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dc.contributor.authorTerrado, Marta
dc.contributor.authorLLedó, Llorenç
dc.contributor.authorBojovic, Dragana
dc.contributor.authorLera St. Clair, Asun
dc.contributor.authorSoret, Albert
dc.contributor.authorDoblas Reyes, Francisco J.
dc.contributor.authorGarcía Manzanas, Rodrigo 
dc.contributor.authorSan Martín Segura, Daniel
dc.contributor.authorChristel, Isadora
dc.date.accessioned2019-12-05T09:54:17Z
dc.date.available2020-04-30T02:45:25Z
dc.date.issued2019-10-24
dc.identifier.issn0003-0007
dc.identifier.issn1520-0477
dc.identifier.otherCGL2017-85791-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/17401
dc.description.abstractClimate predictions, from three weeks to a decade into the future, can provide invaluable information for climate-sensitive socioeconomic sectors, such as renewable energy, agriculture, or insurance. However, communicating and interpreting these predictions is not straightforward. Barriers hindering user uptake include a terminology gap between climate scientists and users, the difficulties of dealing with probabilistic outcomes for decision-making, and the lower skill of climate predictions compared to the skill of weather forecasts. This paper presents a gaming approach to break communication and understanding barriers through the application of the Weather Roulette conceptual framework. In the game, the player can choose between two forecast options, one that uses ECMWF seasonal predictions against one using climatology-derived probabilities. For each forecast option, the bet is spread proportionally to the predicted probabilities, either in a single year game or a game for the whole period of 33 past years. This paper provides skill maps of forecast quality metrics commonly used by the climate prediction community (e.g., ignorance skill score and ranked probability skill score), which in the game are linked to metrics easily understood by the business sector (e.g., interest rate and return on investment). In a simplified context, we illustrate how in skillful regions the economic benefits of using ECMWF predictions arise in the long term and are higher than using climatology. This paper provides an example of how to convey the usefulness of climate predictions and transfer the knowledge from climate science to potential users. If applied, this approach could provide the basis for a better integration of knowledge about climate anomalies into operational and managerial processes.es_ES
dc.description.sponsorshipThe research leading to these results has received funding from the EU FP7 Programme under Grant Agreement 308291 (EUPORIAS), the EU H2020 Programme under Grant Agreements 776787 (S2S4E) and 776613 (EUCP), and the Ministerio de Economía y Competitividad (MINECO) as part of the CLINSA Project CGL2017-85791-R. It is also part of the Copernicus Climate Change Service (C3S) (Framework Agreement C3S_441_Lot2_CEA), a program being implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf of the European Commission.es_ES
dc.format.extent13 p.es_ES
dc.language.isoenges_ES
dc.publisherAmerican Meteorological Societyes_ES
dc.rights© 2019 American Meteorological Society. AMS´s Full Copyright Notice: https://www.ametsoc.org/ams/index.cfm/publications/authors/journal-and-bams-authors/author-resources/copyright-information/copyright-policy/es_ES
dc.sourceBulletin of the American Meteorological Society, 2019, 100(10), 1909-1921es_ES
dc.titleThe weather roulette: a game to communicate the usefulness of probabilistic climate predictionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1175/BAMS-D-18-0214.1es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7/308291/EU/EUropean Provision Of Regional Impact Assessment on a Seasonal-to-decadal timescale/EUPORIAS/es_ES
dc.identifier.DOI10.1175/BAMS-D-18-0214.1
dc.type.versionpublishedVersiones_ES


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