TROPIPOLAR – GLASCLIM project: advancing scientific collaboration on glacier mass balance modelling across the Andes and the Antarctic Peninsula through machine learning

Christian Torres; Jordi Bolíbar; Jorge Arigony‐Neto; Deniz Bozkurt; Edwin Loarte; Alvaro Soruco; Vincent Favier; Antoine Rabatel; Katy Medina; Claudio Bravo; Duilio Fonseca-Gallardo; Ilaria Tabone; David Farías-Barahona; Rubén Basantes-Serrano; Marco Zurita; Rolando Cruz Encarnación; Javier Norambuena; Ricardo Jaña; Inti González; Christie Vera; Bulat Mavlyudov; Cinthya Bello; Bolívar Cáceres; Sebastián Marinsek; Viankcor Cashpa; Jorge Huenante

doi:10.1080/2154896x.2026.2696754

Key Points

Advance glacier mass balance modeling across the Andes and the Antarctic Peninsula by establishing collaborative machine learning frameworks.
Integrated regional climate datasets with in-situ and remote glaciological observations across Andean and Antarctic glacier systems.
Applied machine learning algorithms to simulate and predict glacier mass balance changes across differing climatic zones.
Enabled cross-regional predictions of glacier thinning and retreat rates spanning tropical and polar environments.
Demonstrated the capability of machine learning models to capture complex glacier responses to regional climate drivers.

Implication

Modeling framework reveals glacier mass balance dynamics across tropical and polar regions, highlighting machine learning utility in environmental forecasting.

Abstract

Glaciers worldwide are undergoing rapid retreat and thinning (Zemp, Huss, Thibert, Eckert, McNabb, Huber, Barandun, et al. 2019), driving major environmental impacts across scales. While in-situ an...

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Torres et al. (2026) studied this question.

synapsesocial.com/papers/6a80199875c2e31742c858f9 https://doi.org/10.1080/2154896x.2026.2696754

View at Publisher

Ask AI

Bookmark

Share

TROPIPOLAR – GLASCLIM project: advancing scientific collaboration on glacier mass balance modelling across the Andes and the Antarctic Peninsula through machine learning

Key Points

Implication

Abstract

Discussion

Cite This Study

TROPIPOLAR – GLASCLIM project: advancing scientific collaboration on glacier mass balance modelling across the Andes and the Antarctic Peninsula through machine learning

Key Points

Implication

Abstract

Discussion

Cite This Study

Keep reading

More related papers

More from The Polar Journal

Keep reading

More related papers

More from The Polar Journal