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A local climate perspective on possible development pathways for Longyearbyen, Svalbard

Published online by Cambridge University Press:  13 December 2024

Igor Esau*
Affiliation:
UiT - The Arctic University of Norway, Tromsø, Norway Nansen Environmental and Remote Sensing Center, Bergen, Norway
Victoria Miles
Affiliation:
Nansen Environmental and Remote Sensing Center, Bergen, Norway
*
Corresponding author: Igor Esau; Email:[email protected]
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Abstract

Arctic human settlements experience formidable challenges from accelerating climate change and environmental transformations. While these towns have demonstrated adaptive resilience, the looming threat of local climate extremes raises concerns about the results of adaptation and mitigation efforts. With the further development of Arctic settlements, it is necessary to consider changes in local climatic conditions, shifting the adaptation focus from regional to local scales. The local climate perspective in this literature synthesis study is built upon constraints from physical climatology, focused on the climate and environment within and around the town of Longyearbyen, Svalbard. The study provides insights into Longyearbyen’s local climate dynamics, including physical mechanisms, climate localisation, factors and trends, as well as their implications. Three model pathways for development are discussed, centred on (1) industrial development, (2) public services, and (3) tourism and conservation. This categorisation is introduced to distinguish development scenario sensitivity to the local climate effects. The synthesis indicates that any development concentrated spatially will amplify local warming and climate change, as positive climate feedback predominate. The study emphasises the need for a comprehensive understanding of the environmental factors sustaining local climatic anomalies.

Type
Review Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Introduction

Climate change influences the long-term trends of temperature and weather patterns on global and regional scales. At local geographical scales from 1 km to 100 km, its impacts are not only significant but also more profound, especially in the Arctic (Stuecker et al., Reference Stuecker, Bitz, Armour, Proistosescu, Kang, Xie and Jin2018). The effects of climate change on global and regional levels have been the focus of attention, whereas local climate effects have yet to be generalised or summarised. Fundamental questions relate to the physical mechanisms behind locally amplified climate extremes and the degree to which local extremes may exceed regional climate change. These and similar research questions are frequently addressed in physical and human geography (Hancock, Prokop, Eckerstorfer, & Hendrikx, Reference Hancock, Prokop, Eckerstorfer and Hendrikx2018; Streletskiy, Suter, Shiklomanov, Porfiriev, & Eliseev, Reference Streletskiy, Suter, Shiklomanov, Porfiriev and Eliseev2019; Suter, Streletskiy, & Shiklomanov, Reference Suter, Streletskiy and Shiklomanov2019). However, only fragmentary work has touched on physical climatology (Zhang et al., Reference Zhang, Miller, Jansson, Samuelsson, Mao and Smith2018). This study aims to address these questions by synthesising a local climate perspective from fragmented publications scattered across diverse disciplinary studies. We focus on physical climate change and its effects on the physical environment within and around the town of Longyearbyen, Svalbard. We analyse the density of in situ and high-resolution satellite observations and detailed research studies sufficient to distinguish between climate trends in closely situated locations. We then investigate the influential climate parameters and physical mechanisms and evaluate the magnitude of their local modifications, factors and trends. Finally, we discuss the implications of the local climate perspective for different development pathways for Longyearbyen and Svalbard. This is important for bridging the gap between physical and societal sustainability transformations in the Arctic.

