“Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress

Autores
Miyoshi, Takemasa; Lien, Guo-Yuan; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; Tomita, Hirofumi; Nishizawa, Seiya; Yoshida, Ryuji; Adachi, Sachiho A.; Liao, Jianwei; Gerofi, Balazs; Ishikawa, Yutaka; Kunii, Masaru; Ruiz, Juan Jose; Maejima, Yasumitsu; Otsuka, Shigenori; Otsuka, Michiko; Okamoto, Kozo; Seko, Hiromu
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Following the invention of the telegraph, electronic computer, and remote sensing, “big data” is bringing another revolution to weather prediction. As sensor and computer technologies advance, orders of magnitude bigger data are produced by new sensors and high-precision computer simulation or “big simulation.” Data assimilation (DA) is a key to numerical weather prediction (NWP) by integrating the real-world sensor data into simulation. However, the current DA and NWP systems are not designed to handle the “big data” from next-generation sensors and big simulation. Therefore, we propose “big data assimilation” (BDA) innovation to fully utilize the big data. Since October 2013, the Japan's BDA project has been exploring revolutionary NWP at 100-m mesh refreshed every 30 s, orders of magnitude finer and faster than the current typical NWP systems, by taking advantage of the fortunate combination of next-generation technologies: the 10-petaflops K computer, phased array weather radar, and geostationary satellite Himawari-8. So far, a BDA prototype system was developed and tested with real-world retrospective local rainstorm cases. This paper summarizes the activities and progress of the BDA project, and concludes with perspectives toward the post-petascale supercomputing era.
Fil: Miyoshi, Takemasa. RIKEN Advanced Institute for Computational Science; Japón
Fil: Lien, Guo-Yuan. RIKEN Advanced Institute for Computational Science; Japón
Fil: Satoh, Shinsuke. National Institute of Information and Communications Technology; Japón
Fil: Ushio, Tomoo. Osaka University; Japón
Fil: Bessho, Kotaro. Meteorological Satellite Center; Japón
Fil: Tomita, Hirofumi. RIKEN Advanced Institute for Computational Science; Japón
Fil: Nishizawa, Seiya. RIKEN Advanced Institute for Computational Science; Japón
Fil: Yoshida, Ryuji. RIKEN Advanced Institute for Computational Science; Japón
Fil: Adachi, Sachiho A.. RIKEN Advanced Institute for Computational Science; Japón
Fil: Liao, Jianwei. RIKEN Advanced Institute for Computational Science; Japón
Fil: Gerofi, Balazs. RIKEN Advanced Institute for Computational Science; Japón
Fil: Ishikawa, Yutaka. RIKEN Advanced Institute for Computational Science; Japón
Fil: Kunii, Masaru. RIKEN Advanced Institute for Computational Science; Japón
Fil: Ruiz, Juan Jose. RIKEN Advanced Institute for Computational Science; Japón. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Maejima, Yasumitsu. RIKEN Advanced Institute for Computational Science; Japón
Fil: Otsuka, Shigenori. RIKEN Advanced Institute for Computational Science; Japón
Fil: Otsuka, Michiko. RIKEN Advanced Institute for Computational Science; Japón
Fil: Okamoto, Kozo. RIKEN Advanced Institute for Computational Science; Japón
Fil: Seko, Hiromu. Meteorological Research Institute; Japón
Materia
atmospheric mesaurements
computer applications
kalman filtering
optimal control
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:11336/60304
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/60304
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and ProgressMiyoshi, TakemasaLien, Guo-YuanSatoh, ShinsukeUshio, TomooBessho, KotaroTomita, HirofumiNishizawa, SeiyaYoshida, RyujiAdachi, Sachiho A.Liao, JianweiGerofi, BalazsIshikawa, YutakaKunii, MasaruRuiz, Juan JoseMaejima, YasumitsuOtsuka, ShigenoriOtsuka, MichikoOkamoto, KozoSeko, Hiromuatmospheric mesaurementscomputer applicationskalman filteringoptimal controlhttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Following the invention of the telegraph, electronic computer, and remote sensing, “big data” is bringing another revolution to weather prediction. As sensor and computer technologies advance, orders of magnitude bigger data are produced by new sensors and high-precision computer simulation or “big simulation.” Data assimilation (DA) is a key to numerical weather prediction (NWP) by integrating the real-world sensor data into simulation. However, the current DA and NWP systems are not designed to