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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. This project will combine various satellite-based datasets with statistical methods to get currently lacking global snow depth maps. In the second part of the project, the novel maps are applied to advance our knowledge in the fields of global climate reanalyses, high-mountain precipitation and permafrost.

Knowledge about snow depth in mountains is limited. In this research project we will combine different types of satellite data, ground data, and observations in the field to determine snow mass in different remote areas. Photo: Eivind Torgersen/UiO

Knowledge about snow depth in mountains is limited. In this research project we will combine different types of satellite data, ground data, and observations in the field to determine snow mass in different remote areas. Photo: Eivind Torgersen/UiO

About the project

This research effort is, as the first in the world, to directly measure snow depths globally at high spatial resolution from open ICESat-2 NASA spaceborne laser altimetry data available since autumn 2018. To generate global monthly snow depth maps, including for mountainous and forested areas, we will combine the ICESat-2-derived snow depths with data from the ESA's Copernicus Sentinel satellite snow cover/depth data in an ensemble-based data assimilation (DA) framework. 

During the first part of the project, we aim to develop methods to retrieve global snow depths by means of ensemble-based data assimilation, similar to the methods used within climate reanalyses. The second part of the project includes three application areas where our global snow depths have especially great potential to improve our current knowledge, also in the light of climate change: permafrost modelling, climate reanalyses, and high-elevation precipitation.

Objectives

The research effort with the combination of data is carried out in two phases and is along the way supported by field activities for ground references. In phase 1, we will develop algorithms to derive snow depths at two complementary scales: A) local snow depths from ICESat-2 profiles that capture the high spatial variability in areas with small-scale topography, and B) global snow depth maps with monthly temporal resolution, using DA methods.

In phase 2 of the project timeline, we will use the derived snow depths within three application fields where they directly benefit to advance the state of the art:

  • i) Permafrost: include snow depths in an existing model framework to greatly improve modelling of the ground thermal regime, both locally at targeted field sites and at global scale. The current lack of snow depth data is a key bottleneck for permafrost modelling.
  • ii) High-elevation precipitation: analyse how snow depths vary across orographic barriers to increase understanding of high-altitude precipitation processes. These are currently largely unconstrained due to lack of measurements.
  • iii) Climate reanalysis: verify and improve operational and climate reanalysis products through cross-comparison and improved process understanding. In data-sparse areas, reanalysis products are less accurate and largely model-driven given the lack of observations.

Financing

This research project is funded by the “ROMFORSK-Program for romforskning” of The Research Council of Norway and is given as a Researcher Project for Young Talents to project leader Désirée Treichler. The project number at NFR is 325519.

The project period for SNOWDEPTH is from 2021 to 2026.

Cooperation

The SNOWDEPTH-project is a collaboration with researchers from Norway, Svitzerland and Germany from these departments or research institutions:

Publications

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Published June 16, 2022 2:38 PM - Last modified Sep. 30, 2022 8:36 PM