ATMOSPHERIC DATA

Unraveling Earth’s mysteries with the science of shooting stars

By studying the path and light emission of shooting stars,
we aim to unravel the mysteries of the Earth’s atmosphere.
Based on the history of satellites and weather forecast,
we explore new methods to observe Earth.
Leveraging our human-made shooting stars, small satellites, and plasma technology,
ALE aspires to speed up the acquisition of Earth’s weather data.
By shedding light on the mechanisms of climate change,
we hope to advance scientific knowledge and help create a sustainable world for humankind.

About ATMOSPHERIC DATA

Using its original human-made shooting stars, small satellites and plasma technologies, we are developing new ways to observe Earth. By studying the path and light emission of human-made shooting stars, we aim to increase the pace of obtaining data from the troposphere to the mesosphere that has been challenging in the past.
This will enable us to contribute to the improvement of weather forecast accuracy and help unravel the mechanisms behind climate change.
Subsequently, these data and analysis can help in areas such as disaster countermeasures, energy, agriculture and develop a more detailed production and logistics plan.

AETHER PROJECT

Project mission
Make space closer with commercial weather satellites and bring comfort. For all of us. Together.

Japan's leading organizations in communications, radio astronomy, and meteorology gathered for Industry-Academia collaboration project to tackle natural disasters with commercial weather satellites.

Weather forecasting is done by observational data which shows the present, weather model which can simulate the future, and data assimilation which combines the observational data and weather model to help improve the accuracy of weather forecasts*. In AETHER, organizations specialized in each field have come together and established an integrated research and development system, ranging from observation to forecasting.

*"Data assimilation" is the technique to improve the accuracy of forecasts by comparing simulation results based on the weather model with actual observation data.