Abstract ID: 28.7345 | Accepted as Talk | Talk/Oral | 2025-02-28 09:45 - 10:00 | Ágnes‐Heller‐Haus/Small Lecture Room

Land-terminating ice cliffs are rare features of the cryosphere, displaying unique atmosphere-cryosphere interactions due to their vertical nature. Although the ice cliff surface is small compared to the total glacier surface, the mass balance of the vertical face can play a decisive role in glacier ablation, due to the cliff’s altered exposure to radiative fluxes and modulation of turbulent heat fluxes. Understanding the boundary layer fluxes over these vertical ice walls is therefore essential for accurately modeling the melt of the cliff and other related processes. Our primary research focuses on ice cliffs in northern Greenland, where we aim to investigate how boundary layer dynamics shape their microclimate and ablation processes. To complement this work, we analyze a unique high frequency dataset collected from an ice cliff on Kilimanjaro during a 40-hour campaign in 2010. Two 3D sonic anemometers were deployed to monitor turbulence —one on the ground in front of the cliff and another on the cliff face. This dataset provides an opportunity to examine the turbulence structure specific to vertical ice cliffs and explore whether heat and moisture fluxes calculated from low- and high-frequency measurements are consistent. This allows us to determine whether low-frequency data is sufficient to calculate turbulent fluxes at sites without high-frequency instrumentation, as in Greenland. The vertical nature of ice cliffs presents distinct challenges for turbulence measurements, including determining the mean flow direction, identifying dominant turbulent flux directions, and optimizing coordinate rotation methodologies. By addressing these challenges, the Kilimanjaro dataset not only enhances our understanding of turbulent fluxes but also informs their representation in melt models, contributing to more accurate predictions of ice cliff ablation.