Permafrost thaw can accelerate climate warming by releasing carbon from previously frozen soil in the form of greenhouse gases. Rainfall extremes have been proposed to increase permafrost thaw, but the magnitude and duration of this effect are poorly understood. Here we present empirical evidence showing that one extremely wet summer (+100 mm; 120% increase relative to average June–August rainfall) enhanced thaw depth by up to 35% in a controlled irrigation experiment in an ice-rich Siberian tundra site. The effect persisted over two subsequent summers, demonstrating a carry-over effect of extremely wet summers. Using soil thermal hydrological modelling, we show that rainfall extremes delayed autumn freeze-up and rainfall-induced increases in thaw were most pronounced for warm summers with mid-summer precipitation rainfall extremes. Our results suggest that, with rainfall and temperature both increasing in the Arctic, permafrost will likely degrade and disappear faster than is currently anticipated based on rising air temperatures alone.

Permafrost thaw can cause an intensification of climate change through the release of carbon as greenhouse gases. While the effect of air temperature on permafrost thaw is well quantified, the effect of rainfall is highly variable and not well understood. Here, we provide a literature review of studies reporting on effects of rainfall on ground temperatures in permafrost environments and use a numerical model to explore the underlying physical mechanisms under different climatic conditions. Both the evaluated body of literature and the model simulations indicate that continental climates are likely to show a warming of the subsoil and hence increased end of season active layer thickness, while maritime climates tend to respond with a slight cooling effect. This suggests that dry regions with warm summers are prone to more rapid permafrost degradation under increased occurrences of heavy rainfall events in the future, which can potentially accelerate the permafrost carbon feedback.

Modeling the physical state of permafrost landscapes is a crucial addition to field observations in order to understand the feedback mechanisms between permafrost and the atmosphere within a warming climate. A common hypothesis in permafrost modeling is that vertical heat conduction is most relevant to derive subsurface temperatures. While this approach is mostly applicable to flat landscapes with little topography, landscapes with more topography are subject to lateral flow processes as well. With our study, we contribute to the growing body of evidence that lateral surface and subsurface processes can have a significant impact on permafrost temperatures and active layer properties. We use a numerical model to simulate two idealized hillslopes (a steep and a medium case) with inclinations that can be found in Adventdalen, Svalbard, and compare them to a flat control case. We find that ground temperatures within the active layer uphill are generally warmer than downhill in both slopes (with a difference of up to ∼0.8 ^∘C in the steep and ∼0.6 ^∘C in the medium slope). Further, the slopes are found to be warmer in the uphill section and colder in the base of the slopes compared to the flat control case. As a result, maximum thaw depth increases by about 5 cm from the flat (0.98 m) to the medium (1.03 m) and the steep slope (1.03 m). Uphill warming on the slopes is explained by overall lower heat capacity, additional energy gain through infiltration, and lower evaporation rates due to drier conditions caused by subsurface runoff. The major governing process causing the cooling on the downslope side is heat loss to the atmosphere through evaporation in summer and enhanced heat loss in winter due to wetter conditions and resulting increased thermal conductivity. On a catchment scale, these results suggest that temperature distributions in sloped terrain can vary considerably compared to flat terrain, which might impact the response of subsurface hydrothermal conditions to ongoing climate change.

