Glacier projections sensitivity to temperature-index model choices and calibration strategies

• Published in: Annals of Glaciology
• Main Authors: Lilian Schuster, David R. Rounce, Fabien Maussion
• Format: Article in Journal/Newspaper
• Language: English
• Published: Cambridge University Press
• Subjects: Glacier hydrology; glacier modelling; glacier volume; glacier mass balance; mountain glaciers; Meteorology. Climatology; QC851-999; Annals of Glaciology
• Online Access: https://doi.org/10.1017/aog.2023.57; https://doaj.org/article/093a719104e24d3993001ef07b6d5809

The uncertainty of glacier change projections is largely influenced by glacier models. In this study, we focus on temperature-index mass-balance (MB) models and their calibration. Using the Open Global Glacier Model (OGGM), we examine the influence of different surface-type dependent degree-day factors, temporal climate resolutions (daily, monthly) and downscaling options (temperature lapse rates, temperature and precipitation corrections) for 88 glaciers with in-situ observations. Our findings indicate that higher spatial and temporal resolution observations enhance MB gradient representation due to an improved calibration. The addition of surface-type distinction in the model also improves MB gradients, but the lack of independent observations limits our ability to demonstrate the added value of increased model complexity. Some model choices have systematic effects, for example weaker temperature lapse rates result in smaller projected glaciers. However, we often find counter balancing effects, such as the sensitivity to different degree-day factors for snow, firn and ice, which depends on how the glacier accumulation area ratio changes in the future. Similarly, using daily versus monthly climate data can affect glaciers differently depending on the shifting balance between melt and solid precipitation thresholds. Our study highlights the importance of considering minor model design differences to predict future glacier volumes and runoff accurately.