CEDAR email: PhD studentship in using data science to improve prediction of the upper atmosphere

[Daniel Marsh]

Hello all,

Applications are now being accepted for a PhD studentship to study the upper atmosphere as part of the Satellite Data in Environmental Science – Centre for Doctoral Training (https://eo-cdt.org/). A description of the project and details on applying can be found here:

https://eo-cdt.org/projects/using-data-science-to-improve-prediction-of-the-upper-atmosphere/

Briefly, the overall aim of the PhD is to use satellite and ground based observations, modelling and data science to identify key teleconnections in the atmosphere that drive MLTI variations.  Specifically the student will:

• Data mine level 2 data from satellites and ground based instrument data to identify the key modes of variability in the MLTI.
• Identify potential teleconnections that connect MLTI variability to the lower atmosphere and geospace, using machine learning techniques such as CNN and clustering.
• Evaluate the ability of the current state-of-the-art models to reproduce these teleconnections.

Satellite data identified for this project are: Aeolus, AIRS, COSMIC, HIRDLS, IASI, MLS, SABER and VIIRS. Ground based data identified are from: MF and Meteor radars, Lidars and airglow imagers.

The student will be based at the University of Leeds but will make regular visits to the British Antarctic Survey (BAS) as well as a 3-month placement at the Met Office. This will provide excellent training and first-hand experience of working in world-leading research facilities.

Please contact Dan Marsh if you have any questions.

Prof. Dan Marsh
Priestley Chair in Comparative Planetary Atmospheres
School of Physics & Astronomy, University of Leeds
ph: +44(0) 113 343 9296 email: d.marsh at leeds.ac.uk