Precipitation is a central quantity of hydrometeorological research and applications. Especially in complex terrain, such as in High Mountain Asia (HMA), surface precipitation observations are scarce. Gridded precipitation products are one way to overcome the limitations of ground truth observations. They can provide datasets continuous in both space and time. However, there are many products available, which use various methods for data generation and lead to different precipitation values. In our study we compare nine different gridded precipitation products from different origins (ERA5, ERA5-Land, ERA-interim, HAR v2 10 km, HAR v2 2 km, JRA-55, MERRA-2, GPCC and PRETIP) over a subregion of the Central Himalaya and the Southwest Tibetan Plateau, from May to September 2017. Total spatially averaged precipitation over the study period ranged from 411 mm (GPCC) to 781 mm (ERA-Interim) with a mean value of 623 mm and a standard deviation of 132 mm. We found that the gridded products and the few observations, with few exceptions, are consistent among each other regarding precipitation variability and rough amount within the study area. It became obvious that higher grid resolution can resolve extreme precipitation much better, leading to overall lower mean precipitation spatially, but higher extreme precipitation events. We also found that generally high terrain complexity leads to larger differences in the amount of precipitation between products. Due to the considerable differences between products in space and time, we suggest carefully selecting the product used as input for any research application based on the type of application and specific research question. While coarse products such as ERA-Interim or ERA5 that cover long periods but have coarse grid resolution have previously shown to be able to capture long-term trends and help with identifying climate change features, this study suggests that more regional applications, such as glacier mass-balance modeling, require higher spatial resolution, as is reproduced, for example, in HAR v2 10 km.

In this study, energy and mass balance is quantified using an energy balance model to represent the glacier melt of Urumqi Glacier No. 1, Chinese Tian Shan. Based on data from an Automatic Weather Station (4025 m a.s.l) and the mass balance field survey data nearby on the East Branch of the glacier, the “COupled Snowpack and Ice surface energy and Mass balance model” (COSIMA) was used to derive energy and mass balance simulations during the ablation season of 2018. Results show that the modeled cumulative mass balance (−0.67 ± 0.03 m w.e.) agrees well with the in-situ measurements (−0.64 ± 0.16 m w.e.) (r² = 0.96) with the relative difference within 5% during the study period. The correlation coefficient between modeled and observed surface temperatures is 0.88 for daily means. The main source of melt energy at the glacier surface is net shortwave radiation (84%) and sensible heat flux (16%). The energy expenditures are from net longwave radiation (55%), heat flux for snow/ice melting (32%), latent heat flux of sublimation and evaporation (7%), and subsurface heat flux (6%). The sensitivity testing of mass balance shows that mass balance is more sensitive to temperature increase and precipitation decrease than temperature decrease and precipitation increase.

Permafrost carbon, stored in frozen organic matter across vast Arctic and sub-Arctic regions, represents a substantial and increasingly vulnerable carbon reservoir. As global temperatures rise, the accelerated thawing of permafrost releases greenhouse gases, exacerbating climate change. However, freshly thawed permafrost carbon may also experience lateral transport by groundwater flow to surface water recipients such as rivers and lakes, increasing the terrestrial-to-aquatic transfer of permafrost carbon. Mobilization and subsurface transport mechanisms are poorly understood and not accounted for in global climate models, leading to high uncertainties in the predictions of the permafrost carbon feedback. Here, we focus on a hillslope in Endalen Valley, Svalbard, as a representative example of a high-Arctic hillslope underlain by continuous permafrost. We analyze solute transport in the form of a non-reactive tracer representing dissolved organic carbon (DOC) using a physics-based numerical model with the objective to study governing cryotic and hydrodynamic transport mechanisms relevant for warming permafrost regions. We first analyze transport times for DOC pools at different locations within the active layer under present-day climatic conditions and proceed to study susceptibility for deeper ancient carbon release in the upper permafrost due to thaw under different warming scenarios. Results suggest that DOC in the active layer near the permafrost table experiences rapid lateral transport upon thaw due to saturated conditions and lateral flow, while DOC close to the ground surface experiences slower transport due to flow in unsaturated soil. Deeper permafrost carbon release exhibits vastly different transport behaviors depending on warming and thaw rate. Gradual warming leads to small fractions of DOC being mobilized every year, while the majority moves vertically through percolation and cryosuction. Abrupt thaw resulting from a single very warm year leads to faster lateral transport times, similar to active layer DOC released in saturated conditions. Lastly, we analyze the potential susceptibility of DOC to mineralization to CO₂ prior to export due to soil moisture and temperature conditions. We find that high liquid saturation during transport coincides with very low mineralization rates and potentially inhibits mineralization into CO₂ before export. Overall, the results highlight the importance of subsurface hydrologic and thermal conditions for the retention and lateral export of permafrost carbon by subsurface flow.