handle the “big data” from next-generation sensors and big simulation. Therefore, we propose “big data assimilation” (BDA) innovation to fully utilize the big data. Since October 2013, the Japan's BDA project has been exploring revolutionary NWP at 100-m mesh refreshed every 30 s, orders of magnitude finer and faster than the current typical NWP systems, by taking advantage of the fortunate combination of next-generation technologies: the 10-petaflops K computer, phased array weather radar, and geostationary satellite Himawari-8. So far, a BDA prototype system was developed and tested with real-world retrospective local rainstorm cases. This paper summarizes the activities and progress of the BDA project, and concludes with perspectives toward the post-petascale supercomputing era.Fil: Miyoshi, Takemasa. RIKEN Advanced Institute for Computational Science; JapónFil: Lien, Guo-Yuan. RIKEN Advanced Institute for Computational Science; JapónFil: Satoh, Shinsuke. National Institute of Information and Communications Technology; JapónFil: Ushio, Tomoo. Osaka University; JapónFil: Bessho, Kotaro. Meteorological Satellite Center; JapónFil: Tomita, Hirofumi. RIKEN Advanced Institute for Computational Science; JapónFil: Nishizawa, Seiya. RIKEN Advanced Institute for Computational Science; JapónFil: Yoshida, Ryuji. RIKEN Advanced Institute for Computational Science; JapónFil: Adachi, Sachiho A.. RIKEN Advanced Institute for Computational Science; JapónFil: Liao, Jianwei. RIKEN Advanced Institute for Computational Science; JapónFil: Gerofi, Balazs. RIKEN Advanced Institute for Computational Science; JapónFil: Ishikawa, Yutaka. RIKEN Advanced Institute for Computational Science; JapónFil: Kunii, Masaru. RIKEN Advanced Institute for Computational Science; JapónFil: Ruiz, Juan Jose. RIKEN Advanced Institute for Computational Science; Japón. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Maejima, Yasumitsu. RIKEN Advanced Institute for Computational Science; JapónFil: Otsuka, Shigenori. RIKEN Advanced Institute for Computational Science; JapónFil: Otsuka, Michiko. RIKEN Advanced Institute for Computational Science; JapónFil: Okamoto, Kozo. RIKEN Advanced Institute for Computational Science; JapónFil: Seko, Hiromu. Meteorological Research Institute; JapónInstitute of Electrical and Electronics Engineers2016-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/60304Miyoshi, Takemasa; Lien, Guo-Yuan; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; et al.; “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress; Institute of Electrical and Electronics Engineers; Proceedings Of The Ieee; 104; 11; 11-2016; 2155-21790018-9219CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1109/JPROC.2016.2602560info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7576655/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:42:13Zoai:ri.conicet.gov.ar:11336/60304instacron: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:34982025-10-15 15:42:14.249CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
title “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
spellingShingle “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
Miyoshi, Takemasa
atmospheric mesaurements
computer applications
kalman filtering
optimal control
title_short “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
title_full “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
title_fullStr “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
title_full_unstemmed “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
title_sort “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress
dc.creator.none.fl_str_mv Miyoshi, Takemasa
Lien, Guo-Yuan
Satoh, Shinsuke
Ushio, Tomoo
Bessho, Kotaro
Tomita, Hirofumi
Nishizawa, Seiya
Yoshida, Ryuji
Adachi, Sachiho A.
Liao, Jianwei
Gerofi, Balazs
Ishikawa, Yutaka
Kunii, Masaru
Ruiz, Juan Jose
Maejima, Yasumitsu
Otsuka, Shigenori
Otsuka, Michiko
Okamoto, Kozo
Seko, Hiromu
author Miyoshi, Takemasa
author_facet Miyoshi, Takemasa
Lien, Guo-Yuan
Satoh, Shinsuke
Ushio, Tomoo
Bessho, Kotaro
Tomita, Hirofumi
Nishizawa, Seiya
Yoshida, Ryuji
Adachi, Sachiho A.
Liao, Jianwei
Gerofi, Balazs
Ishikawa, Yutaka
Kunii, Masaru
Ruiz, Juan Jose
Maejima, Yasumitsu
Otsuka, Shigenori
Otsuka, Michiko
Okamoto, Kozo
Seko, Hiromu
author_role author
author2 Lien, Guo-Yuan
Satoh, Shinsuke
Ushio, Tomoo
Bessho, Kotaro
Tomita, Hirofumi
Nishizawa, Seiya
Yoshida, Ryuji
Adachi, Sachiho A.
