| dc.description.abstract | Severe wind gusts pose substantial risks to transmission towers and the electric grid.
With the ongoing energy transition and global warming, these risks are likely to increase.
Despite this, there is a lack of research specifically focused on wind gusts, particularly in
the context of climate change.
This thesis investigates how wind gust dynamics respond to climate change by
applying a global warming method to two regional climate models. The first model,
RACMO, operates at a 12 km resolution with parameterized convection schemes, while
the second model, HCLIM, is nested within RACMO and has a higher resolution of 2.5
km, enabling explicit convection resolving. These models are run for a severe wind gust
event that has been linked to numerous severe wind reports, with the boundary and
initial conditions altered using perturbations to simulate future or past climates. The
perturbations applied for this thesis correspond to −1.5 °C, +1.5 °C, and wet and dry +3
°C global warming scenarios.
The results indicate a significant increase in both wind gust intensity and extent
due to global warming, especially in the +3°C dry scenario. The strongest wind gusts in
this scenario highlight the impact of a lower relative humidity, which directly enhances
evaporative cooling and likely increases cold pool strength. Wind gust-related parame-
ters, such as the rear inflow jet (RIJ), mesovortices, and downward mass transport, show
stronger correlations with wind gust intensity than environmental parameters like convec-
tive available potential energy (CAPE) and vertical wind shear. These findings emphasize
downward mass transport as a key predictor of wind gust intensity, underscoring the role
of vertical momentum conversion near the surface.
Additionally, mesoscale convective systems (MCSs) in warmer climates tend to ex-
hibit delayed peak wind gust intensities and longer lifespans due to enhanced convection
and mesovortex formation. These results emphasize the need for further research on wind
gust dynamics in future climates to improve forecasting and risk assessments for severe
storms. | |