The Arctic was – and still is – an inhospitable and remote region with a cold climate and harsh weather. The Arctic region is undergoing influential environmental transitions, and regional warming is accelerating (Taylor et al., Reference Taylor, Boeke, Boisvert, Feldl, Henry, Huang and Tan2022) and is more than four times stronger than the global average (Overland, Wang, Walsh, & Stroeve, Reference Overland, Wang, Walsh and Stroeve2014; Rantanen et al., Reference Rantanen, Karpechko, Lipponen, Nordling, Hyvärinen, Ruosteenoja and Laaksonen2022; Isaksen et al., Reference Isaksen, Nordli, Ivanov, Køltzow, Aaboe, Gjelten and Karandasheva2022b). This amplification is reflected in many essential climate variables and environmental indicators (Box et al., Reference Box, Colgan, Christensen, Schmidt, Lund, Parmentier and Olsen2019), particularly in sea ice retreat and multiyear ice disappearance (Liu, Key, Wang, & Tschudi, Reference Liu, Key, Wang and Tschudi2020). Evidence of ecological transitions (Myers-Smith et al., Reference Myers-smith, Kerby, Phoenix, Bjerke, Epstein, Assmann and Wilmking2020), coastal erosion (Jaskólski, Pawłowski, & Strzelecki, Reference Jaskólski, Pawłowski and Strzelecki2018), and destabilisation of frozen grounds under infrastructural objects (Hjort et al., Reference Hjort, Karjalainen, Aalto, Westermann, Romanovsky, Nelson and Luoto2018) are found all over the Arctic.

Svalbard is a High Arctic archipelago at the northernmost reaches of warm Atlantic Waters at about 80°N – it is at the forefront of climate and environmental change (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019). Exceptional warming has been found across and to the east of Svalbard (Isaksen et al., Reference Isaksen, Nordli, Førland, Łupikasza, Eastwood and Niedźwiedź2016, Reference Isaksen, Nordli, Ivanov, Køltzow, Aaboe, Gjelten and Karandasheva2022b). Due to local environmental changes in Svalbard, risks to infrastructure, ecological habitats, and human adaptation are increasing (Winther & Gudmestad, Reference Winther and Gudmestad2023). Although non-climatic factors dominate the ability of Arctic communities to adapt to and mitigate climate change (Ford, McDowell, & Pearce, Reference Ford, McDowell and Pearce2015), this significant local increase in Arctic warming exacerbates the vulnerability of Svalbard communities. (Hestnes, Bakkehøi, & Jaedicke, Reference Hestnes, Bakkehøi and Jaedicke2016; Hovelsrud, Kaltenborn, & Olsen, Reference Hovelsrud, Kaltenborn and Olsen2020). There is an urgent need for research to address local climate change in Svalbard, especially since traditional engineering methods of “techno-fixing” are ineffective against locally intensifying changes. (Winther & Gudmestad, Reference Winther and Gudmestad2023).

The longest temperature record in the High Arctic has been established for Longyearbyen, extending more than a century (Nordli et al., Reference Nordli, Wyszyński, Gjelten, Isaksen, Łupikasza, Niedźwiedź and Przybylak2020). The record reveals winter warming exceeding +10°C since 1991 and amplified warming across all seasons (Nordli et al., Reference Nordli, Wyszyński, Gjelten, Isaksen, Łupikasza, Niedźwiedź and Przybylak2020). Summer heatwaves in 2020 (Dobricic, Russo, Pozzoli, Wilson, & Vignati, Reference Dobricic, Russo, Pozzoli, Wilson and Vignati2020; Overland & Wang, Reference Overland and Wang2021) and 2022 (Nilsen, Reference Nilsen2022) broke climatic temperature records in many Arctic places. Longyearbyen recorded its record-high temperature of +21.7°C on 25 July 2020, as documented at the Svalbard Airport station. That heat event had profound consequences. Built into permafrost, the Svalbard Global Seed Vault, where thousands of crop seeds are stored, is threatened by thawing permafrost. (Vaughan, Reference Vaughan2020). Mine 7, which produces 60,000 tons of coal annually for export and the local coal-fired power station, temporarily ceased operations after being damaged by flooding (Jonassen, Reference Jonassen2020). This seemingly well-protected underground mining was surprisingly sensitive to climate warming. Those examples manifest the vulnerability of the biophysical and human environment to locally amplified climate extremes. A crucial inquiry emerges regarding the potential of local climate changes to elevate vulnerability within Arctic societies and surpass resilience thresholds in their physical environments.

