Mostrar el registro sencillo del ítem

dc.contributor.author
Merryfield, William  
dc.contributor.author
Doblas Reyes, Francisco  
dc.contributor.author
Ferranti, Laura  
dc.contributor.author
Jeong, Jee-Hoon  
dc.contributor.author
Orsolini, Yvan  
dc.contributor.author
Saurral, Ramiro Ignacio  
dc.contributor.author
Scaife, Adam  
dc.contributor.author
Tolstykh, Mikhail  
dc.contributor.author
Rixen, Michel  
dc.date.available
2018-09-19T19:34:08Z  
dc.date.issued
2017-11  
dc.identifier.citation
Merryfield, William; Doblas Reyes, Francisco; Ferranti, Laura; Jeong, Jee-Hoon; Orsolini, Yvan; et al.; Advancing Climate Forecasting; American Geophysical Union; Eos; 11-2017; 1-7  
dc.identifier.issn
0096-3941  
dc.identifier.uri
http://hdl.handle.net/11336/60306  
dc.description.abstract
Climate forecasts predict weather averages and other climatic properties from a few weeks to a few years in advance. Increasingly, forecasters are using comprehensive models of Earth?s climate system to make such predictions. Researchers also use climate models to project forced changes many decades into the future under assumed scenarios for human influence. Those simulations typically start in preindustrial times, so far in the past that details of their initial states have little influence in the present era. By contrast, climate forecasts begin from more recent observed climate system states, much like weather forecasts. For this reason, they are sometimes referred to as ?initialized climate predictions.? Climate forecasts are produced at numerous operational [Graham et al., 2011] and research centers worldwide. Models and approaches vary, and by coordinating research efforts, the modeling community can make even greater progress. The Working Group on Subseasonal to Interdecadal Prediction (WGSIP) of the World Climate Research Programme (WCRP) facilitates such coordination through a program of numerical experimentation?evaluating model responses to different inputs?aimed at assessing and improving climate forecasts. WGSIP currently supports a project that archives hindcasts; this is a major community resource for climate forecasting research. It also supports three additional targeted research projects aimed at advancing specific aspects of climate forecasting. These projects examine how well climate forecast models represent global influences of tropical rainfall, assess how snow predictably influences climate, and study how model drifts and biases develop and affect climate forecasts.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Geophysical Union  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Climate Forecasts  
dc.subject
Seasonal  
dc.subject
Chfp  
dc.subject
Decadal  
dc.subject.classification
Meteorología y Ciencias Atmosféricas  
dc.subject.classification
Ciencias de la Tierra y relacionadas con el Medio Ambiente  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Advancing Climate Forecasting  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-09-07T13:51:55Z  
dc.journal.pagination
1-7  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Merryfield, William. Canadian Centre for Climate Modelling and Analysis; Canadá  
dc.description.fil
Fil: Doblas Reyes, Francisco. Barcelona Supercomputing Center; España  
dc.description.fil
Fil: Ferranti, Laura. European Centre for Medium-Range Weather Forecasts; Reino Unido  
dc.description.fil
Fil: Jeong, Jee-Hoon. Chonnam National University; Corea del Sur  
dc.description.fil
Fil: Orsolini, Yvan. Norwegian Institute for Air Research; Noruega  
dc.description.fil
Fil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina  
dc.description.fil
Fil: Scaife, Adam. Met Office Hadley Centre; Reino Unido  
dc.description.fil
Fil: Tolstykh, Mikhail. Russian Academy of Sciences. Institute of Numerical Mathematics; Argentina  
dc.description.fil
Fil: Rixen, Michel. World Meteorological Organization; Suiza  
dc.journal.title
Eos  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://eos.org/project-updates/advancing-climate-forecasting  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1029/2017EO086891