Fully funded PhD scholarship in "Numerical modeling of tornado winds in the Po
Valley"
Description of the research topic
Extreme weather events such as tornadoes are increasingly documented in Italy. A
recent study conducted by CNR-ISAC confirmed the existence of specific areas that
are more frequently affected by this phenomenon. One of these areas is represented
by the Po Valley. Tornadoes, along with downbursts, are highly localized
atmospheric phenomena with an impact radius of only few hundreds of meters to a
few tens of kilometers, and winds that are among the most violent ever recorded in
nature. Winds of such intensity are devastating for both civil structures and
strategic infrastructures. However, since these are very localized phenomena,
meteorological models operating at the horizontal grid resolutions of few
kilometers and coarse time scales are unable to capture events that occur over a
very short spatiotempral scales. It is therefore essential to adopt numerical
models with extremely high resolution capable of replicating their localized and
unsteady nature at the scale of buildings. In a completely innovative approach,
high-resolution computational fluid dynamics (CFD) and cloud model simulations
will be used to reproduce tornadoes on both flat terrain and in more complex
surroundings of Po Valley. These numerical simulations will aim to quantify the
dynamical proceses of tornado genesis - through validation with real-world
measurements and laboratory tests already present in the literature. Validated
models will further be used to evaluate tornadic wind impact on structures.
Research team and environment
The PhD candidate will carry out the research study at IUSS of Pavia, in the
CARISMA group, in close collaboration with the McGill University, Department of
Atmospheric and Oceanic Sciences. The student co-supervised by Dr. Alessio Ricci
from IUSS of Pavia, Italy, and Dr. Djordje Romanic from McGill University, Canada,
will benefit from the extensive experience of the two groups in climatology, wind
measurement and modeling; wind effects on infrastructures and environment; impact
assessment of extreme natural events; risk management of natural and anthropogenic
hazards.
Suggested skills for this research topic
The candidate should have knowledge of Computational Fluid Dynamics, mesoscale
cloud models used in atmospheric sciences, atmospheric dynamics, data analysis and
statistics. Programming skills in Matlab/Python /Fortran/C++ and knowledge of
signal processing could also be beneficial. Team working attitude and excellent
knowledge of spoken and written English are highly desirable.
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