This project will improve predictions of dust plume evolution, further our understanding of dust’s impact on life, and provide a unique window into the influence of aerosols on ice cloud dynamics by updating a leading aerosol/cloud measurement system. Aerosols are particles or droplets suspended in the atmosphere that can alter weather directly by scattering and absorbing sunlight. As the seeds of cloud droplet formation, aerosols can change the properties of clouds, making them an essential component of the Earth’s energy budget.
Plumes of dust blown from deserts evolve over minutes to hours but can extend over thousands of kilometres. These tiny particles endanger human health when inhaled but are a major source of nutrients for plants in tropical oceans and rainforests. Dust plumes block enough sunlight to reduce surrounding temperatures, but the longest lasting particles may seed ice clouds that instead trap heat. Weather forecasting centres, such as the Met Office (MO), ingest satellite observations of aerosol optical depth (AOD) to account for the impact of desert dust. Existing data provide insufficient detail to track the evolution of plumes throughout the day. Geostationary sensors that image every 10-15 minutes, such as the recently launched Meteosat Third Generation (MTG-I), are necessary to accurately track plume evolution.
A successful applicant will join the Optimal Retrieval of Aerosol and Cloud (ORAC) team, an international group of experts in aerosol and cloud measurement who provide data to the European Space Agency and Copernicus Climate Change Service. The results of this project will improve forecast quality for weather and air quality by improving assimilation of dust aerosols alongside investigating aerosol-cloud-precipitation interactions to reduce a major source of uncertainty in climate predictions. Applicants should have a background in a quantitative physical science like physics, mathematics, or physical geography.
Figure 1: A plume of Saharan dust on 15 Mar 2022 that resulted in sepia-toned skies across western Europe. This project will analyse similar images to determine dust properties such as the plume’s height and the size of the particles. Image by Joshua Stevens, using VIIRS data, for the NASA Earth Observatory at https://earthobservatory.nasa.gov/images/149588/an-atmospheric-river-of-dust.
This project is a CENTA Flagship Project.
This project is suitable for CASE funding
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This project builds on a previous work placement which demonstrated that ORAC can be implemented on MO infrastructure. The student will deploy and test ORAC on geostationary imagery over ocean, evaluating it against current MO dust products to survey current understanding of dust behaviour and impacts. The student will extend the dataset over land by updating the representation of light scattering off of the surface, use new observation modes to accurately identify dust plumes, optimise the code to MO operational requirements, and evaluate the improvement in MO forecasts due to this new dataset. These data will be used to quantify the role of dust in fertilising the central Pacific, investigate the influence of desert dust on ice formation within anvil clouds, or validate climate model scenarios (according to the student’s interests and results).
DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.
Statistical analysis will be learned practically through scientific study of environmental data. Field work to collect additional ground observations, potentially at the Chilbolton Observatory, can be supported by the Field Spectroscopy Facility. Experience with scientific coding will be developed through collaborative working and courses on Python and Fortran available through CENTA. Leicester will provide instruction in optimisation methods and radiative transfer. Presentation and communication skills are taught at the Doctoral College, which will be refined at meetings of our lab, the ORAC team, NCEO research themes, and (inter)national conferences.
The MO is the UK’s national weather and climate service, based in Exeter. Dr Tubbs leads the Satellite Imagery group, which develops derived products for situational awareness and nowcasting such as identifying convective systems, estimating cloud properties, and tracking mineral dust or volcanic ash. As well as hosting the student for placements and providing expenses, the MO will provide access to their cloud computing facilities and near-real time data so that the student can demonstrate their aerosol products on the operational system. As such, applicants must be able to obtain MO security clearance.
Year 1: Learn ORAC by deploying on MO servers for over-ocean observation; Evaluate results against MO, ESA, and NASA dust products; Investigate influence of mineralogy on plant growth with season
Year 2: Devise alternative surface reflectance scheme to improve measurement over land; Quantify influence of dust on ice cloud properties; Assess impact of dust product on forecasts
Year 3: Estimate flux of iron into tropical oceans; Update representation of dust within radiative transfer code; Optimise ORAC for MO operational systems to deliver a geostationary dust product
EUMETSAT (2023) Meteosat Real-Time Imagery. Available at: https://eumetview.eumetsat.int/static-images/
Met Office (2024) What is Saharan dust? Available at: https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/wind/saharan-dust
Fan, J., Y. Wang, D. Rosenfeld, and X. Liu (2016) ‘Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges’, Journal of the Atmospheric Sciences, 73, pp. 4221–4252. doi:10.1175/JAS-D-16-0037.1
Sus, O., Stengel, M., Stapelberg, S., McGarragh, G., Poulsen, C., Povey, A. C., Schlundt, C., Thomas, G., Christensen, M., Proud, S., Jerg, M., Grainger, R., and Hollmann, R. (2018) ‘The Community Cloud retrieval for CLimate (CC4CL) – Part 1: A framework applied to multiple satellite imaging sensors’, Atmospheric Measurement Techniques, 11, pp. 3373–3396. doi:10.5194/amt-11-3373-2018
McGarragh, G. R., Poulsen, C. A., Thomas, G. E., Povey, A. C., Sus, O., Stapelberg, S., Schlundt, C., Proud, S., Christensen, M. W., Stengel, M., Hollmann, R., and Grainger, R. G. (2018) ‘The Community Cloud retrieval for CLimate (CC4CL) – Part 2: The optimal estimation approach’, Atmospheric Measurement Techniques, 11, pp. 3397–3431. doi:10.5194/amt-11-3397-2018
The ORAC code base can be accessed at https://github.com/ORAC-CC/orac
Dr Povey’s personal website: https://le.ac.uk/people/adam-povey
Weather and Climate Research Lab: https://wcrl.co.uk
Earth Observation Science at Leicester: https://le.ac.uk/physics/research/earth-observation-science
For any enquiries related to this project please contact Adam Povey, [email protected]
To apply to this project:
Applications must be submitted by 23:59 GMT on Wednesday 7th January 2026.