Forecasting snow avalanche days from meteorological data using classification trees, Grasdalen, Western Norway.

Avalanches pose one of the most serious problems to infrastructure and people in the mountains in Norway. Processes leading to avalanche release are deterministic but the time and place of avalanche release is notoriously difficult to predict. Statistical approaches using meteorological parameters to predict the probability of natural avalanche release provide an alternative to deterministic prediction. We used classification trees to predict days with and without avalanches in the valley of Grasdalen in Western Norway based on meteorological parameters. A database with avalanche observations from almost 30 years was spatially and temporally coupled to grids of wind, precipitation and temperature. The grids were used because they provided more temporally consistent datasets than measurements from a local weather station. Avalanches were observed on 254 days and the same number of non-avalanche days was randomly selected. The optimal classification trees gave misclassification rates of 15% for all avalanche days, 18% for days with dry avalanches and 13% for days with wet avalanches. The most important meteorological parameters for the classification were the five-, one- and three-day sum of precipitation. Then followed wind speed, either measured as the maximum or mean over five days, three days or one day. Finally, daily temperature was important for the classification both alone and through a degree day parameter. Based on realistic scenarios for precipitation and temperature, our results imply that avalanche frequency will increase in the future. Further studies are needed to quantify this increase

Surface temperatures and their influence on the permafrost thermal regime in high-Arctic rock walls on Svalbard

Permafrost degradation in steep rock walls and associated slope destabilization have been studied increasingly in recent years. While most studies focus on mountainous and sub-Arctic regions, the occurring thermo-mechanical processes also play an important role in the high Arctic. A more precise understanding is required to assess the risk of natural hazards enhanced by permafrost warming in high-Arctic rock walls. This study presents one of the first comprehensive datasets of rock surface temperature measurements of steep rock walls in the high Arctic, comparing coastal and near-coastal settings. We applied the surface energy balance model CryoGrid 3 for evaluation, including adjusted radiative forcing to account for vertical rock walls. Our measurements comprise 4 years of rock surface temperature data from summer 2016 to summer 2020. Mean annual rock surface temperatures ranged from −0.6 in a coastal rock wall in 2017/18 to −4.3 ∘C in a near-coastal rock wall in 2019/20. Our measurements and model results indicate that rock surface temperatures at coastal cliffs are up to 1.5 ∘C higher than at near-coastal rock walls when the fjord is ice-free in winter, resulting from additional energy input due to higher air temperatures at the coast and radiative warming by relatively warm seawater. An ice layer on the fjord counteracts this effect, leading to similar rock surface temperatures to those in near-coastal settings. Our results include a simulated surface energy balance with shortwave radiation as the dominant energy source during spring and summer with net average seasonal values of up to 100 W m−2 and longwave radiation being the main energy loss with net seasonal averages between 16 and 39 W m−2. While sensible heat fluxes can both warm and cool the surface, latent heat fluxes are mostly insignificant. Simulations for future climate conditions result in a warming of rock surface temperatures and a deepening of active layer thickness for both coastal and near-coastal rock walls. Our field data present a unique dataset of rock surface temperatures in steep high-Arctic rock walls, while our model can contribute towards the understanding of factors influencing coastal and near-coastal settings and the associated surface energy balance

Understanding the drivers of extensive plant damage in boreal and Arctic ecosystems: Insights from field surveys in the aftermath of damage.

