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In the context of the accelerating impacts of climate change on permafrost landscapes, we use an uncrewed aerial vehicle (UAV) carrying a lidar scanner to investigate seasonal terrain changes in palsas – mounds of frozen peat – since other remote sensing methods have struggled to capture the full dynamics of these landforms. We investigated two palsas (4–5 m in height) in Sweden's largest palsa mire complex, where we performed five field campaigns between September 2022 and September 2023 to track intra-annual frost heave and thaw subsidence. Our approach allowed us to create digital terrain models (DTMs) from high-density point clouds (> 1000 points m−2) and analyze elevation changes over time. We found that both palsas heaved on average 0.15 m (and up to 0.30 m) from September to April and subsided back to their height from the previous year, or slightly below, over the course of the following summer. At one of the palsas, we observed a notable lateral degradation hotspot over the study period in a 225 m2 area, with 0.5–1.9 m height loss, likely initiated during the preceding warm and wet summer months. Part of this degradation occurred between September 2022 and April 2023, suggesting that the degradation of these palsas is not limited to the summer months. Our study shows the substantial value of using UAV lidar for understanding how permafrost areas are changing. It facilitates tracking the ongoing effects of climate change and highlights palsa dynamics that would not be captured by annual measurements alone.

The CryoGrid community model is a flexible toolbox for simulating the ground thermal regime and the ice–water balance for permafrost and glaciers, extending a well-established suite of permafrost models (CryoGrid 1, 2, and 3). The CryoGrid community model can accommodate a wide variety of application scenarios, which is achieved by fully modular structures through object-oriented programming. Different model components, characterized by their process representations and parameterizations, are realized as classes (i.e., objects) in CryoGrid. Standardized communication protocols between these classes ensure that they can be stacked vertically. For example, the CryoGrid community model features several classes with different complexity for the seasonal snow cover, which can be flexibly combined with a range of classes representing subsurface materials, each with their own set of process representations (e.g., soil with and without water balance, glacier ice). We present the CryoGrid architecture as well as the model physics and defining equations for the different model classes, focusing on one-dimensional model configurations which can also interact with external heat and water reservoirs. We illustrate the wide variety of simulation capabilities for a site on Svalbard, with point-scale permafrost simulations using, e.g., different soil freezing characteristics, drainage regimes, and snow representations, as well as simulations for glacier mass balance and a shallow water body. The CryoGrid community model is not intended as a static model framework but aims to provide developers with a flexible platform for efficient model development. In this study, we document both basic and advanced model functionalities to provide a baseline for the future development of novel cryosphere models.

Ground temperatures in coarse, blocky deposits such as mountain blockfields and rock glaciers have long been observed to be lower in comparison with other (sub)surface material. One of the reasons for this negative temperature anomaly is the lower soil moisture content in blocky terrain, which decreases the duration of the zero curtain in autumn. Here we used the CryoGrid community model to simulate the effect of drainage on the ground thermal regime and ground ice in blocky terrain permafrost at two sites in Norway. The model set-up is based on a one-dimensional model domain and features a surface energy balance, heat conduction and advection, as well as a bucket water scheme with adjustable lateral drainage. We used three idealized subsurface stratigraphies, blocks only, blocks with sediment and sediment only, which can be either drained (i.e. with strong lateral subsurface drainage) or undrained (i.e. without drainage), resulting in six scenarios. The main difference between the three stratigraphies is their ability to retain water against drainage: while the blocks only stratigraphy can only hold small amounts of water, much more water is retained within the sediment phase of the two other stratigraphies, which critically modifies the freeze–thaw behaviour. The simulation results show markedly lower ground temperatures in the blocks only, drained scenario compared to other scenarios, with a negative thermal anomaly of up to 2.2 ∘C. For this scenario, the model can in particular simulate the time evolution of ground ice, with build-up during and after snowmelt and spring and gradual lowering of the ice table in the course of the summer season. The thermal anomaly increases with larger amounts of snowfall, showing that well-drained blocky deposits are less sensitive to insulation by snow than other soils. We simulate stable permafrost conditions at the location of a rock glacier in northern Norway with a mean annual ground surface temperature of 2.0–2.5 ∘C in the blocks only, drained simulations. Finally, transient simulations since 1951 at the rock glacier site (starting with permafrost conditions for all stratigraphies) showed a complete loss of perennial ground ice in the upper 5 m of the ground in the blocks with sediment, drained run; a 1.6 m lowering of the ground ice table in the sediment only, drained run; and only 0.1 m lowering in the blocks only, drained run. The interplay between the subsurface water–ice balance and ground freezing/thawing driven by heat conduction can at least partly explain the occurrence of permafrost in coarse blocky terrain below the elevational limit of permafrost in non-blocky sediments. It is thus important to consider the subsurface water–ice balance in blocky terrain in future efforts in permafrost distribution mapping in mountainous areas. Furthermore, an accurate prediction of the evolution of the ground ice table in a future climate can have implications for slope stability, as well as water resources in arid environments.