Meyer (Reference Meyer2022) recognised a “techno-fix” bias in current adaptation practices in Longyearbyen. These practices imply a narrow understanding of adaptation and do not address the more challenging task of transforming society. Simultaneously, Winther and Gudmestad (Reference Winther and Gudmestad2023) warned that a techno-fix would require innovations as traditional techniques may fail under the combined pressure of locally amplified geohazards, e.g. increasing coastal erosion, soil moisture, and permafrost thaw. Ignoring local climate prospects can cause maladaptation and negative consequences. Place-based knowledge is crucial for successful adaptation (Fedorov, Reference Fedorov2019; Meyer, Reference Meyer2022). Following studies in ecology (Colloff, Wise, Palomo, Lavorel, & Pascual, Reference Colloff, Wise, Palomo, Lavorel and Pascual2020), maintenance of a declining resource, e.g. permafrost maintenance with a thermosyphon technology (Aftret & Daleng, Reference Aftret and Daleng2022), might become a case of maladaptation in Longyearbyen.

Since the 1990s, climate issues have become essential for the Arctic urban development agenda (Petrov et al., Reference Petrov, BurnSilver, Chapin, Fondahl, Graybill, Keil and Schweitzer2016; Shiklomanov, Streletskiy, Swales, & Kokorev, Reference Shiklomanov, Streletskiy, Swales and Kokorev2016; Orttung et al., Reference Orttung, Laruelle, Anisimov, Streletskiy, Shiklomanov and Cooper2017). Some Arctic towns, such as Utqiagvik (formerly Barrow, Alaska), may have to relocate (Lynch & Brunner Reference Lynch and Brunner2007); others, such as Norilsk (Russia), have to restructure and rebuild (Shiklomanov, Streletskiy, Grebenets, & Suter, Reference Shiklomanov, Streletskiy, Grebenets and Suter2017). For some towns, such as Vorkuta (Russia), the effects of combined socio-economic and climate changes are overwhelming (Shiklomanov, Streletskiy, Suter, Orttung, & Zamyatina, Reference Shiklomanov, Streletskiy, Suter, Orttung and Zamyatina2020; Kotov & Khilimonyuk Reference Kotov and Khilimonyuk2021). Under increasing socio-economic pressure, local climatic factors are becoming critical for proper adaptation to climate change. A local climate perspective is a perspective that focuses on the specific climate conditions and patterns of a smaller geographic area. In the context of Longyearbyen, the town faces one of the strongest climatic warming followed by influential environmental changes (Vickers et al., Reference Vickers, Høgda, Solbø, Karlsen, Tømmervik, Aanes and Hansen2016). The warm West Spitsbergen Current keeps the ocean to the southwest of the islands free of sea ice (Frank, Jonassen, Skogseth, & Vihma, Reference Frank, Jonassen, Skogseth and Vihma2023). It makes Longyearbyen logistically more accessible than other parts of the Arctic, facilitating tourism development (Bystrowska, Reference Bystrowska2019), mineral resources, and fisheries exploitation (Stocker, Renner, & Knol-Kauffman, Reference Stocker, Renner and Knol-Kauffman2020). Two processes – climate change and socio-economic shifts – shape Longyearbyen´s concerns and debates (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020, Meyer, Reference Meyer2022). Climate change is a global issue that affects local communities differently. To effectively address the issue, it is crucial to consider every community’s distinct outlook and necessity. This synthesis study looks at how local climate impacts can shape development pathways. Researchers have been exploring the co-effects approach, which considers the interconnectedness of different climate impacts. For example, Dannevig et al. (Reference Dannevig, Søreide, Sveinsdóttir, Olsen, Hovelsrud, Rusdal and Dale2023) studied the effects of climate change on nature-based tourism in Svalbard and found that it can have cascading impacts. Winther and Gudmestad (Reference Winther and Gudmestad2023) reviewed the local climate problems in Longyearbyen and suggested ways to address them.

Our study examines local perspectives on physical climatology by selecting and analysing the literature on the main climate variables in the Longyearbyen area. We reviewed all relevant papers and several technical and student reports, which can be found by searching Google Scholar™ requests (63 records in total as of August 2, 2023). The literature search query is based on terms related to “local climate,” “meteorology,” “observational data,” and the like. We considered publication providing for climate variables at spatial scales finer than 10 km around the Longyearbyen. If there is a chain or a nest of related publications, we consider only the most relevant publications to elucidate physical mechanisms. In this study, we have examined the references related to essential climate variables that are considered influential factors in Longyearbyen’s societal transformation. We acknowledge that the references outside physical climatology are patchy and subjective. However, our objective is to identify publications that can bridge the gap between physical and societal sustainability transformations.

