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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
The ionosphere is a layer of plasma in the upper atmosphere (thermosphere), produced by the ionization of atmospheric constituents by solar radiation and energetic particles. By virtue of its conductivity, the ionosphere has significant implications for radio communications and navigation systems that propagate signals through or within that medium. To mitigate the impact of the ionosphere on these systems, numerical and statistical modeling approaches, akin to those used to model conventional atmospheric weather, are essential.
Ionospheric models generally come in three forms: statistical climatologies, physics-based numerical models, and data assimilation models. Each of these model types have their own unique strengths and weaknesses that fundamentally restrict what roles they can fulfill, ultimately limiting the breadth of their application. To address some of these limitations, the Space Environment and Radio Engineering (SERENE) group at UoB has developed a broad range of ionospheric and thermospheric models and assimilation systems.
The successful applicant will conduct research to address the following questions:
1) What are the limitations of existing modeling approaches?
2) How can different modeling approaches and assimilation methods be blended to optimally represent the ionosphere?
3) Can advanced, hybrid techniques provide improved representations of not only the ionosphere, but the thermosphere as well?
These questions will be addressed through the use of sophisticated numerical techniques applied to the wide range of ionospheric modeling and data assimilation systems being developed at SERENE.
Applicant Information:
Applicants should have or expect a First or Upper Second Class MSci, MEng, MPhys or equivalent degree in Geophysics, Environmental Science, Physics, Mathematics, or a closely related discipline. Holders of BSc honours degrees are eligible but successful BSc applicants typically have additional research experience.
The successful applicant will join a growing Space Environment research group spanning research interests from atmosphere-ionosphere coupling to thermospheric modeling to magnetospheric physics and the subsequent impacts of these systems on satellite drag and communications, navigation, and remote sensing systems.
How to Apply:
Use the form at the following link to submit an application for this PhD post: https://forms.office.com/r/kpakLrssSB
Those interested should send a CV and a statement outlining their interest and how their relevant experience would make them a strong candidate for the project to Dr. David Themens at [Email Address Removed]. The deadline to apply is January 15th, 2023.
Funding Notes
References
Elvidge, S., & M.J. Angling (2019). Using the local ensemble Transform Kalman Filter for upper atmospheric modelling, J. Space Weather Space Clim., 9, A30, doi: https://doi.org/10.1051/swsc/2019018
Themens, D.R., P.T. Jayachandran, I. Galkin, and C. Hall (2017). The Empirical Canadian High Arctic Ionospheric Model (E-CHAIM): NmF2 and hmF2, J. Geophys. Res. Space Physics, doi: 10.1002/2017JA024398
Dang, T., Zhang, B., Lei, J., Wang, W., Burns, A., Liu, H., Pham, K., and Sorathia, K. A. (2021). Azimuthal averaging–reconstruction filtering techniques for finite-difference general circulation models in spherical geometry, Geosci. Model Dev., 14, 859–873, https://doi.org/10.5194/gmd-14-859-2021
Liu, H.-L., Bardeen, C. G., Foster, B. T., Lauritzen, P., Liu, J., Lu, G., … Wang, W. (2018). Development and validation of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X 2.0). Journal of Advances in Modeling Earth Systems, 10, 381– 402. https://doi.org/10.1002/2017MS001232
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