SNOWDEPTH - Global snow depths from spaceborne remote sensing for permafrost, high-elevation precipitation, and climate reanalyses

Snow in the mountains is a source for drinking water, hydropower, irrigation, but can also cause floods and geohazards. There are currently no efficient methods to measure depth of snow in mountains and remote areas.

The first aim of this project is to combine snow depth measurements from satellite data with elevation data, climate data and statistical methods to get currently lacking global snow depth maps. The second aim is to use the novel maps to improve global climate reanalyses and our knowledge on high-mountain precipitation and permafrost.

Read more about the project (mn.uio.no)

Tags: Bayesian inference, Data fusion/integration, Spatial statistics, Time series, Earth and environmental sciences
Published May 31, 2023 1:13 PM - Last modified Oct. 23, 2023 12:00 PM