Understanding Longyearbyen’s unique climate: geographical features, weather patterns, and environmental impacts

Longyearbyen (78°13’N, 15°38’E) is a town of unique geographical and climatic features. It is located on Spitsbergen, the largest island of the Svalbard archipelago (Fig. 1). At this latitude, the polar night lasts from November 14 to January 29, and the midnight sun lasts from April 20 to August 22. The town, with a population of about 2,300, is nestled in a narrow, steep-sided valley on the southern side of the Adventfjorden, the entrance to the larger Isfjord that opens into the Atlantic Ocean on the western side of Svalbard. The mountains surrounding the city exhibit flat, ice-covered peaks and steep, crumbling slopes, which significantly influence local temperature contrasts and spatial differences in snow accumulation and soil moisture. The prevalence of permafrost necessitates the construction of buildings on piles for improved ventilation above frozen ground (Bekele & Sinitsyn, Reference Bekele and Sinitsyn2017), and all communications and utilities require additional insulation. The West Spitsbergen Current, with its relatively warm waters, plays a crucial role in keeping sea ice away from the coastline, although not at a considerable distance (Frank et al., Reference Frank, Jonassen, Skogseth and Vihma2023), thereby influencing the local climate of Longyearbyen.

Figure 1. The map of Longyearbyen and its surrounding area with identified locations of observational sites. The main station at the Svalbard airport is shown as a red dot with a black circle. Stations of the Norwegian Meteorological Institute (MET.NORWAY) are shown in red; stations of the University Centre in Svalbard (UNIS) – in blue; and the private citizens’ stations NETATMO – in grey. The background topographic map is taken from TopoSvalbard (https://toposvalbard.npolar.no; The Norwegian Polar Institute).

Svalbard’s climate is categorized as a polar tundra (ET) climate under the Köppen-Geiger classification system. (Kottek, Grieser, Beck, Rudolf, & Rubel, Reference Kottek, Grieser, Beck, Rudolf and Rubel2006). Numerous research works have established connections between the long-distance meridional transfer of heat and moisture and the fluctuations in daily air temperature and precipitation patterns in Svalbard (Osuch & Wawrzyniak Reference Osuch and Wawrzyniak2017; Pithan et al., Reference Pithan, Svensson, Caballero, Chechin, Cronin, Ekman, Neggers and Wendisch2018). The meridional heat transport in the mid-atmosphere (3–7 km above the ground) is a key mechanism supporting the lower atmospheric stability and local climate anomalies (Feldl, Bordoni, & Merlis, Reference Feldl, Bordoni and Merlis2017; Stuecker et al., Reference Stuecker, Bitz, Armour, Proistosescu, Kang, Xie and Jin2018; Esau et al., Reference Esau, Pettersson, Cancet, Chapron, Chernokulsky, Donlon and Johannesen2023). The local climate experiences alternating impacts of the western (wet and cool) and eastern (dry and cold) climate regimes (Esau, Argentini, Przybylak, Repina, & Sjöblom, Reference Esau, Argentini, Przybylak, Repina and Sjöblom2012; Pilguj, Kolendowicz, Kryza, Migała, & Czernecki, Reference Pilguj, Kolendowicz, Kryza, Migała and Czernecki2019; Łupikasza, Niedźwiedź, Przybylak, & Nordli, Reference Łupikasza, Niedźwiedź, Przybylak and Nordli2021). There are also regular climate differences on the local scales. The mildest climate is found along the western coast (Vikhamar-Schuler, Lutz, & Gjelten, Reference Vikhamar-Schuler, Lutz and Gjelten2019). The mean temperature drops considerably in the inner and eastern parts of the island, for example, along the Svalbard Airport-Advent valley axis over just a few kilometres (Gjelten et al., Reference Gjelten, Nordli, Isaksen, Førland, Sviashchennikov, Wyszynski and Urazgildeeva2016). This land-sea temperature gradient drives the Advent Valley´s local winds (breeze) (Henkies, Høyland, Shestov, Duscha, & Sjöblom, Reference Henkies, Høyland, Shestov, Duscha and Sjöblom2023). Summer temperatures in Longyearbyen remain above freezing, and the melting season (122 days on average during 1991–2018) is surprisingly long for such high latitudes. The 21st century has witnessed warm winters, coinciding with the reduction (from 50% to less than 10%) of the sea ice cover in Isfjorden (Nilsen, Cottier, Skogseth, & Mattsson, Reference Nilsen, Cottier, Skogseth and Mattsson2008; Muckenhuber, Nilsen, Korosov, & Sandven, Reference Muckenhuber, Nilsen, Korosov and Sandven2016).

