European Fundend Projects

  • ID:
    projects-127
  • fiwar:
    101096057
  • Project_Acronym:
    GLACMASS
  • Project_Name:
    Past and Future High-resolution Global Glacier Mass Changes
  • Funding Authority:
    HORIZON
  • Call for proposals:
    ERC-2022-ADG
  • Focus Area:
    ERC-2022-ADG
  • Begin Date:
    2023-10-01
  • End Date:
    2028-09-30
  • Status:
    On going
  • Budget:
    € 002 499 957.00
  • Description:
    World-wide glaciers are losing mass which affects global sea-level, river runoff, freshwater influx to the oceans, glacier-related hazards, and landscape changes, with implications for human livelihoods and ecosystems. Hence, accurate estimates of past, current and future glacier mass variations at a high temporal and spatial resolution are key to effective adaptation strategies. However, previous mass-balance reconstructions and projections have relied on scarce observations with limited spatial and/or temporal resolution, as well as overparameterized, insufficiently constrained and highly simplified models, the latter necessitated by high computational costs incurred by the global scale.GLACMASS will propel the current state-of-the-art of global-scale glacier reconstruction and projection forward in unprecedented ways by delivering a fundamentally novel and internally consistent physically-based modelling framework that draws, for the first time on a global scale, on both data assimilation and modern machine learning techniques facilitated by emerging global-scale glacier-related satellite-derived data. The framework will be used to reconstruct multi-decadal past glacier changes, and make policy-relevant multi-century projections of mass and area changes of all >200,000 glaciers outside the ice sheets with unprecedented accuracy, spatiotemporal detail and computational efficiency, and also nowcast present mass changes in a near-real-time fashion for selected regions. The model framework will fuse output from a novel physically-based glacier evolution model with all relevant observations available for each glacier, such as in-situ, geodetic and gravimetry-derived mass balances, as well as snowlines and other observations, thus simultaneously exploiting the untapped strengths of different types of observational data sets in an optimal manner.
  • Resource:
    https://cordis.europa.eu/project/id/101096057
  • Inland water types:
    Snow and ice'