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New approach for better space weather forecasts | N7232

Schematic representation of the ring current in space. The spheres represent the electrons during the geomagnetic storm, with the colors describing the flux density. Blue low flux density, red high flux density. The satellite trajectories are shown
(c) Bernhard Haas / GFZ
The principle of data assimilation, known from weather forecasting, can – based on satellite data – significantly improve the forecast of particle dynamics in the electron ring current around the Earth. This was shown by a team led by Bernhard Haas and Yuri Shprits from the German Research Centre for Geosciences GFZ in a study in the journal Nature Scientific Reports.

Summary

In the age of a rapidly growing fleet of satellites in space, the accurate prediction of space weather phenomena such as storm-like amplifications of electromagnetic fields and particle streams is essential to protect the satellite infrastructure from damage and system failures. Similar to how the accuracy of weather forecasts on Earth depends on precise knowledge of the current atmospheric conditions, predicting weather phenomena in near-Earth space requires a deep understanding of the current state of the dynamic radiation belts that surround the Earth. An international research team led by Bernhard Haas and Yuri Shprits from the German Research Centre for Geosciences GFZ – in collaboration with the Collaborative Research Centre «Data assimilation» at the University of Potsdam – has shown, using the example of a geomagnetic storm, how the principle of data assimilation, which is very powerful in terrestrial weather forecasting, can be used for this purpose. This is a process that uses physically based models to continuously determine a consistent overall starting point for further forecasts from a large number of point-in-time measurements, in this case by satellite. The study was published in the journal Nature Scientific Reports.

Background: Necessity and challenge in space weather forecasting

The radiation belts and ring current that surround the Earth in space pose a threat to satellites: the charged particles flying there can cause temporary malfunctions or irreversible damage to electronic components through effects such as charging or surface charging. This risk increases during geomagnetic storms that amplify and «swirl» the particle streams. A timely forecast of such dangers can help satellite operators to protect their valuable assets.

In order to be able to predict the particle flows around the Earth as precisely as possible in terms of space and time, it is necessary to know the initial state as precisely as possible. However, only point measurements from a few specialized satellites are available for this. The global picture must be calculated from this using models.

There has been progress in the modelling and description of ring currents. For example, a study published by GFZ researchers in mid-2023 discovered a previously unconsidered loss mechanism of particles in the ring current that could significantly improve the accuracy of space weather forecasts. And physical models can already provide a good representation of the basic dynamics of the ring current in geomagnetically quiet times.

“Especially in the case of highly dynamic events such as geomagnetic storms, global state descriptions in near real time are still a challenge,” says Bernhard Haas, doctoral student in the GFZ Space Physics and Space Weather section and lead author of the study.

Transfer of a method from meteorology: data assimilation

Therefore, Haas and his team from the GFZ, led by Yuri Shprits, head of the section and professor at the University of Potsdam, together with other researchers from the Collaborative Research Center «Data Assimilation» (SFB 1294) at the University of Potsdam and from the USA and Japan, took advantage of the benefits of so-called data assimilation. This method has already proven to be indispensable in meteorology, where even small uncertainties in the knowledge of the current state can lead to significant errors in future forecasts.

Data assimilation is the merging of information from measurements and physical models. One underlying algorithm is the Kalman filter, which is also used in this study. In an iterative loop, the future state is constantly re-estimated based on the currently available measurement data and the underlying physical model, including an indication of the associated uncertainty.

Also in the field of space weather forecasting, the assimilation of real-time particle flux data provided by satellites is key to gaining insights into the current state of the space environment and performing analyses after extreme events such as geomagnetic storms.

Validation of the approach with data from a 2017 geomagnetic storm

While previous efforts to use this approach could not be quantitatively validated due to limited data sets, the Van Allen probes of the US space agency NASA and the Arase satellite of the Japanese space agency JAXA offered the scientific community a unique opportunity to do so: several highly specialized satellites orbited the Earth simultaneously. They were able to provide highly precise data on the particle fluxes during the geomagnetic storm on September 7, 2017. The Van Allen probes were on the day side of the Earth, Arase on the opposite night side. This combination allowed the researchers to validate the results of assimilating data from one satellite by that of the other and to study the global response of the ring current during this event.

Summary

«The results of our study underline that data assimilation becomes a crucial tool in geomagnetic storms, where predicting the dynamic system is difficult. Assimilating measurements from a single satellite is sufficient to significantly improve global model results. This challenges traditional assumptions in meteorology, where large amounts of data are often used for assimilation,» summarizes Bernhard Haas.

Yuri Shprits emphasizes: «The ring current model operated at GFZ combines all available data, including from other satellites, with our state-of-the-art model, providing the most accurate reconstruction of the current state of the hazardous space environment as well as precise predictions for the future. This research paves the way for a new type of predictions based on measurements that will help protect our most valuable assets in space.»

Scientific contacts:
M.Sc. Bernhard Haas
PhD student in Section 2.7 Space Physics and Space Weather
Helmholtz Centre Potsdam
German Research Centre for Geosciences GFZ
Tel.: +49 331 6264-1235
E-mail: bernhard.haas@gfz-potsdam.de

Prof. Dr. Yuri Shprits
Head of Section 2.7 Space Physics and Space Weather
Helmholtz Centre Potsdam
German Research Centre for Geosciences GFZ
Tel.: +49 331 6264-
E-Mail: yuri.shprits@gfz-potsdam.de

Original publication:
Haas, B., Shprits, YY, Wutzig, M. et al. Global validation of data-assimilative electron ring current nowcast for space weather applications. Sci Rep 14, 2327 (2024).
https://doi.org/10.1038/s41598-024-52187-0

Further information:
https://www.gfz-potsdam.de/weltraumwetter
https://www.gfz-potsdam.de/weltraumwetter-wissenschaft 

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