Dust storms in the Sahara and Sahel: From Nowcasting to Climate - SENSE CDT

Dust storms are a dramatic weather hazard, and dust is an essential component of earth’s climate system, affecting radiation and coupling with the carbon cycle. The inherent difficulties in modelling dust storms mean there is a need and opportunity for dust predictions based directly on forward extrapolations of observations, i.e. “nowcasts”, a technique that is very successfully used for short-range prediction of convective storms. This project will develop a tool for dust nowcasting, and then use this tool to fill key gaps in our understanding of dust emissions and the Earth’s dust cycle, informing development of models.

Dust is the largest fraction of airborne aerosol by mass and is an important quantity to predict across a range of time and spatial scales. Dust storms directly impact human activities, such as transport. Predicting dust in weather models improves forecasts, even in regions far from dust, since dust interacts with both solar and infrared radiation. Dust has wide earth-system impacts: it is a source of ice-nucleating particles for clouds, aged dust can act as a cloud condensation nucleus, and deposited dust darkens snow/ice surfaces and provides vital nutrients to land and ocean ecosystems, coupling with the carbon cycle. IPCC AR6 notes low confidence in estimates of dust emission response to climate change and uncertainty on the sign of dust-climate feedback. Improved knowledge of dust sources would help improve models.

Dust predictions are very challenging for numerical models, since they must capture the rare high-wind uplift events and the often small-scale variations in soil type, soil moisture and vegetation. The summertime Sahara and the Sahel is the world’s largest dust source, but knowledge of sources within it is rudimentary. Existing source maps suffer from being based on very sparse knowledge of soils, often conflating soil and wind characteristics, not being objectively determined, and not being able to identify seasonal variations in sources, or human impacts on sources. Cold-pool outflows from deep convection (‘haboobs’) are a dominant source of high winds, yet these are largely missing in models and even reanalyses. Large uncertainties remain in our understanding. For example, how do spatial and temporal variations in land-surface properties control emission? What fraction of dust is generated by which meteorological mechanism? How do anthropogenic changes to the land surface affect dustiness? The project will both address these fundamental science questions and produce tools that could transform short range predictions of airborne dust.

Aims and Objectives

The project will focus on the Sahara and Sahel, due to their importance for the global dust cycle, vulnerable populations and the high quality data available from Meteosat, which is in geostationary orbit. We will first apply data science techniques to forward extrapolate satellite retrievals of airborne dust to generate nowcast predictions and evaluate these to understand variations in skill. Using the newly developed tool, combined with reanalyses, and other remotely-sensed products we will generate new understanding of sources, and their variability, as well as new quantification of the role of different meteorological mechanisms in dust uplift. If time allows, and as a possible application of the above findings, we will apply the above approach to investigate dust emissions from other important regions, such as the Middle East desert and the Gobi desert.

Potential for high impact science

The project has the potential to have high impact beyond academia, both in terms of providing new tools for prediction, and new understanding and quantification for dust modelling. The Met Office provides one key route for this impact, and channels such as the World Meteorological Office Sand and Dust Storm Warning Advisory and Assessment System provide routes for wider and direct international impact. Contacts from the £8M GCRF African SWIFT consortium, led from Leeds, may provide another route for international collaboration and impact.

The supervisory team and environment:

All university supervisors have a strong track record of successfully supervising PhDs, with their students first-author of a number of papers in top journals. Marsham and Knippertz both have many high impact papers on dust. The student would be part of a large and active Leeds group studying tropical and African meteorology and Edinburgh’s Atmospheric Chemistry and Climate of the Anthropocene group.  Interdisciplinary groups such as Edinburgh’s Global Change Research Institute, water@leeds and the Priestley Centre allow the possibility to establish links with other disciplines, such as ecology and oceanography. Knippertz is a leading authority on dust, and Leeds has formal partnerships with KIT, opening up opportunities for international collaboration and impact. Met Office co-supervisors will input on observations and modelling, facilitating data access, and provide a route to impact.

This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See http://www.eo-cdt.org

Funding Notes

This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,500 for 2021/22), tax-free stipend at the UK research council rate (£15,609 for 2021/22), and a research training and support grant to support national and international conference travel. www.eo-cdt.org/apply-now