Laan et al. (2025) Decadal re-forecasts of glacier climatic mass balance

Identification

• Journal: ˜The œcryosphere
• Year: 2025
• Date: 2025-09-16
• Authors: Larissa van der Laan, Anouk Vlug, Adam A. Scaife, Fabien Maussion, Kristian Förster
• DOI: 10.5194/tc-19-3879-2025

Research Groups

• Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
• Institute of Hydrology and Water Resources Management, Leibniz University Hannover, Hannover, Germany
• Institute of Geography, University of Bremen, Bremen, Germany
• Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
• Met Office Hadley Centre, Exeter, UK
• College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
• Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
• Institute of Ecology and Landscape, University of Applied Sciences Weihenstephan-Triesdorf, Freising, Germany

Short Summary

This study presents the first application of decadal re-forecasts to simulate global glacier climatic mass balance, bridging the gap between seasonal forecasts and long-term projections. It demonstrates that forcing the Open Global Glacier Model (OGGM) with decadal re-forecasts generally outperforms persistence forecasts and historical General Circulation Model (GCM) simulations for multi-annual glacier mass balance, offering moderate improvements for near-term predictions.

Objective

• To investigate the utility and predictive skill of forcing a glacier mass balance model with decadal-scale re-forecasts of temperature and precipitation, aiming to bridge the gap between seasonal forecasts and long-term projections of glacier contributions to catchment hydrology and sea-level rise.

Study Configuration

• Spatial Scale: Global (approximately 214,000 land-terminating glaciers), regional (18 RGI regions), and individual glacier scale (279 reference glaciers).
• Temporal Scale: Decadal (1 to 10 years), with re-forecasts initialized annually from 1960 to 2010, and validation performed for the period 2000–2020.

Methodology and Data

• Models used:
  • Open Global Glacier Model (OGGM) v1.5.3 (open-source, Python-based, temperature index model for mass balance).
• Data sources:
  • Climate Forcing:
    • Coupled Model Intercomparison Project Phase 6 (CMIP6) Decadal Climate Prediction Project (DCPP-A) multi-model, multi-member ensemble of monthly temperature and precipitation re-forecasts (FGOALS, NorCPM, MIROC6).
    • CMIP6 historical simulations and projections (SSP2-4.5, also SSP1-2.6 and SSP5-8.5 for FGOALS) from FGOALS, NorCPM, MIROC6.
    • Climatic Research Unit Time Series (CRU TS v4.01) and CRU CL v2.0 (0.5° and 10' resolution, respectively) for baseline climate and persistence forecasts.
  • Glacier Data:
    • Randolph Glacier Inventory (RGI) version 6.0 for glacier outlines.
  • Observational Data for Calibration/Validation:
    • World Glacier Monitoring Service (WGMS) direct mass balance observations (N=279 reference glaciers, at least 5 consecutive years, 2000-2020).
    • Hugonnet et al. (2021) geodetic mass balance estimates for 94% of global glaciers (2000-2020).

Main Results

• For annual mean mass balance of 279 reference glaciers, decadal re-forecasts consistently showed lower Mean Absolute Error (MAE) (0.63-0.65 meters water equivalent) and higher Pearson correlation (0.07-0.14) across lead times compared to persistence (MAE 0.69-0.72 meters water equivalent, variable r) and GCM historical simulations (MAE 0.66 meters water equivalent, r 0.01).
• For decadal mean mass balance of 279 reference glaciers (2000-2020), decadal re-forecasts achieved the highest Pearson correlation (0.64) and a lower MAE (0.27 meters water equivalent) compared to GCM historical (r=0.61, MAE=0.29 meters water equivalent) and persistence (r=0.58, MAE=0.39 meters water equivalent).
• A binomial test indicated that 174 out of 279 reference glaciers showed improved skill (reduced MAE) for decadal mean mass balance, and 186 showed improved skill for cumulative mass balance when using decadal re-forecasts over persistence or historical forcing, suggesting overall significant improvement at the 5% level.
• Globally, for land-terminating glaciers (2000-2010), decadal re-forecasts showed a 23% and 18% reduction in MAE relative to persistence and GCM historical forcing, respectively (MAE 0.28 meters water equivalent vs 0.35 meters water equivalent and 0.33 meters water equivalent). Pearson correlation was highest for re-forecasts (0.71).
• Regional analysis showed decadal re-forecasts achieved good agreement (difference ≤0.1 meters water equivalent) with observed regional mean mass balances in 10 of 18 RGI regions for 2000-2010.
• The skill differences between experiments were often within 1 standard deviation of the mean error of observations, and observed data differences between WGMS and geodetic datasets were of similar magnitude to simulation errors, reinforcing the satisfactory quality of simulated results.

Contributions

• Presents the first study to employ decadal re-forecasts for simulating global glacier climatic mass balance, addressing a critical gap in glacier modeling timescales.
• Demonstrates the added value of initialized decadal re-forecasts over persistence forecasts and traditional uninitialized GCM historical simulations for near-term (1-10 year) glacier mass balance predictions.
• Provides a comprehensive evaluation of decadal re-forecast skill for glacier mass balance at individual, regional, and global scales, utilizing both direct and geodetic observations.
• Highlights the potential for improved near-term glacier predictions relevant to hydrological applications and water resource management, despite modest statistical significance in some tests.
• Emphasizes the importance of multi-model ensembles for enhancing predictive skill in glacier modeling.

Funding

• Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), grant no. 416069075 (FO1269/1) for project "Global glacier mass balance prediction on seasonal and decadal scale GLISSADE".
• Austrian Science Fund (FWF) project P30256.
• German Research Foundation (DFG) – MA 6966/5-1.
• Met Office Hadley Centre Climate Programme (HCCP) funded by the UK Department for Science, Innovation and Technology (DSIT).
• Open-access fund of Leibniz Universität Hannover.

Citation

@article{Laan2025Decadal,
  author = {Laan, Larissa van der and Vlug, Anouk and Scaife, Adam A. and Maussion, Fabien and Förster, Kristian},
  title = {Decadal re-forecasts of glacier climatic mass balance},
  journal = {˜The œcryosphere},
  year = {2025},
  doi = {10.5194/tc-19-3879-2025},
  url = {https://doi.org/10.5194/tc-19-3879-2025}
}