Details of Award
NERC Reference : NE/S010033/1
Solar wind data assimilation - maximising the accuracy of space-weather forecasting
Grant Award
- Principal Investigator:
- Professor MJ Owens, University of Reading, Meteorology
- Co-Investigator:
- Professor AS Lawless, University of Reading, Mathematics and Statistics
- Grant held at:
- University of Reading, Meteorology
- Science Area:
- Atmospheric
- Overall Classification:
- Panel B
- ENRIs:
- Environmental Risks and Hazards
- Science Topics:
- Solar & Solar-Terrestrial Phys
- Abstract:
- "Space weather" describes changes in the Sun's magnetic field which occur over seconds to days. It can damage space- and ground-based technologies, particularly power, communication and Earth-observation systems. In order to forecast space weather with more than about 1 hour of warning time, it is necessary to accurately forecast the solar wind, the continual flow of material away from the Sun which fills the solar system. At present, telescopic observations of the Sun's surface are used to provide the starting conditions for computer simulations of the solar wind. These simulations propagate conditions all the way from the Sun to Earth, where the space-weather impact can be estimated. There are ongoing efforts to improve solar wind simulations and to make more accurate measurements of the solar wind near the Sun. But spacecraft also routinely make direct measurements of the solar wind far from the Sun, which provide useful additional information that is not presently used to improve forecasts. Experience from terrestrial weather prediction shows that the biggest advance in forecasting ability can be achieved by using the available observations to regularly "nudge" the computer simulations back towards reality. This observational "nudging" of computer models is called "data assimilation" (DA), and it is at the heart of modern weather forecasting. Accurate weather forecast lead times have advanced about a day a decade, mainly due to advances in DA. Given this success, it is time to fully explore DA capabilities for space weather, in particular the solar wind. Our group has recently made preliminary studies in this area. The proposed work will build on this to develop and test the first ever solar wind data assimilation (SWDA) system using a physics-based, operational forecast simulation of the solar wind. This represents the first effort to apply DA to the solar wind in a manner comparable to terrestrial numerical weather prediction. The solar wind, however, differs from the atmosphere and other geophysical systems in a number of fundamental ways, thus adapting existing DA techniques will involve overcoming a number of scientific challenges. This will form the core science of the proposed work. In addition to improving space-weather forecasting, the SWDA system will enable cutting-edge space-weather research. One by-product of testing the SWDA system is that we will combine models and observations to produce the most accurate estimate to date of the solar wind conditions back near the Sun, where we are unable to directly make measurements. This will help us to understand which magnetic structures on the Sun are related to different solar wind conditions, serving as a direct observational test for theoretical models of solar wind formation. The SWDA will also be used to determine where, ideally, we would position spacecraft in the solar wind in order to make the biggest improvements to space-weather forecasting. This will inform the design of future space-weather mission design.
- NERC Reference:
- NE/S010033/1
- Grant Stage:
- Completed
- Scheme:
- Standard Grant FEC
- Grant Status:
- Closed
- Programme:
- Standard Grant
This grant award has a total value of £357,855
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DA - Other Directly Allocated | DI - T&S |
|---|---|---|---|---|---|---|
| £5,844 | £138,292 | £40,249 | £36,365 | £119,898 | £3,767 | £13,440 |
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