Himawari-8 data assimilated simulation enables 10-minute updates of rain and flood predictions

January 18, 2018

Using the power of Japan’s K computer, scientists from the RIKEN Advanced Institute for Computational Science and collaborators have shown that incorporating satellite data at frequent intervals—ten minutes in the case of this study—into weather prediction models can significantly improve the rainfall predictions of the models and allow more precise predictions of the rapid development of a typhoon.

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New system promises more rapid and accurate prediction of rainfall

July 4, 2017

Using a powerful technique known as “3D nowcasting,” an international team including scientists from the RIKEN Advanced Institute for Computational Science (AICS) has begun to provide, on an experimental basis, forecasts that predict the likelihood of precipitation in a given location ten minutes in advance. The group will use the system to determine if the experimental forecasts, based on data that is updated every 30 seconds, could be used to prevent damage from torrential rains. The work, conducted by a team including researchers from AICS as well as the National Institute of Information and Communications Technology (NICT), Tokyo Metropolitan University, and Osaka University, uses a combination of phased-array radar and computer algorithms that make predictions based on data from the radars.

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K computer and high-tech weather radar come together to predict sudden torrential rains

August 9, 2016

Today, supercomputer-based weather predictions are typically done with simulations that use grids spaced at least one kilometer apart, and incorporate new observational data every hour. However, due to the roughness of the calculations, these simulations cannot accurately predict the threat of torrential rains, which can develop within minutes when cumulonimbus clouds suddenly develop. Now, an international team led by Takemasa Miyoshi of the RIKEN Advanced Center for Computational Science (AICS) has used the powerful K computer and advanced radar observational data to accurately predict the occurrence of torrential rains in localized areas.

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Largest ensemble simulation of global weather using real-world data

November 11, 2015

When performing numerical weather predictions, it is important that the simulation itself be accurate, but it is also key for real-world data, based on observations, to be accurately entered into the model. Typically, weather simulations work by having the computer conduct a number of simulations based on the current state, and then entering observational data into the simulation to nudge it in a way that puts it closer to the actual state. The problem of incorporating data in the simulation—data assimilation—has become increasingly complex with the large number of types of available data, such as satellite observations and measurements taken from ground stations. Typically, supercomputers today spend an approximately equal amount of time running the simulations and incorporating the real-world data.

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K computer runs largest ever ensemble simulation of global weather

July 23, 2014

Ensemble forecasting is a key part of weather forecasting today. Computers typically run multiple simulations, called ensembles, using slightly different initial conditions or assumptions, and then analyze them together to try to improve forecasts. Now, in research published in Geophysical Research Letters, using Japan’s flagship 10-petaFLOPS K computer, researchers from the RIKEN Advanced Institute for Computational Science (AICS) have succeeded in running 10,240 parallel simulations of global weather, the largest number ever performed, using data assimilation to reduce the range of uncertainties.

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■■ Data Assimilation Research Team ■■
Data Assimilation Research Team

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