SWEEP: Space Weather Empirical Ensemble Package

Lead Research Organisation: Aberystwyth University
Department Name: Inst of Mathematical and Physical Sci


The Sun's atmosphere flows into interplanetary space as the solar wind. Solar eruptions cause large variations in this flow that can cause huge disruption to Earth, economy and society. This disruption can be reduced given advance warning of severe space weather, and the main purpose of this project is to improve this warning system through forecasts.

Space weather forecasting is a relatively new field, and the UK Met Office has a dedicated unit providing forecasts and alerts for various organisations. The forecasts are based on telescope measurements of the Sun and it's extended atmosphere (the corona). These data are continually monitored for large eruptive events which may impact Earth. The data also drive large-scale computational models of the solar wind, giving a forecast of conditions at Earth. This project is tasked with providing a new system that will run alongside the current system, and provide certain key improvements.

The proposed project is called Space Weather Empirical Ensemble Package (SWEEP). SWEEP takes in data from multiple telescopes observing the Sun and the corona, and uses novel methods to create multiple three-dimensional maps of the coronal magnetic field, the coronal density, and of coronal mass ejections (CMEs). Thus there are multiple, independent streams of information based on different types of data and methods. These multiple streams are used to drive a highly-efficient model of the solar wind, giving multiple forecasts at Earth.

SWEEP will compare these multiple forecasts against recent measurements of the solar wind near Earth, calculating a 'skill score', which is a measure of each forecast's performance. Certain forecast streams may perform better than others under different conditions. The skill scores are then used to combine the individual forecast streams into a final main forecast. This approach has the advantage of being modular. If one telescope fails to collect data, the other forecast streams continue to operate - the system is therefore robust.

SWEEP uses a highly-efficient solar wind model - several orders of magnitude faster than the current model. This allows an 'ensemble' approach to forecasting. We can run the model several hundred times, and for each instance apply random small variations on the data fed into the model near the Sun. This leads to a large set, or an ensemble, of forecasts near Earth. The final output can then be given as the most probable forecast, with an estimate of the forecast uncertainty.

Unlike Earth weather forecasting, where there are dozens, or hundreds, of weather stations sampling Earth's atmosphere directly, telescopes that observe the Sun and corona are few and expensive. The properties of the Sun's atmosphere must be indirectly inferred from the telescope remote data. Any new information that we can extract from these data is valuable, and may improve current forecasting performance without the cost of building new telescopes. SWEEP exploits several new analysis tools and models of the solar corona, some of which have not previously been used for forecasting.

SWEEP will be a fully automated system, which is another improvement from the current system. The modular basis also allows for future developments - it will be straightforward to add other forecast streams as new telescopes come online in future years, or to incorporate newly-developed data analysis methods or models.

This initial 2.5 year project is dedicated to adapting and combining existing tools into a fully functional SWEEP. By the end of the project it will be fully operational at the Met Office. Over the next few decades, we hope that SWEEP will be a key forecasting tool that helps protect society from the damage of space weather.


10 25 50