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dc.contributor.authorArdilouze, Constantin
dc.contributor.authorBatté, L.
dc.contributor.authorBunzel, F.
dc.contributor.authorDecremer, D.
dc.contributor.authorDéqué, M.
dc.contributor.authorDoblas-Reyes, Francisco
dc.contributor.authorDouville, H.
dc.contributor.authorFereday, D.
dc.contributor.authorGuemas, Virginie
dc.contributor.authorMacLachlan, C.
dc.contributor.authorMüller, W.
dc.contributor.authorProdhomme, Chloe
dc.contributor.otherBarcelona Supercomputing Center
dc.date.accessioned2017-11-17T14:30:19Z
dc.date.available2018-12-01T01:31:20Z
dc.date.issued2017-12-01
dc.identifier.citationArdilouze, C. [et al.]. Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability. "Climate Dynamics", 1 Desembre 2017, vol. 49, núm. 11-12, p. 3959-3974.
dc.identifier.issn0930-7575
dc.identifier.urihttp://hdl.handle.net/2117/110866
dc.description.abstractLand surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992–2010 period performed by five different global coupled ocean–atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land–atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.
dc.description.sponsorshipThe authors thank Jeff Knight (Met Office Hadley Centre) for his constructive comments on earlier versions of this manuscript. The research leading to these results received funding from the European Union Seventh Framework Programme (FP7/2007–2013) SPECS project (Grant Agreement Number 308378) and H2020 Framework Programme IMPREX project (Grant Agreement Number 641811). Constantin Ardilouze was also supported by the BSC Centro de Excelencia Severo Ochoa Programme.
dc.format.extent16 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Energies
dc.subject.lcshSeasonal climate forecasting
dc.subject.lcshClimatology
dc.subject.lcshAtmosphere--Computer simulation
dc.subject.otherLand-surface initialization
dc.subject.otherSeasonal forecasting
dc.subject.otherLand–atmosphere coupling
dc.subject.otherMulti-model Ensemble forecast
dc.titleMulti-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability
dc.typeArticle
dc.subject.lemacClima--Observacions
dc.subject.lemacClimatologia
dc.identifier.doi10.1007/s00382-017-3555-7
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s00382-017-3555-7
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/EC/H2020/641811/EU/IMproving PRedictions and management of hydrological EXtremes/IMPREX
local.citation.publicationNameClimate Dynamics
local.citation.volume49
local.citation.number11-12
local.citation.startingPage3959
local.citation.endingPage3974


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