Global modelling of the solar atmosphere and comparison to solar observations
Lead Research Organisation:
University of St Andrews
Department Name: Mathematics and Statistics
Abstract
Over the last 40 years a vast amount of observational data has been produced on the spatial and time evolution of the Sun's magnetic field.
This data has been taken by a wide range of observatories using different spectral lines and at different spatial and temporal resolution.
The first stage of the project will analyse the huge amount of data from a wide variety of observatories in order to determine magnetic bipoles and the relationship between the varying data sets to produce a consistent and coherent understanding of the variation of the Sun's magnetic field over the last 4 cycles across all spatial scales. Once this is carried out automated data preparation and reduction techniques will be developed so that
(I) future data sets of bipoles may be analysed in real time.
(ii) observational data can be included in realtime simulations of the Sun to carry out predictions relevant to Space Weather both on a global and local scale where these simulation are directly driven from the observations.
(iii) A detailed comparison of the simulations with observations will be carried out.
This data has been taken by a wide range of observatories using different spectral lines and at different spatial and temporal resolution.
The first stage of the project will analyse the huge amount of data from a wide variety of observatories in order to determine magnetic bipoles and the relationship between the varying data sets to produce a consistent and coherent understanding of the variation of the Sun's magnetic field over the last 4 cycles across all spatial scales. Once this is carried out automated data preparation and reduction techniques will be developed so that
(I) future data sets of bipoles may be analysed in real time.
(ii) observational data can be included in realtime simulations of the Sun to carry out predictions relevant to Space Weather both on a global and local scale where these simulation are directly driven from the observations.
(iii) A detailed comparison of the simulations with observations will be carried out.
Organisations
People |
ORCID iD |
| Duncan Mackay (Primary Supervisor) | |
| Callan Noble (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| ST/P006809/1 | 01/10/2017 | 30/09/2024 | |||
| 2011385 | Studentship | ST/P006809/1 | 27/09/2017 | 26/12/2021 | Callan Noble |