EESS talk on "Searching for an attractor in large radar data archives to study the predictability of precipitation"
Event details
| Date | 20.09.2016 |
| Hour | 12:15 › 13:15 |
| Speaker | Dr Loris Foresti, MeteoSwiss, Locarno-Monti |
| Location | |
| Category | Conferences - Seminars |
Abstract: Very short-term precipitation forecasting (0-6 hours), usually known as nowcasting, is a fundamental ingredient in early warning systems for urban floods, landslides, severe thunderstorms and hail. The fractal behaviour and high variability of precipitation in space and time makes both its measurement and prediction particularly challenging. As a consequence, it is practically impossible to provide an accurate deterministic quantitative precipitation forecast and more efforts should be spent in estimating the forecast uncertainty.
Using as basis the concept of analogues, which first appeared in the idealized Lorenz attractor, the core idea of this Ambizione project is to present a new framework to construct a strange attractor for precipitation directly from the large radar and satellite data archives. The ensemble of analogue precipitation patterns retrieved from the attractor is expected to give new insights into the intrinsic predictability of precipitation and could be exploited to design adaptive nowcasting systems that better represent the forecast uncertainty.
Short biography: Loris Foresti is research scientist at MeteoSwiss and is leading a Swiss National Science Foundation (SNSF) Ambizione project on the short-term predictability of precipitation using the large radar and satellite data archives. Loris Foresti was born in Locarno, Switzerland, in 1985, and studied environmental geosciences at the University of Lausanne, where he also received a PhD degree in 2011. The topic of the thesis was the spatial interpolation of meteorological variables in complex orography using kernel-based machine learning methods. After obtaining the PhD he has been 4 years abroad working as postdoctoral scientist at the Australian Bureau of Meteorology, Melbourne (supported by SNSF) and at the Royal Meteorological Institute of Belgium. In both places he carried out cutting edge research on the predictability of precipitation and also developed a real-time probabilistic precipitation nowcasting system based on the extrapolation of radar images in Belgium.
Using as basis the concept of analogues, which first appeared in the idealized Lorenz attractor, the core idea of this Ambizione project is to present a new framework to construct a strange attractor for precipitation directly from the large radar and satellite data archives. The ensemble of analogue precipitation patterns retrieved from the attractor is expected to give new insights into the intrinsic predictability of precipitation and could be exploited to design adaptive nowcasting systems that better represent the forecast uncertainty.
Short biography: Loris Foresti is research scientist at MeteoSwiss and is leading a Swiss National Science Foundation (SNSF) Ambizione project on the short-term predictability of precipitation using the large radar and satellite data archives. Loris Foresti was born in Locarno, Switzerland, in 1985, and studied environmental geosciences at the University of Lausanne, where he also received a PhD degree in 2011. The topic of the thesis was the spatial interpolation of meteorological variables in complex orography using kernel-based machine learning methods. After obtaining the PhD he has been 4 years abroad working as postdoctoral scientist at the Australian Bureau of Meteorology, Melbourne (supported by SNSF) and at the Royal Meteorological Institute of Belgium. In both places he carried out cutting edge research on the predictability of precipitation and also developed a real-time probabilistic precipitation nowcasting system based on the extrapolation of radar images in Belgium.
Practical information
- General public
- Free
- This event is internal
Organizer
- EESS - IIE
Contact
- Prof. Alexis Berne, LTE