The exact cause of population dieback in nature is often challenging to identify retrospectively. Plant research in northern regions has in recent decades been largely focussed on the opposite trend, namely increasing populations and higher productivity. However, a recent unexpected decline in remotely-sensed estimates of terrestrial Arctic primary productivity suggests that warmer northern lands do not necessarily result in higher productivity. As large-scale plant dieback may become more frequent at high northern latitudes with increasing frequency of extreme events, understanding the drivers of plant dieback is especially urgent. Here, we report on recent extensive damage to dominant, short, perennial heath and tundra plant populations in boreal and Arctic Norway, and assess the potential drivers of this damage. In the High-Arctic archipelago of Svalbard, we recorded that 8-50% of Cassiope tetragona and Dryas octopetala shoots were dead, and that the ratios of dead shoots increased from 2014 to 2015. In boreal Norway, 38-63% of Calluna vulgaris shoots were dead, while Vaccinium myrtillus had damage to 91% of shoots in forested sites, but was healthy in non-forested sites. Analyses of numerous sources of environmental information clearly point towards a winter climate-related reason for damage to three of these four species. In Svalbard, the winters of 2011/12 and 2014/15 were documented to be unusually severe, i.e. insulation from ambient temperature fluctuation by snow was largely absent, and ground-ice enforced additional stress. In boreal Norway, the 2013/14 winter had a long period with very little snow combined with extremely low precipitation rates, something which resulted in frost drought of uncovered Calluna plants. However, extensive outbreaks of a leaf-defoliating geometrid moth were identified as the driver of Vaccinium mortality. These results suggest that weather and biotic extreme events potentially have strong impacts on the vegetation state of northern lands

A new approach to meteorological observations on remote polar glaciers using open-source internet of things technologies

Key regions of the world lack sufficient infrastructure to collect geophysical observations, often due to logistical challenges such as difficult accessibility and cost. With the advent of Internet-of-Things (IoT) technologies and low-cost electronics, it is possible today to build monitoring systems collecting spatially distributed, in-situ data with real-time connectivity to online servers for immediate and long-term usage at costs comparable to those of a single autonomous weather station. We present here a custom-built, modular system that collects quality data, and, that is, robust to adverse meteorological conditions and lack of energy. It integrates commercial and custom-built sensors connected to a node (main device) that manages power, data and radio communication. Data is sent to gateways and then to a server that parses, stores and quality controls the data. We deployed two networks in the vicinity of Ny-Ålesund in Svalbard, and operated from May 2021 to April 2022 to measure meteorological and glaciological variables. Our system collected reliable data and had sufficient power resources to survive 4–5 months of darkness during the polar night. Here, we present the design considerations and performance metrics, report our lessons learned from this challenging deployment, and suggest pathways for future improvements

Impact of Multiple Ecological Stressors on a Sub-Arctic Ecosystem: No Interaction Between Extreme Winter Warming Events, Nitrogen Addition and Grazing

Climate change is one of many ongoing human-induced environmental changes, but few studies consider interactive effects between multiple anthropogenic disturbances. In coastal sub-arctic heathland, we quantified the impact of a factorial design simulating extreme winter warming (WW) events (7 days at 6–7∘C) combined with episodic summer nitrogen (+N) depositions (5 kg N ha-1) on plant winter physiology, plant community composition and ecosystem CO2 fluxes of an Empetrum nigrum dominated heathland during 3 consecutive years in northern Norway. We expected that the +N would exacerbate any stress effects caused by the WW treatment. During WW events, ecosystem respiration doubled, leaf respiration declined (-58%), efficiency of Photosystem II (Fv/Fm) increased (between 26 and 88%), while cell membrane fatty acids showed strong compositional changes as a result of the warming and freezing. In particular, longer fatty acid chains increased as a result of WW events, and eicosadienoic acid (C20:2) was lower when plants were exposed to the combination of WW and +N. A larval outbreak of geometrid moths (Epirrita autumnata and Operophtera brumata) following the first WW led to a near-complete leaf defoliation of the dominant dwarf shrubs E. nigrum (-87%) and Vaccinium myrtillus (-81%) across all experimental plots. Leaf emergence timing, plant biomass or composition, NDVI and growing season ecosystem CO2 fluxes were unresponsive to the WW and +N treatments. The limited plant community response reflected the relative mild winter freezing temperatures (-6.6∘C to -11.8∘C) recorded after the WW events, and that the grazing pressure probably overshadowed any potential treatment effects. The grazing pressure and WW both induce damage to the evergreen shrubs and their combination should therefore be even stronger. In addition, +N could have exacerbated the impact of both extreme events, but the ecosystem responses did not support this. Therefore, our results indicate that these sub-arctic Empetrum-dominated ecosystems are highly resilient and that their responses may be limited to the event with the strongest impact

