Project Start Date : Subject to Availability
Application Deadline : Open Until Filled
Description:
Characterizing wind flow in and above vegetated surfaces is critical for advancing our understanding of land-atmosphere interactions, modeling surface fluxes, and improving weather and climate predictions. Complex canopy geometries influence the structure of the atmospheric boundary layer (ABL), creating spatially variable shear and turbulence that remain difficult to measure and model accurately.
At the WiRE Laboratory of EPFL, we use a combination of scanning lidar systems, advanced data processing, and complementary mobile measurements to study the dynamics of flow over complex natural surfaces.
Specific tasks in which the Master student will be involved include:
Scanning lidar measurements of the flow over and within a vegetated canopy
We use scanning Doppler lidar systems to capture wind velocity fields with high spatial and temporal resolution. These systems allow for non-intrusive monitoring of flow structures across large sections of terrain, providing valuable data on wind shear, velocity gradients, and turbulence modulation due to vegetation. Measurements will focus on both the internal canopy flow and the transition to the flow above the canopy.
Characterization of wind shear across canopy-top regions
Special attention will be given to resolving the vertical structure of the flow in the transition region between the canopy and the overlying ABL. The measurements will help determine the location and characteristics of shear layers and mixing zones. These features are central to understanding vertical transport and canopy-atmosphere coupling.
Data analysis and interpretation using atmospheric turbulence theory
The student will process lidar data to extract key variables such as mean wind speed, turbulence intensities, and flow direction variability. Spectral and statistical analysis techniques will be used to describe the dynamics of the flow field in relation to surface heterogeneity.
Complementary measurements with a mobile platform
Where appropriate, supplemental point measurements using a drone may be used to provide additional data at key canopy-top locations.
Learning Outcomes:
- Hands-on experience with state-of-the-art lidar systems for atmospheric boundary layer measurements
- Skills in processing and analyzing large lidar datasets using Python, Matlab, or similar tools
- Deeper understanding of canopy-flow interactions and environmental turbulence dynamics
- Experience designing and conducting field experiments in natural environments
- Development of scientific writing and communication skills for presenting results
This project is ideal for students with an interest in environmental fluid dynamics, remote sensing, or field-based atmospheric research. Coding experience and familiarity with lidar technology are a plus.
To express interest and obtain more information about the project, please contact:
Dr. Amr Khedr
Email: [email protected]
(Please include in cc the lab supervisor Prof. Fernando Portè-Agel at [email protected])