The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

Glaciers play a crucial role in the Earth System: they are important water suppliers to lower‐
lying areas during hot and dry periods, and they are major contributors to the observed …

DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep
learning in the field of earth sciences, from four leading voices Deep learning is a …

Notwithstanding the large availability of data and models, a consistent picture of the snow
cover extent and duration changes in global mountain areas is lacking for long-term trends …

This work introduces the S2M (SAFRAN–SURFEX/ISBA–Crocus–MEPRA) meteorological
and snow cover reanalysis in the French Alps, Pyrenees and Corsica, spanning the time …

This paper introduces the Instructed Glacier Model (IGM)–a model that simulates ice
dynamics, mass balance and its coupling to predict the evolution of glaciers, icefields or ice …

Knowledge of glacier volume is crucial for ice flow modelling and predicting the impacts of
climate change on glaciers. Rugged terrain, harsh weather conditions and logistic costs limit …

Glacier, snow, and ice are the essential components of the Himalayan cryosphere and
provide a sustainable water source for different applications. Continuous and accurate …

Studying glacier mass changes at regional scale provides critical insights into the impact of
climate change on glacierized regions, but is impractical using in situ estimates alone due to …

Glaciers and ice caps are experiencing strong mass losses worldwide, challenging water
availability, hydropower generation, and ecosystems. Here, we perform the first-ever glacier …