Permanent fast flow versus cyclic surge behaviour: numerical simulations of the Austfonna ice cap, Svalbard

A large part of the ice flux within ice caps occurs through spatially limited fast-flowing units. Some of them permanently maintain fast flow, whereas others operate in an oscillatory mode, characterized by short-lived active phases followed by long quiescent phases. This surge-type behaviour results from intrinsic rather than external factors, thus complicating estimates of glacier response to climate change. Here we present numerical model results from Austfonna, an ice cap on Svalbard that comprises several surge-type basins. Previous studies have suggested a thermally controlled soft-bed surge mechanism for Svalbard. We systematically change the parameters that govern the nature of basal motion and thereby control the transition between permanent and oscillatory fast flow. Surge-type behaviour is realized by a relatively abrupt onset of basal sliding when basal temperatures approach the pressure-melting point and enhanced sliding of marine grounded ice. Irrespective of the dynamic regime, the absence of considerable volumes of temperate ice, both in the observed and simulated ice cap, indicates that fast flow is accomplished by basal motion over a temperate bed. Given an idealized present-day climate, the equilibrium ice-cap size varies significantly, depending on the chosen parameters

Changes in winter warming events in the Nordic Arctic Region

In recent years extreme winter warming events have been reported in arctic areas. These events are characterized as extraordinarily warm weather episodes, occasionally combined with intense rainfall, causing ecological disturbance and challenges for arctic societies and infrastructure. Ground-ice formation due to winter rain or melting prevents ungulates from grazing, leads to vegetation browning, and impacts soil temperatures. The authors analyze changes in frequency and intensity of winter warming events in the Nordic arctic region—northern Norway, Sweden, and Finland, including the arctic islands Svalbard and Jan Mayen. This study identifies events in the longest available records of daily temperature and precipitation, as well as in future climate scenarios, and performs analyses of long-term trends for climate indices aimed to capture these individual events. Results show high frequencies of warm weather events during the 1920s–30s and the past 15 years (2000–14), causing weak positive trends over the past 90 years (1924–2014). In contrast, strong positive trends in occurrence and intensity for all climate indices are found for the past 50 years with, for example, increased rates for number of melt days of up to 9.2 days decade−1 for the arctic islands and 3–7 days decade−1 for the arctic mainland. Regional projections for the twenty-first century indicate a significant enhancement of the frequency and intensity of winter warming events. For northern Scandinavia, the simulations indicate a doubling in the number of warming events, compared to 1985–2014, while the projected frequencies for the arctic islands are up to 3 times higher

Measured and modeled historical precipitation trends for Svalbard

Abstract Precipitation plays an important role in the Arctic hydrological cycle, affecting different areas like the surface energy budget and the mass balance of glaciers. Thus, accurate measurements of precipitation are crucial for physical process studies, but gauge measurements in the Arctic are sparse and subject to relocations and several gauge issues. From Svalbard, we analyze precipitation trends at six weather stations for the last 50–100 years by combining different observation series and adjusting for inhomogeneities. For the past 50 years, the measured annual precipitation has increased by 30%–45%. However, precipitation measurements in the cold and windy climate are strongly influenced by gauge undercatch. Correcting for undercatch reduces the trend values by 10% points, since the fraction of solid precipitation has decreased and undercatch is larger for solid precipitation. Thus, precipitation corrected for undercatch should be used to study “true” precipitation trends in the Arctic. Precipitation over Svalbard has been modeled by downscaling reanalysis data to a spatial resolution of 1 km. In general, the modeled annual precipitation is higher (13%–175%) than the measured values and mainly higher than the precipitation corrected for undercatch. Although the model resolves orographic effects on a regional scale, the downscaling is not able to reproduce local orographic enhancement for onshore winds, nor local effects of rain shadow. The downscaled dataset explains approximately 60% of the interannual precipitation variability. The model-based trends during 1979–2018 are positive, but weaker (~4% decade −1 ) than the observed (~8% decade −1 ) trends