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 numerical models.
Left: A Haboob dust storm in Mali. Credit: Françoise Guichard / Laurent Kergoat / CNRS Photo Library. Right: A false colour Meteosat image of a large haboob in 2012. Dust is shown in pink, deep convective clouds in red. A large haboob (pink) spanning 100s of kilometres, is seen emanating from a mesoscale convective system (red) located around the ‘triple-point’ of Malia, Algeria and Niger. This huge dust storm was missed by the operational global Unified Model run operationally by the Met Office.
Mineral 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, and are linked to outbreaks of meningitis. 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 AR5 notes large uncertainties from dust radiative forcing and disagreements on effects on monsoons. Improved knowledge of dust sources would help model dusts impacts.
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 significant 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. The £8M GCRF African SWIFT consortium, led from Leeds, may provide another route for international collaboration and impact.
The supervisory team and environment:
All the academic supervisors have a strong track record of successfully supervising PhDs, with their students having led a number of first-author papers in top peer-reviewed journals, with many high impact papers on dust. Met Office co-supervisors will input on both observations and modelling, and provide a route to impact. Leeds is home to the headquarters of the National Centre for Atmospheric Science (NCAS) as well as ICAS and SEE, which provides a diverse research environment. The student will be part of both 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. Leeds has formal partnerships with KIT, opening up opportunities for international collaboration, visits and impact. Subject to Covid19, there may be opportunities to participate in GCRF African SWIFT project meetings in Africa, or other relevant project meetings in India.
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