Scottish snow patches: remote sensing, machine learning and modelling 

Mountain snow provides many services as a store of water, a habitat and a playground, but also poses threats as a flood and avalanche risk because it is highly sensitive to climate variability and change.

The high spatial variability of snow in mountains, compared with the resolutions of satellite sensors and models, makes measuring and forecasting snow cover characteristics particularly difficult in the very environments they are most needed.

Even in the maritime climate of Scotland, snow can persist throughout the summer in favourable mountain locations. In fact, until recently, some highland corries would house perennial snow patches for many decades without seeing them melt. The fine balance between preferential snow deposition in winter and sheltering in summer makes predicting the distribution of these snow patches a rigorous test for the kind of physically based snow models used in climate projection and impacts studies.

The motivation for my project is to use newly available high resolution remote sensing and meteorological modelling with machine learning to improve understanding of the climate sensitivity of mountain snow.

https://wsl.zoom.us/j/63147899501?pwd=AFtgNnnxbtLWPdaqg5GeFtn7g9bNwe.1

Meeting ID: 631 4789 9501
Passcode: 398816