Ice-wedge polygons are common features of lowland tundra in the continuous permafrost zone and prone to rapid degradation through melting of ground ice. There are many interrelated processes involved in ice-wedge thermokarst and it is a major challenge to quantify their influence on the stability of the permafrost underlying the landscape. In this study we used a numerical modelling approach to investigate the degradation of ice wedges with a focus on the influence of hydrological conditions. Our study area was Samoylov Island in the Lena River delta of northern Siberia, for which we had in situ measurements to evaluate the model. The tailored version of the CryoGrid 3 land surface model was capable of simulating the changing microtopography of polygonal tundra and also regarded lateral fluxes of heat, water, and snow. We demonstrated that the approach is capable of simulating ice-wedge degradation and the associated transition from a low-centred to a highcentred polygonal microtopography. The model simulations showed ice-wedge degradation under recent climatic conditions of the study area, irrespective of hydrological conditions. However, we found that wetter conditions lead to an earlier onset of degradation and cause more rapid ground subsidence. We set our findings in correspondence to observed types of ice-wedge polygons in the study area and hypothesized on remaining discrepancies between modelled and observed ice-wedge thermokarst activity. Our quantitative approach provides a valuable complement to previous, more qualitative and conceptual, descriptions of the possible pathways of ice-wedge polygon evolution. We concluded that our study is a blueprint for investigating thermokarst landforms and marks a step forward in understanding the complex interrelationships between various processes shaping ice-rich permafrost landscapes.

Abstract. The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.

Abstract. In this study we simulate the climatic mass balance of Svalbard glaciers with a coupled atmosphere–glacier model with 3 km grid spacing, from September 2003 to September 2013. We find a mean specific net mass balance of −257 mm w.e. yr−1, corresponding to a mean annual mass loss of about 8.7 Gt, with large interannual variability. Our results are compared with a comprehensive set of mass balance, meteorological, and satellite measurements. Model temperature biases of 0.19 and −1.9 °C are found at two glacier automatic weather station sites. Simulated climatic mass balance is mostly within about 100 mm w.e. yr−1 of stake measurements, and simulated winter accumulation at the Austfonna ice cap shows mean absolute errors of 47 and 67 mm w.e. yr−1 when compared to radar-derived values for the selected years 2004 and 2006. Comparison of modeled surface height changes from 2003 to 2008, and satellite altimetry reveals good agreement in both mean values and regional differences. The largest deviations from observations are found for winter accumulation at Hansbreen (up to around 1000 mm w.e. yr−1), a site where sub-grid topography and wind redistribution of snow are important factors. Comparison with simulations using 9 km grid spacing reveal considerable differences on regional and local scales. In addition, 3 km grid spacing allows for a much more detailed comparison with observations than what is possible with 9 km grid spacing. Further decreasing the grid spacing to 1 km appears to be less significant, although in general precipitation amounts increase with resolution. Altogether, the model compares well with observations and offers possibilities for studying glacier climatic mass balance on Svalbard both historically as well as based on climate projections.

Abstract. Earth system models (ESMs) are our primary tool for projecting future climate change, but their ability to represent small-scale land surface processes is currently limited. This is especially true for permafrost landscapes in which melting of excess ground ice and subsequent subsidence affect lateral processes which can substantially alter soil conditions and fluxes of heat, water, and carbon to the atmosphere. Here we demonstrate that dynamically changing microtopography and related lateral fluxes of snow, water, and heat can be represented through a tiling approach suitable for implementation in large-scale models, and we investigate which of these lateral processes are important to reproduce observed landscape evolution. Combining existing methods for representing excess ground ice, snow redistribution, and lateral water and energy fluxes in two coupled tiles, we show that the model approach can simulate observed degradation processes in two very different permafrost landscapes. We are able to simulate the transition from low-centered to high-centered polygons, when applied to polygonal tundra in the cold, continuous permafrost zone, which results in (i) a more realistic representation of soil conditions through drying of elevated features and wetting of lowered features with related changes in energy fluxes, (ii) up to 2 ∘C reduced average permafrost temperatures in the current (2000–2009) climate, (iii) delayed permafrost degradation in the future RCP4.5 scenario by several decades, and (iv) more rapid degradation through snow and soil water feedback mechanisms once subsidence starts. Applied to peat plateaus in the sporadic permafrost zone, the same two-tile system can represent an elevated peat plateau underlain by permafrost in a surrounding permafrost-free fen and its degradation in the future following a moderate warming scenario. These results demonstrate the importance of representing lateral fluxes to realistically simulate both the current permafrost state and its degradation trajectories as the climate continues to warm. Implementing laterally coupled tiles in ESMs could improve the representation of a range of permafrost processes, which is likely to impact the simulated magnitude and timing of the permafrost–carbon feedback.

Peat plateaus and palsas are characteristic morphologies of sporadic permafrost, and the transition from permafrost to permafrost‐free ground typically occurs on spatial scales of meters. They are particularly vulnerable to climate change and are currently degrading in Fennoscandia. Here we present a spatially distributed data set of ground surface temperatures for two peat plateau sites in northern Norway for the year 2015–2016. Based on these data and thermal modeling, we investigate how the snow depth and water balance modulate the climate signal in the ground. We find that mean annual ground surface temperatures are centered around 2 to 2.5 °C for stable permafrost locations and 3.5 to 4.5 °C for permafrost‐free locations. The surface freezing degree days are characterized by a noticeable threshold around 200 °C.day, with most permafrost‐free locations ranging below this value and most stable permafrost ones above it. Freezing degree day values are well correlated to the March snow cover, although some variability is observed and attributed to the ground moisture level. Indeed, a zero curtain effect is observed on temperature time series for saturated soils during winter, while drained peat plateaus show early freezing surface temperatures. Complementarily, modeling experiments allow identifying a drainage effect that can modify 1‐m ground temperatures by up to 2 °C between drained and water accumulating simulations for the same snow cover. This effect can set favorable or unfavorable conditions for permafrost stability under the same climate forcing.