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Active RESEARCH GRANT UKRI Gateway to Research

Why have space weather forecasts not improved for over a decade?

£3.96M GBP

Funder Natural Environment Research Council
Recipient Organization University of Reading
Country United Kingdom
Start Date Feb 16, 2024
End Date Feb 15, 2027
Duration 1,095 days
Number of Grantees 1
Roles Principal Investigator
Data Source UKRI Gateway to Research
Grant ID NE/Y001052/1
Grant Description

The solar wind is a continual outflow of material from the Sun, which fills the solar system. Rapid changes in the solar wind conditions in near-Earth space have consequences for technologies in space and on the ground, most notably the power grid. It also poses a radiation threat to humans on high altitude flights and in space, such as future crewed missions to the moon and Mars.

For these reasons, such "space weather" features prominently on the UK National Risk register; accurate space-weather forecasting a goal of critical importance.

In order to mitigate against the costly, and sometimes dangerous, impacts of space weather, it is necessary to provide adequate warning time of an incoming event. As the solar wind always flows away from the Sun, forecasting further into the future effectively means starting the forecasts with information from closer to the Sun. Currently, the Met Office (and other international forecast agencies) uses remote observations of the Sun's surface and lower atmosphere in conjunction with computer models in order to forecast space weather 2-4 days into the future.

Unfortunately, the accuracy with which these state-of-the-art methods can forecast the time of onset of the severe space weather is both insufficient to be useful for many applications, and has not improved for more than a decade.

However, there are measurements of the solar wind being routinely made that are not currently being used by the models. Using methods developed at the University of Reading over the last 4-5-years, we have shown that solar wind forecasts can be significantly improved by ingesting these observations into the models using a technique called data assimilation (DA).

We will employ our new solar wind DA methods to determine what factors most influence space-weather forecast accuracy and, consequently, what are the fundamental limits to how accurate forecasting can hope to reach. We will also adapt our solar wind DA methods to work with the Met Office's forecast models, providing a significant improvement in future space-weather forecasting.

This will have wide societal benefits, as both satellite operation and the power grids can be impacted by space weather.

All Grantees

University of Reading

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