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1. Stream hydrology controls on ice cliff evolution and survival on debris-covered glaciers

   Petersen, E; Hock, R; Loso, M (May 2024, Earth Surface Dynamics)

   Ice cliffs are melt hot spots that contribute disproportionately to melt on debris-covered glaciers. In this study, we investigate the impact of supraglacial stream hydrology on ice cliffs using in situ and remote sens- ing observations, streamflow measurements, and a conceptual geomorphic model of ice cliff backwasting applied to ice cliffs on Kennicott Glacier, Alaska. We found that 33 % of ice cliffs (accounting for 69 % of the ice cliff area) are actively influenced by streams, while half are nearer than 10 m from the nearest stream. Supraglacial streams contribute to ice cliff formation and maintenance by horizontal meandering, vertical incision, and de- bris transport. These processes produce an undercut lip at the ice cliff base and transport clasts up to tens of centimeters in diameter, preventing reburial of ice cliffs by debris. Stream meander morphology reminiscent of sedimentary river channel meanders and oxbow lakes produces sinuous and crescent ice cliff shapes. Stream avulsions result in rapid ice cliff collapse and local channel abandonment. Ice cliffs abandoned by streams are observed to be reburied by supraglacial debris, indicating a strong role played by streams in ice cliff persistence. We also report on a localized surge-like event at the glacier’s western margin which drove the formation of ice cliffs from crevassing; these cliffs occur in sets with parallel linear morphologies contrasting with the crescent planform shape of stream-driven cliffs. The development of landscape evolution models may assist in quanti- fying the total net effect of these processes on steady-state ice cliff coverage and mass balance, contextualizing them with other drivers including supraglacial ponds, differential melt, ice dynamics, and collapse of englacial voids. 

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2. Marine ice-cliff instability modeling shows mixed-mode ice-cliff failure and yields calving rate parameterization

   https://doi.org/10.1038/s41467-021-23070-7  

   Crawford, Anna J.; Benn, Douglas I.; Todd, Joe; Åström, Jan A.; Bassis, Jeremy N.; Zwinger, Thomas (December 2021, Nature Communications)

   Abstract Marine ice-cliff instability could accelerate ice loss from Antarctica, and according to some model predictions could potentially contribute >1 m of global mean sea level rise by 2100 at current emission rates. Regions with over-deepening basins >1 km in depth (e.g., the West Antarctic Ice Sheet) are particularly susceptible to this instability, as retreat could expose increasingly tall cliffs that could exceed ice stability thresholds. Here, we use a suite of high-fidelity glacier models to improve understanding of the modes through which ice cliffs can structurally fail and derive a conservative ice-cliff failure retreat rate parameterization for ice-sheet models. Our results highlight the respective roles of viscous deformation, shear-band formation, and brittle-tensile failure within marine ice-cliff instability. Calving rates increase non-linearly with cliff height, but runaway ice-cliff retreat can be inhibited by viscous flow and back force from iceberg mélange. 

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3. Impacts of Rainstorm Intensity and Temporal Pattern on Caprock Cliff Persistence and Hillslope Morphology in Drylands

   https://doi.org/10.1029/2023JF007478  

   Shmilovitz, Yuval; Tucker, Gregory E.; Rossi, Matthew W.; Morin, Efrat; Armon, Moshe; Pederson, Joel; Campforts, Benjamin; Haviv, Itai; Enzel, Yehouda (February 2024, Journal of Geophysical Research: Earth Surface)

   Abstract Hillslope topographic change in response to climate and climate change is a key aspect of landscape evolution. The impact of short‐duration rainstorms on hillslope evolution in arid regions is persistently questioned but often not directly examined in landscape evolution studies, which are commonly based on mean climate proxies. This study focuses on hillslope surface processes responding to rainstorms in the driest regions of Earth. We present a numerical model for arid, rocky hillslopes with lithology of a softer rock layer capped by a cliff‐forming resistant layer. By representing the combined action of bedrock and clast weathering, cliff‐debris ravel, and runoff‐driven erosion, the model can reproduce commonly observed cliff‐profile morphology. Numerical experiments with a fixed base level were used to test hillslope response to cliff‐debris grain size, rainstorm intensities, and alternation between rainstorm patterns. The persistence of vertical cliffs and the pattern of sediment sorting depend on rainstorm intensities and the size of cliff debris. Numerical experiments confirm that these two variables could have driven the landscape in the Negev Desert (Israel) toward an observed spatial contrast in topographic form over the past 10⁵–10⁶ years. For a given total storm rain depth, short‐duration higher‐intensity rainstorms are more erosive, resulting in greater cliff retreat distances relative to longer, low‐intensity storms. Temporal alternation between rainstorm regimes produces hillslope profiles similar to those previously attributed to Quaternary oscillations in the mean climate. We suggest that arid hillslopes may undergo considerable geomorphic transitions solely by alternating intra‐storm patterns regardless of rainfall amounts. 

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4. The cost of ectoparasitism in Cliff Swallows declines over 35 years

   https://doi.org/10.1002/ecm.1446  

   Brown, Charles R.; Hannebaum, Stacey L.; O’Brien, Valerie A.; Page, Catherine E.; Rannala, Bruce; Roche, Erin A.; Wagnon, Gigi S.; Knutie, Sarah A.; Moore, Amy T.; Brown, Mary B. (May 2021, Ecological Monographs)
5. Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments

   Sullivan, Ryan; Terry, Jordan K; Black, Benjamin; Dickerson, John P. (January 2022, Proceedings of the 39th International Conference on Machine Learning)

   Visualizing optimization landscapes has resulted in many fundamental insights in numeric optimization, specifically regarding novel improvements to optimization techniques. However, visualizations of the objective that reinforcement learning optimizes (the "reward surface") have only ever been generated for a small number of narrow contexts. This work presents reward surfaces and related visualizations of 27 of the most widely used reinforcement learning environments in Gym for the first time. We also explore reward surfaces in the policy gradient direction and show for the first time that many popular reinforcement learning environments have frequent "cliffs" (sudden large drops in expected reward). We demonstrate that A2C often "dives off" these cliffs into low reward regions of the parameter space while PPO avoids them, confirming a popular intuition for PPO’s improved performance over previous methods. We additionally introduce a highly extensible library that allows researchers to easily generate these visualizations in the future. Our findings provide new intuition to explain the successes and failures of modern RL methods, and our visualizations concretely characterize several failure modes of reinforcement learning agents in novel ways. 

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