About the project
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.
This 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.
Objectives
In GLACMASS we will develop a novel global glacier modelling framework that allows us to reconstruct past, nowcast present, and simulate future global-scale glacier mass changes of all >200,000 glaciers on Earth with unprecedented spatial and temporal detail, accuracy, and computational efficiency leveraging the vast amounts of emerging large-scale observational data, and recent advances in data assimilation and machine learning. The specific scientific objectives are:
- Objective 1: Reconstruct global-scale monthly glacier mass evolution of all glaciers on Earth over the last four decades using data assimilation, thus producing the first ever global glacier reanalysis, and nowcast present mass changes in a near-real-time fashion for selected regions.
- Objective 2: Provide policy-relevant multi-century global glacier projections and scenarios.
Financing
Advanced Grant (AdG). The full name of this project is 'Past and Future High-resolution Global Glacier Mass Changes (GLACMASS)'.
The GLACMASS project period is from October 2023 to September 2028.
Tools for modelling
The GLACMASS project will build on the numerical simulation model Python Glacier Evolution Model (PyGEM). This modelling tool is an open-source glacier evolution model coded in Python. The model is laying at the GitHub-platform.
Visit the homepage for PyGEM – GitHub.
Disclaimer: “Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or [name of the granting authority]. Neither the European Union nor the granting authority can be held responsible for them.”
