@article{fdi:010082829,
  title = {{S}killful decadal prediction of unforced southern {E}uropean summer temperature variations},
  author = {{B}orchert, {L}. {F}. and {K}oul, {V}. and {M}enary, {M}. {B}. and {B}efort, {D}. {J}. and {S}wingedouw, {D}. and {S}gubin, {G}. and {M}ignot, {J}uliette},
  editor = {},
  language = {{ENG}},
  abstract = {{W}e assess the capability of decadal prediction simulations from the {C}oupled {M}odel {I}ntercomparison {P}roject phase 6 ({CMIP}6) archive to predict {E}uropean summer temperature during the period 1970-2014. {U}sing a multi-model ensemble average, we show that {S}outhern {E}uropean ({SEU}) summer temperatures are highly predictable for up to ten years in {CMIP}6. {M}uch of this predictive skill, is related to the externally forced response: historical simulations explain about 90% of observed {SEU} summer temperature variance. {P}rediction skill for the unforced signal of {SEU} summer temperature is low: initialized model simulations explain less than 10% of observed variance after removing the externally forced response. {A}n observed link between unforced {SEU} summer temperature and preceding spring {E}astern {N}orth {A}tlantic-{M}editerranean sea surface temperature ({SST}) motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over {E}urope. {T}his dynamical-statistical model uses dynamical spring {SST} predictions to predict {E}uropean summer temperature, and significantly increases decadal prediction skill of unforced {E}uropean summer temperature variations, showing significant prediction skill for unforced {S}outhern {E}uropean summer temperature 2-9 years ahead. {A}s a result, dynamical-statistical models can benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over {E}urope.},
  keywords = {climate prediction ; {CMIP}6 ; {E}uropean summer temperature ; {EUROPE} ; {MEDITERRANEE} ; {ATLANTIQUE} {NORD} {EST}},
  booktitle = {},
  journal = {{E}nvironmental {R}esearch {L}etters},
  volume = {16},
  numero = {10},
  pages = {104017 [10 ]},
  ISSN = {1748-9326},
  year = {2021},
  DOI = {10.1088/1748-9326/ac20f5},
  URL = {https://www.documentation.ird.fr/hor/fdi:010082829},
}