},
  journal = {{C}limate {D}ynamics},
  volume = {40},
  numero = {9-10},
  pages = {2359--2380},
  ISSN = {0930-7575},
  year = {2013},
  DOI = {10.1007/s00382-012-1466-1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010060873},
}