Liao, Jianwei
Gerofi, Balazs
Ishikawa, Yutaka
Kunii, Masaru
Ruiz, Juan Jose
Maejima, Yasumitsu
Otsuka, Shigenori
Otsuka, Michiko
Okamoto, Kozo
Seko, Hiromu
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv atmospheric mesaurements
computer applications
kalman filtering
optimal control
topic atmospheric mesaurements
computer applications
kalman filtering
optimal control
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Following the invention of the telegraph, electronic computer, and remote sensing, “big data” is bringing another revolution to weather prediction. As sensor and computer technologies advance, orders of magnitude bigger data are produced by new sensors and high-precision computer simulation or “big simulation.” Data assimilation (DA) is a key to numerical weather prediction (NWP) by integrating the real-world sensor data into simulation. However, the current DA and NWP systems are not designed to handle the “big data” from next-generation sensors and big simulation. Therefore, we propose “big data assimilation” (BDA) innovation to fully utilize the big data. Since October 2013, the Japan's BDA project has been exploring revolutionary NWP at 100-m mesh refreshed every 30 s, orders of magnitude finer and faster than the current typical NWP systems, by taking advantage of the fortunate combination of next-generation technologies: the 10-petaflops K computer, phased array weather radar, and geostationary satellite Himawari-8. So far, a BDA prototype system was developed and tested with real-world retrospective local rainstorm cases. This paper summarizes the activities and progress of the BDA project, and concludes with perspectives toward the post-petascale supercomputing era.
Fil: Miyoshi, Takemasa. RIKEN Advanced Institute for Computational Science; Japón
Fil: Lien, Guo-Yuan. RIKEN Advanced Institute for Computational Science; Japón
Fil: Satoh, Shinsuke. National Institute of Information and Communications Technology; Japón
Fil: Ushio, Tomoo. Osaka University; Japón
Fil: Bessho, Kotaro. Meteorological Satellite Center; Japón
Fil: Tomita, Hirofumi. RIKEN Advanced Institute for Computational Science; Japón
Fil: Nishizawa, Seiya. RIKEN Advanced Institute for Computational Science; Japón
Fil: Yoshida, Ryuji. RIKEN Advanced Institute for Computational Science; Japón
Fil: Adachi, Sachiho A.. RIKEN Advanced Institute for Computational Science; Japón
Fil: Liao, Jianwei. RIKEN Advanced Institute for Computational Science; Japón
Fil: Gerofi, Balazs. RIKEN Advanced Institute for Computational Science; Japón
Fil: Ishikawa, Yutaka. RIKEN Advanced Institute for Computational Science; Japón
Fil: Kunii, Masaru. RIKEN Advanced Institute for Computational Science; Japón
Fil: Ruiz, Juan Jose. RIKEN Advanced Institute for Computational Science; Japón. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Maejima, Yasumitsu. RIKEN Advanced Institute for Computational Science; Japón
Fil: Otsuka, Shigenori. RIKEN Advanced Institute for Computational Science; Japón
Fil: Otsuka, Michiko. RIKEN Advanced Institute for Computational Science; Japón
Fil: Okamoto, Kozo. RIKEN Advanced Institute for Computational Science; Japón
Fil: Seko, Hiromu. Meteorological Research Institute; Japón
description Following the invention of the telegraph, electronic computer, and remote sensing, “big data” is bringing another revolution to weather prediction. As sensor and computer technologies advance, orders of magnitude bigger data are produced by new sensors and high-precision computer simulation or “big simulation.” Data assimilation (DA) is a key to numerical weather prediction (NWP) by integrating the real-world sensor data into simulation. However, the current DA and NWP systems are not designed to handle the “big data” from next-generation sensors and big simulation. Therefore, we propose “big data assimilation” (BDA) innovation to fully utilize the big data. Since October 2013, the Japan's BDA project has been exploring revolutionary NWP at 100-m mesh refreshed every 30 s, orders of magnitude finer and faster than the current typical NWP systems, by taking advantage of the fortunate combination of next-generation technologies: the 10-petaflops K computer, phased array weather radar, and geostationary satellite Himawari-8. So far, a BDA prototype system was developed and tested with real-world retrospective local rainstorm cases. This paper summarizes the activities and progress of the BDA project, and concludes with perspectives toward the post-petascale supercomputing era.
publishDate 2016
dc.date.none.fl_str_mv 2016-11
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/11336/60304
Miyoshi, Takemasa; Lien, Guo-Yuan; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; et al.; “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress; Institute of Electrical and Electronics Engineers; Proceedings Of The Ieee; 104; 11; 11-2016; 2155-2179
0018-9219
CONICET Digital
CONICET
url http://hdl.handle.net/11336/60304
identifier_str_mv Miyoshi, Takemasa; Lien, Guo-Yuan; Satoh, Shinsuke; Ushio, Tomoo; Bessho, Kotaro; et al.; “Big Data Assimilation” Toward Post-Petascale Severe Weather Prediction: An Overview and Progress; Institute of Electrical and Electronics Engineers; Proceedings Of The Ieee; 104; 11; 11-2016; 2155-2179
0018-9219
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1109/JPROC.2016.2602560
info:eu-repo/semantics/altIdentifier/url/https://ieeexplore.ieee.org/document/7576655/
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
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers
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
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score 13.22299

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