Skillful decadal prediction of unforced southern European summer temperature variations

We assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970–2014. Using a multi-model ensemble average, we show that Southern European (SEU) summer temperatures are hig...

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Main Authors: L F Borchert, V Koul, M B Menary, D J Befort, D Swingedouw, G Sgubin, J Mignot
Format: Article
Language:English
Published: IOP Publishing 2021-01-01
Series:Environmental Research Letters
Subjects:
Online Access:https://doi.org/10.1088/1748-9326/ac20f5
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author L F Borchert
V Koul
M B Menary
D J Befort
D Swingedouw
G Sgubin
J Mignot
author_facet L F Borchert
V Koul
M B Menary
D J Befort
D Swingedouw
G Sgubin
J Mignot
author_sort L F Borchert
collection DOAJ
description We assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970–2014. Using a multi-model ensemble average, we show that Southern European (SEU) summer temperatures are highly predictable for up to ten years in CMIP6. Much of this predictive skill, is related to the externally forced response: historical simulations explain about 90% of observed SEU summer temperature variance. Prediction 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. An observed link between unforced SEU summer temperature and preceding spring Eastern North Atlantic—Mediterranean sea surface temperature (SST) motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over Europe. This dynamical-statistical model uses dynamical spring SST predictions to predict European summer temperature, and significantly increases decadal prediction skill of unforced European summer temperature variations, showing significant prediction skill for unforced Southern European summer temperature 2–9 years ahead. As a result, dynamical-statistical models can benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over Europe.
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spelling doaj.art-f165558c696842a085b43686d12d3f4a2023-08-09T15:06:52ZengIOP PublishingEnvironmental Research Letters1748-93262021-01-01161010401710.1088/1748-9326/ac20f5Skillful decadal prediction of unforced southern European summer temperature variationsL F Borchert0https://orcid.org/0000-0002-3232-7409V Koul1M B Menary2https://orcid.org/0000-0002-9627-2056D J Befort3https://orcid.org/0000-0002-2851-0470D Swingedouw4G Sgubin5J Mignot6Sorbonne Universités (SU/CNRS/IRD/MNHN), IPSL Laboratory, Institut Pierre Simon Laplace (IPSL) , Paris, France; Laboratoire de Météorologie Dynamique (LMD), École Normale Supérieure (ENS) , Paris, FranceInstitute of Coastal Systems Analysis and Modeling, Helmholtz-Zentrum Hereon , Geesthacht, Germany; Institute for Oceanography, CEN, Universität Hamburg , Hamburg, GermanySorbonne Universités (SU/CNRS/IRD/MNHN), IPSL Laboratory, Institut Pierre Simon Laplace (IPSL) , Paris, France; Laboratoire de Météorologie Dynamique (LMD), École Normale Supérieure (ENS) , Paris, FranceAtmospheric, Oceanic and Planetary Physics, Department of Physics, University of Oxford , Oxford, United KingdomEPOC, Université de Bordeaux , Pessac, FranceEPOC, Université de Bordeaux , Pessac, FranceSorbonne Universités (SU/CNRS/IRD/MNHN), IPSL Laboratory, Institut Pierre Simon Laplace (IPSL) , Paris, FranceWe assess the capability of decadal prediction simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) archive to predict European summer temperature during the period 1970–2014. Using a multi-model ensemble average, we show that Southern European (SEU) summer temperatures are highly predictable for up to ten years in CMIP6. Much of this predictive skill, is related to the externally forced response: historical simulations explain about 90% of observed SEU summer temperature variance. Prediction 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. An observed link between unforced SEU summer temperature and preceding spring Eastern North Atlantic—Mediterranean sea surface temperature (SST) motivates the application of a dynamical-statistical model to overcome the low summer temperature skill over Europe. This dynamical-statistical model uses dynamical spring SST predictions to predict European summer temperature, and significantly increases decadal prediction skill of unforced European summer temperature variations, showing significant prediction skill for unforced Southern European summer temperature 2–9 years ahead. As a result, dynamical-statistical models can benefit the decadal prediction of variables with initially limited skill beyond the forcing, such as summer temperature over Europe.https://doi.org/10.1088/1748-9326/ac20f5climate predictionCMIP6European summer temperature
spellingShingle L F Borchert
V Koul
M B Menary
D J Befort
D Swingedouw
G Sgubin
J Mignot
Skillful decadal prediction of unforced southern European summer temperature variations
Environmental Research Letters
climate prediction
CMIP6
European summer temperature
title Skillful decadal prediction of unforced southern European summer temperature variations
title_full Skillful decadal prediction of unforced southern European summer temperature variations
title_fullStr Skillful decadal prediction of unforced southern European summer temperature variations
title_full_unstemmed Skillful decadal prediction of unforced southern European summer temperature variations
title_short Skillful decadal prediction of unforced southern European summer temperature variations
title_sort skillful decadal prediction of unforced southern european summer temperature variations
topic climate prediction
CMIP6
European summer temperature
url https://doi.org/10.1088/1748-9326/ac20f5
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