2015ComputerRequires access

Big Ensemble Data Assimilation in Numerical Weather Prediction

Takemasa Miyoshi, Keiichi Kondo, Koji Terasaki

Open publisher page 59 citations

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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What this paper is about

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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OpenAlex reports 59 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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.

Key concepts: Data assimilation, Numerical weather prediction, Computer science, Big data, Weather forecasting, Supercomputer, Weather prediction, Global Forecast System

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