{"id":463,"date":"2021-11-23T14:57:07","date_gmt":"2021-11-23T14:57:07","guid":{"rendered":"https:\/\/research.reading.ac.uk\/met-aerosols\/?p=463"},"modified":"2021-11-23T15:27:32","modified_gmt":"2021-11-23T15:27:32","slug":"phd-positions-open-for-application","status":"publish","type":"post","link":"https:\/\/research.reading.ac.uk\/met-aerosols\/2021\/11\/23\/phd-positions-open-for-application\/","title":{"rendered":"Dust Modelling PhD Position Open"},"content":{"rendered":"

The impact of high resolution modelling on mineral dust forecasts over West Africa using the ECMWF integrated forecast system<\/strong><\/p>\n

Supervisors: Dr Claire Ryder (University of Reading) , Dr Angela Benedetti (ECMWF), Professor Helen Dacre (UoR), Dr Guigma Kiswendsida (Red Cross Climate Centre, Burkina Faso), Dr Zak Kipling (ECMWF), Dr Samuel R\u00e9my (Hygeos).<\/p>\n

Dust storms are a major driver of poor air quality in many parts of the world, particularly in West Africa. Accurately forecasting dust storms remains a challenge in weather forecast models because many features which drive dust storms occur at smaller scales than are typically represented in forecast models. Currently, the ECMWF run a NWP model at 9km horizontal resolution, though dust uplift and transport are not predicted using forecast winds. However, wind-driven dust is included in the lower resolution (40km) ECMWF Copernicus Atmosphere Monitoring Service (CAMS) model. The timing and magnitude of dust storms can be inaccurate in the CAMS forecast due to poor representation of small scale wind features which pick up dust from the surface and transport it away from sources.<\/p>\n

In this PhD, the successful student will add the representation of wind-driven dust to the 9km ECMWF NWP model. The student will assess the improvements in forecast dust as a result of higher model resolution, as well as the impacts on air quality across West Africa during extreme dust events.<\/p>\n

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The student will address the following research questions:<\/p>\n