EESS talk on "Snowflakes of different size, shape, type and mass: the processes behind this variability, measurement techniques and retrievals."
Event details
| Date | 12.10.2021 |
| Hour | 12:15 › 13:15 |
| Speaker | Dr Jacopo Grazioli, Scientist, Environmental Remote Sensing Laboratory (LTE) |
| Location | Online |
| Category | Conferences - Seminars |
| Event Language | English |
Abstract:
Individual snow crystals or larger snowflakes naturally occur in an incredible variety of shapes, sizes and types. The appearance of a snowflake, as we observe it just before it deposits on the ground, is in fact the combined result of all the environmental conditions encountered during its descent, from the cloud to the ground, and of the mechanical interactions with other snowflakes or with liquid water droplets.
There are several open questions regarding the small-scale microphysical properties of snowflakes, many of them revolving around the estimation of their mass or density and how it is varying or scaling with other quantities, for example with size. This aspect is crucial for the parametrization of numerical weather models or climate models that cannot resolve the processes occurring at the scale of individual snow particles. It is of paramount importance also to appropriately interpret remote sensing data of snowfall collected by ground-based radars or satellites, which are representative of large physical volumes and thus large populations of particles.
Knowledge often starts from observations. In the last years a significant momentum for research in the field of snowfall microphysics has been promoted by the development of instruments designed to continuously collect high resolution images of (individual) snowflakes in free fall. This talk focuses in particular on one of those instruments, the Multi-Angle Snowflake Camera (MASC). It will be shown how high-resolution pictures can be used to automatically classify snowflakes, to infer their physical properties and, in combination with simulations and machine learning techniques, even to reconstruct their mass and three-dimensional structure.
Short biography:
Dr Jacopo Grazioli holds a PhD in Environmental Sciences and Engineering from the EPFL of Lausanne. He is working for the Environmental Remote Sensing (LTE) laboratory at EPFL in the field of remote sensing applied to Alpine and Antarctic meteorology as well as for the Swiss Federal Office for Meteorology and Climatology (MeteoSwiss) to develop meteorological services for the civil and military aviation.
Individual snow crystals or larger snowflakes naturally occur in an incredible variety of shapes, sizes and types. The appearance of a snowflake, as we observe it just before it deposits on the ground, is in fact the combined result of all the environmental conditions encountered during its descent, from the cloud to the ground, and of the mechanical interactions with other snowflakes or with liquid water droplets.
There are several open questions regarding the small-scale microphysical properties of snowflakes, many of them revolving around the estimation of their mass or density and how it is varying or scaling with other quantities, for example with size. This aspect is crucial for the parametrization of numerical weather models or climate models that cannot resolve the processes occurring at the scale of individual snow particles. It is of paramount importance also to appropriately interpret remote sensing data of snowfall collected by ground-based radars or satellites, which are representative of large physical volumes and thus large populations of particles.
Knowledge often starts from observations. In the last years a significant momentum for research in the field of snowfall microphysics has been promoted by the development of instruments designed to continuously collect high resolution images of (individual) snowflakes in free fall. This talk focuses in particular on one of those instruments, the Multi-Angle Snowflake Camera (MASC). It will be shown how high-resolution pictures can be used to automatically classify snowflakes, to infer their physical properties and, in combination with simulations and machine learning techniques, even to reconstruct their mass and three-dimensional structure.
Short biography:
Dr Jacopo Grazioli holds a PhD in Environmental Sciences and Engineering from the EPFL of Lausanne. He is working for the Environmental Remote Sensing (LTE) laboratory at EPFL in the field of remote sensing applied to Alpine and Antarctic meteorology as well as for the Swiss Federal Office for Meteorology and Climatology (MeteoSwiss) to develop meteorological services for the civil and military aviation.
Practical information
- General public
- Free
- This event is internal
Organizer
- EESS - IIE
Contact
- Prof. Alexis Berne, LTE