research-article

Big Ensemble Data Assimilation in Numerical Weather Prediction

Authors:

Takemasa Miyoshi,

Koji TerasakiAuthors Info & Claims

Computer, Volume 48, Issue 11

Pages 15 - 21

https://doi.org/10.1109/MC.2015.332

Published: 01 November 2015 Publication History

Abstract

Powerful computers and advanced sensors enable precise simulations of the atmospheric state, requiring data assimilation to connect simulations to real-world sensor data using statistical mathematics and dynamical systems theory. Numerical weather prediction (NWP) thus enables simulations that more closely represent the real world. The authors explore the NWP-associated challenges in managing big data through supercomputing.

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Cited By

Li YJu XXiao YJia QZhou YQian SLin RYang BShi SLiu XGao JWang ZLiu STan JWang XHu ZYan LXue WMohror KArnold DBadia R(2023)Rapid simulations of atmospheric data assimilation of hourly-scale phenomena with modern neural networksProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607031(1-13)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3581784.3607031
Zhang G(2022)Packaging Big Data Visualization Based on Computational Intelligence Information DesignComputational Intelligence and Neuroscience10.1155/2022/45588392022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/4558839
Yashiro HTerasaki KKawai YKudo SMiyoshi TImamura TMinami KInoue HNishiki TSaji TSatoh MTomita HCuicchi CQualters IKramer W(2020)A 1024-member ensemble data assimilation with 3.5-km mesh global weather simulationsProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.5555/3433701.3433703(1-10)Online publication date: 9-Nov-2020
https://dl.acm.org/doi/10.5555/3433701.3433703
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Published: 01 November 2015

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Cited By

Li YJu XXiao YJia QZhou YQian SLin RYang BShi SLiu XGao JWang ZLiu STan JWang XHu ZYan LXue WMohror KArnold DBadia R(2023)Rapid simulations of atmospheric data assimilation of hourly-scale phenomena with modern neural networksProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.1145/3581784.3607031(1-13)Online publication date: 12-Nov-2023
https://dl.acm.org/doi/10.1145/3581784.3607031
Zhang G(2022)Packaging Big Data Visualization Based on Computational Intelligence Information DesignComputational Intelligence and Neuroscience10.1155/2022/45588392022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/4558839
Yashiro HTerasaki KKawai YKudo SMiyoshi TImamura TMinami KInoue HNishiki TSaji TSatoh MTomita HCuicchi CQualters IKramer W(2020)A 1024-member ensemble data assimilation with 3.5-km mesh global weather simulationsProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis10.5555/3433701.3433703(1-10)Online publication date: 9-Nov-2020
https://dl.acm.org/doi/10.5555/3433701.3433703
Aljawarneh SLara JYassein M(2020)A visual big data system for the prediction of weather-related variables: Jordan-Spain case studyMultimedia Tools and Applications10.1007/s11042-020-09848-982:9(13103-13139)Online publication date: 1-Oct-2020
https://dl.acm.org/doi/10.1007/s11042-020-09848-9
Kudo SImamura T(2019)Cache-efficient implementation and batching of tridiagonalization on manycore CPUsProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3293320.3293329(71-80)Online publication date: 14-Jan-2019
https://dl.acm.org/doi/10.1145/3293320.3293329
Liao JGerofi BLien GNishizawa SMiyoshi TTomita HIshikawa Y(2016)Toward a General I/O Arbitration Framework for netCDF Based Big Data ProcessingProceedings of the 22nd International Conference on Euro-Par 2016: Parallel Processing - Volume 983310.1007/978-3-319-43659-3_22(293-305)Online publication date: 24-Aug-2016
https://dl.acm.org/doi/10.1007/978-3-319-43659-3_22

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