Climate warming-related hydrological transformations are changing material mobilization, composition, and transport pathways along the terrestrial-aquatic continuum. Here, we integrate decade-long hydrometeorological and biogeochemical data from the High Arctic to show that annual fluvial energy is shifting from a skewed (snowmelt-dominated) to a multi-modal (snowmelt- and rainfall-dominated) distribution. This shift enhanced terrestrial-aquatic connectivity for dissolved and particulate material fluxes, but to overcome the watersheds’ buffering capacity for particulate material rainfall events had to increase by an order of magnitude. Permafrost disturbances (< 3 % of the watersheds’ areal extent) reduced watershed-scale DOC export enough to offset concurrent increased DOC export in undisturbed watersheds but play a weaker role in altering C export than the increased magnitude and frequency of late summer rainfall events. However, the disturbances have primed the landscape for accelerated geomorphic change when future rainfall magnitudes and consequent pluvial responses exceed the current buffering capacity of the terrestrial-aquatic continuum.

Abstract. Infrastructure built on perennially frozen ice-rich ground relies heavily on thermally stable subsurface conditions. Climate warming-induced deepening of ground thaw puts such infrastructure at risk of failure. For better assessing the risk of large-scale future damage to Arctic infrastructure, improved strategies for model-based approaches are urgently needed. We used the laterally-coupled one-dimensional heat conduction model CryoGrid3 to simulate permafrost degradation affected by linear infrastructure. We present a case study of a gravel road built on continuous permafrost (Dalton highway, Alaska) and forced our model under historical and strong future warming conditions (following the RCP8.5 scenario). As expected, the presence of a gravel road in the model leads to higher net heat flux entering the ground compared to a reference run without infrastructure, and thus a higher rate of thaw. Further, our results suggest that road failure is likely a consequence of lateral destabilization due to talik formation in the ground beside the road, rather than a direct consequence of a top-down thawing and deepening of the active layer below the road centre. In line with previous studies, we identify enhanced snow accumulation and ponding (both a consequence of infrastructure presence) as key factors for increased soil temperatures and road degradation. Using differing horizontal model resolutions we show that it is possible to capture these key factors and their impact on thawing dynamics with a low number of lateral model units, underlining the potential of our model approach for use in pan-arctic risk assessments. Our results suggest a general two-phase behaviour of permafrost degradation: an initial phase of slow and gradual thaw, followed by a strong increase in thawing rates after exceedance of a critical ground warming. The timing of this transition and the magnitude of thaw rate acceleration differ strongly between undisturbed tundra and infrastructure-affected permafrost ground. Our model results suggest that current model-based approaches which do not explicitly take into account infrastructure in their designs are likely to strongly underestimate the timing of future Arctic infrastructure failure. By using a laterally-coupled one-dimensional model to simulate linear infrastructure, we infer results in line with outcomes from more complex 2D- and 3D-models, but our model's computational efficiency allows us to account for long-term climate change impacts on infrastructure from permafrost degradation. Our model simulations underline that it is crucial to consider climate warming when planning and constructing infrastructure on permafrost as a transition from a stable to a highly unstable state can well occur within the service life time (about 30 years) of such a construction. Such a transition can even be triggered in the coming decade by climate change for infrastructure built on high northern latitude continuous permafrost that displays cold and relatively stable conditions today.

Abstract. It is well established that the Arctic strongly influences global climate through positive feedback processes (Cohen et al., 2014), one of the most effective being the sea-ice – albedo feedback (Screen et al., 2010). Understanding the region’s sensitivity to both internal and external forcings is a prerequisite to better forecast future global climate variations. Here, sedimentological evidence from an annually laminated (varved) record highlights that North Pacific climate variability has been a persistent regulator of the regional climate in the western Canadian Arctic. The varved record is negatively correlated with both the instrumental and reconstructed Pacific Decadal Oscillation (PDO) (D'arrigo et al., 2001; Gedalof et al., 2001; Macdonald et al., 2005; Mantua et al., 1997) throughout most of the last 700 years, suggesting drier conditions during high PDO phases, and vice-versa. This is in agreement with known regional teleconnections whereby the PDO is negatively and positively correlated with summer precipitation and mean sea level pressure, respectively. This pattern is also seen during the positive phase of the North Pacific Index (NPI) (Trenberth et al., 1994) in autumn. A reduced sea-ice cover during summer is observed in the region during PDO- (NPI+), as has been found during winter (Screen et al., 2016). Strongest during the autumn season, low-level southerly winds extend from the northernmost Pacific across the Bering Strait and can reach as far as the Western Canadian Arctic. These climate anomalies projecting onto the PDO- (NPI+) phase are key factors in enhancing evaporation and subsequent precipitation in this region. As projected sea-ice loss will contribute to enhanced future warming in the Arctic, future negative phases of the PDO (or NPI+) will likely act as amplifiers of this positive feedback (Screen et al., 2016).

Text 1 Chronological control The methods used to count varves rely on both visual examination of thin sections and the use of ~ 7000 microscopic images (1024 X 768 µm) obtained using a scanning electron microscope in backscattered mode. This technique allows for the identification of thin varves (< 0.4 mm), thus decreasing the chances of missing thin varves (Ojala et al., 2012). The chronology of the recent part of the record was also

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