Advancing Climate Forecasting

Autores
Merryfield, William; Doblas Reyes, Francisco; Ferranti, Laura; Jeong, Jee-Hoon; Orsolini, Yvan; Saurral, Ramiro Ignacio; Scaife, Adam; Tolstykh, Mikhail; Rixen, Michel
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
Fil: Merryfield, William. Canadian Centre for Climate Modelling and Analysis; Canadá
Fil: Doblas Reyes, Francisco. Barcelona Supercomputing Center; España
Fil: Ferranti, Laura. European Centre for Medium-Range Weather Forecasts; Reino Unido
Fil: Jeong, Jee-Hoon. Chonnam National University; Corea del Sur
Fil: Orsolini, Yvan. Norwegian Institute for Air Research; Noruega
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
Fil: Scaife, Adam. Met Office Hadley Centre; Reino Unido
Fil: Tolstykh, Mikhail. Russian Academy of Sciences. Institute of Numerical Mathematics; Argentina
Fil: Rixen, Michel. World Meteorological Organization; Suiza
Materia
climate forecasts
seasonal
CHFP
decadal
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/60306
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Advancing Climate ForecastingMerryfield, WilliamDoblas Reyes, FranciscoFerranti, LauraJeong, Jee-HoonOrsolini, YvanSaurral, Ramiro IgnacioScaife, AdamTolstykh, MikhailRixen, Michelclimate forecastsseasonalCHFPdecadalhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Climate 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.Fil: Merryfield, William. Canadian Centre for Climate Modelling and Analysis; CanadáFil: Doblas Reyes, Francisco. Barcelona Supercomputing Center; EspañaFil: Ferranti, Laura. European Centre for Medium-Range Weather Forecasts; Reino UnidoFil: Jeong, Jee-Hoon. Chonnam National University; Corea del SurFil: Orsolini, Yvan. Norwegian Institute for Air Research; NoruegaFil: 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; ArgentinaFil: Scaife, Adam. Met Office Hadley Centre; Reino UnidoFil: Tolstykh, Mikhail. Russian Academy of Sciences. Institute of Numerical Mathematics; ArgentinaFil: Rixen, Michel. World Meteorological Organization; SuizaAmerican Geophysical Union2017-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/60306Merryfield, William; Doblas Reyes, Francisco; Ferranti, Laura; Jeong, Jee-Hoon; Orsolini, Yvan; et al.; Advancing Climate Forecasting; American Geophysical Union; Eos; 11-2017; 1-70096-3941CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://eos.org/project-updates/advancing-climate-forecastinginfo:eu-repo/semantics/altIdentifier/doi/10.1029/2017EO086891info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:08:36Zoai:ri.conicet.gov.ar:11336/60306instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:08:36.742CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Advancing Climate Forecasting
title Advancing Climate Forecasting
spellingShingle Advancing Climate Forecasting
Merryfield, William
climate forecasts
seasonal
CHFP
decadal
title_short Advancing Climate Forecasting
title_full Advancing Climate Forecasting
title_fullStr Advancing Climate Forecasting
title_full_unstemmed Advancing Climate Forecasting
title_sort Advancing Climate Forecasting
dc.creator.none.fl_str_mv Merryfield, William
Doblas Reyes, Francisco
Ferranti, Laura
Jeong, Jee-Hoon
Orsolini, Yvan
Saurral, Ramiro Ignacio
Scaife, Adam
Tolstykh, Mikhail
Rixen, Michel
author Merryfield, William
author_facet Merryfield, William
Doblas Reyes, Francisco
Ferranti, Laura
Jeong, Jee-Hoon
Orsolini, Yvan
Saurral, Ramiro Ignacio
Scaife, Adam
Tolstykh, Mikhail
Rixen, Michel
author_role author
author2 Doblas Reyes, Francisco
Ferranti, Laura
Jeong, Jee-Hoon
Orsolini, Yvan
Saurral, Ramiro Ignacio
Scaife, Adam
Tolstykh, Mikhail
Rixen, Michel
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv climate forecasts
seasonal
CHFP
decadal
topic climate forecasts
seasonal
CHFP
decadal
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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.
Fil: Merryfield, William. Canadian Centre for Climate Modelling and Analysis; Canadá
Fil: Doblas Reyes, Francisco. Barcelona Supercomputing Center; España
Fil: Ferranti, Laura. European Centre for Medium-Range Weather Forecasts; Reino Unido
Fil: Jeong, Jee-Hoon. Chonnam National University; Corea del Sur
Fil: Orsolini, Yvan. Norwegian Institute for Air Research; Noruega
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
Fil: Scaife, Adam. Met Office Hadley Centre; Reino Unido
Fil: Tolstykh, Mikhail. Russian Academy of Sciences. Institute of Numerical Mathematics; Argentina
Fil: Rixen, Michel. World Meteorological Organization; Suiza
description 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/60306
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
0096-3941
CONICET Digital
CONICET
url http://hdl.handle.net/11336/60306
identifier_str_mv 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
0096-3941
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://eos.org/project-updates/advancing-climate-forecasting
info:eu-repo/semantics/altIdentifier/doi/10.1029/2017EO086891
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Geophysical Union
publisher.none.fl_str_mv American Geophysical Union
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842270051534635008
score 13.13397

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