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dc.contributor.authorGarcía Manzanas, Rodrigo 
dc.contributor.authorTorralba, Verónica
dc.contributor.authorLledó Ponsati, Llorenç
dc.contributor.authorBretonnière, Pierre-Antoine
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2022-11-30T14:16:01Z
dc.date.available2022-11-30T14:16:01Z
dc.date.issued2022-09-16
dc.identifier.issn0094-8276
dc.identifier.issn1944-8007
dc.identifier.urihttps://hdl.handle.net/10902/26726
dc.description.abstractOne of the key quality aspects in a probabilistic prediction is its reliability. However, this property is difficult to estimate in the case of seasonal forecasts due to the limited size of most of the hindcasts that are available nowadays. To shed light on this issue, this work presents a detailed analysis of how the ensemble size, the hindcast length and the number of points pooled together within a particular region affect the resulting reliability estimates. To do so, we build on 42 land reference regions recently defined for the IPCC-AR6 and assess the reliability of global seasonal forecasts of temperature and precipitation from the European Center for Medium Weather Forecasts SEAS5 prediction system, which is compared against its predecessor, System4. Our results indicate that whereas longer hindcasts and larger ensembles lead to increased reliability estimates, the number of points that are pooled together within a homogeneous climate region is much less relevant.es_ES
dc.description.sponsorshipThis research has been partially supported by the AfriCultuReS (“Enhancing Food Security in African Agricultural Systems with the Support of Remote Sensing”) and FOCUS-Africa projects, which received funding from the European Union's Horizon 2020 Research and Innovation Framework Programme under grant agreements No. 77465 [i.e. 774652] and 869575, respectively.es_ES
dc.format.extent12 p.es_ES
dc.language.isoenges_ES
dc.publisherAmerican Geophysical Uniones_ES
dc.rightsAttribution-NonCommercial 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceGeophysical Research Letters, 2022, 49(17), e2021GL094662es_ES
dc.titleOn the reliability of global seasonal forecasts: sensitivity to ensemble size, hindcast length and region definitiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/774652/EU/Enhancing Food Security in AFRIcan AgriCULTUral Systems with the Support of REmote Sensing/AFRICULTURES/es_ES
dc.identifier.DOI10.1029/2021GL094662
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial 4.0 International