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Dr V Phillips
Prof A Blyth
Applications accepted all year round
Competition Funded PhD Project (UK Students Only)
About the Project
In Europe and the USA, fall-out of hail during the warmer months causes much damage to crops and
urban areas every year. In 1997, insurance companies paid out 0.3 billion Euros in France and Spain
due to hail damage of crops. Total damage there that year to all crops, including uninsured ones, was
almost a billion Euros.
Hail is formed in vigorous cumulonimbus clouds, which are types of deep convection. Hailstones grow
by the accretion of supercooled liquid. Prediction of hail requires state-of-the-art detailed models at high
resolution that treat the complexity of hail growth. Hence, models capable of forecasting hail events
operationally are lacking.
The PhD project will innovate a new type of 'hail damage index' by applying a hierarchy of detailed
models of convective clouds. By including information about the predicted microphysical properties of
the hail (mean size, bulk density, liquid fraction), the index will quantify more comprehensively the likely
damage to crops or buildings from hail episodes. The models will then be applied to understand the
dependencies of hail damage on the most critical environmental factors. From sensitivity tests with the
models, we will predict how the hail damage index depends on factors such as dustiness, wind-shear,
relative humidity and atmospheric instability.
Hailstorms are the fundamental building block of systems of severe weather, which has costly impacts in
human terms and economically. The aim is to provide forecasters with a valuable tool for predicting the
likely damage on the ground from hail. A hail damage index will encapsulate results from the project in
an accessible way for use by the forecasting community. But equally, the project will be an avenue for
advancing understanding of the glaciation, latent heat release and dynamics of deep convection, which is
still quite uncertain.
The project will create a foundation of knowledge for the community subsequently to examine how
aspects of high-impact severe weather will evolve in future during climate change.
urban areas every year. In 1997, insurance companies paid out 0.3 billion Euros in France and Spain
due to hail damage of crops. Total damage there that year to all crops, including uninsured ones, was
almost a billion Euros.
Hail is formed in vigorous cumulonimbus clouds, which are types of deep convection. Hailstones grow
by the accretion of supercooled liquid. Prediction of hail requires state-of-the-art detailed models at high
resolution that treat the complexity of hail growth. Hence, models capable of forecasting hail events
operationally are lacking.
The PhD project will innovate a new type of 'hail damage index' by applying a hierarchy of detailed
models of convective clouds. By including information about the predicted microphysical properties of
the hail (mean size, bulk density, liquid fraction), the index will quantify more comprehensively the likely
damage to crops or buildings from hail episodes. The models will then be applied to understand the
dependencies of hail damage on the most critical environmental factors. From sensitivity tests with the
models, we will predict how the hail damage index depends on factors such as dustiness, wind-shear,
relative humidity and atmospheric instability.
Hailstorms are the fundamental building block of systems of severe weather, which has costly impacts in
human terms and economically. The aim is to provide forecasters with a valuable tool for predicting the
likely damage on the ground from hail. A hail damage index will encapsulate results from the project in
an accessible way for use by the forecasting community. But equally, the project will be an avenue for
advancing understanding of the glaciation, latent heat release and dynamics of deep convection, which is
still quite uncertain.
The project will create a foundation of knowledge for the community subsequently to examine how
aspects of high-impact severe weather will evolve in future during climate change.
Funding Notes
A degree in science or engineering is required. Experience in computer programming is desirable.
Project supervisors
Dr V Phillips's profile is coming soon
View other supervisors at University of LeedsCareer overview
Professor Alan Blyth is a Professor of Atmospheric Science at the University of Leeds, within the School of Earth and Environment. He has expertise in cloud physics, convection, atmospheric observations, atmospheric instrumentation, flooding, and weather forecasts. Professor Blyth''s research involves various projects, including the diabolic evolution of clouds in a Lagrangian framework, and he is actively engaged in initiatives such as the GCRF African Science for Weather Information and Forecasting Techniques (Africa-SWIFT) and the Yorkshire Integrated Catchment Solutions Programme (iCASP). He is associated with the Institute for Climate and Atmospheric Science and welcomes inquiries from prospective postgraduate researchers interested in PhD opportunities.
Research interests
Professor Blyth''s research focuses on atmospheric science, with specific areas of expertise in cloud physics, convection, atmospheric observations, atmospheric instrumentation, flooding, and weather forecasting. He is involved in several research projects, including the DCMEX additional funding (CloudSense2), the diabatic evolution of clouds in a Lagrangian framework, and the GCRF African Science for Weather Information and Forecasting Techniques (Africa-SWIFT). Additionally, he participates in the Yorkshire Integrated Catchment Solutions Programme (iCASP). Professor Blyth is affiliated with the Institute for Climate and Atmospheric Science.