Advancements in satellite observations, data synthesis, and modelling for studying Svalbard’s local climate

Unlike global, pan-Arctic, and regional assessments, local climate information is often fragmented and overlooked (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019). An essential component of local climate research is satellite observations. Recent advances in polar-orbiting satellite observations have made remote-sensing products indispensable for Arctic climate research (Esau et al., Reference Esau, Pettersson, Cancet, Chapron, Chernokulsky, Donlon and Johannesen2023). Local climate studies benefit from satellite observations, allowing monitoring of large areas at metre-scale spatial resolution (Duncan et al., Reference Duncan, Ott, Abshire, Brucker, Carroll, Carton and Wu2020). The Svalbard Integrated Arctic Earth Observing System (SIOS) is an international consortium developing an efficient observing system for long-term in situ measurements and remote sensing in Svalbard (Jawak et al., Reference Jawak, Pohjola, Kääb, Andersen, Błaszczyk, Salzano and Fjæraa2023). Satellite platforms (e.g. the Sentinel and Landsat series) provide data in multiple wavelength bands at metre-scale resolution. The data could be openly accessed through SIOS, COPERNICUS, and Earth Observer initiatives. Another component of local climate research includes a network of routine meteorological and ground-based observations (Wickström, Jonassen, Cassano, & Vihma, Reference Wickström, Jonassen, Cassano and Vihma2020) and networks of low-cost, amateur-grade environmental sensors that enhance local observation capabilities (Hintz et al., Reference Hintz, McNicholas, Randriamampianina, Williams, Macpherson, Mittermaier and Szintai2021). The final component is high-resolution modelling, becoming increasingly available and popular (Kilpeläinen et al., Reference Kilpeläinen, Vihma, Manninen, Sjöblom, Jakobson, Palo and Maturilli2012). As Earth modelling technology advances, the concept of ‘digital twins’ is emerging as a potential game-changer for informed environmental management (Bauer et al., Reference Bauer, Dueben, Hoefler, Quintino, Schulthess and Wedi2021). In the context of Earth modelling, a digital twin is essentially a representation of the Earth’s natural systems.

This study’s most important data sources are provided in the Norwegian Centre for Climate Service report “Climate in Svalbard 2100” (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019). The report is an expert synthesis of observational data and climate change projections from the regional climate perspective. The report combines current knowledge of Svalbard’s climate based on original datasets and regional downscaling of the global climate model simulations (Vikhamar-Schuler et al., Reference Vikhamar-Schuler, Lutz and Gjelten2019). It includes results from numerous climatological and environmental publications. However, it does not focus on actionable scales – the spatial scales of 0.1 km–10 km at which climate adaptation measures directly affect the physical environment. The local climate perspective can be constructed for Longyearbyen because this area is densely covered with climate and environmental observations. Many of these datasets can be retrieved from SIOS, an international observing system for long-term measurements in and around Svalbard (https://sios-svalbard.org/, last accessed 10.07.2024). Archived historical meteorological datasets are accessible on MET Norway’s websites, frost.met.no and seklima.met.no. Nordli et al. (Reference Nordli, Wyszyński, Gjelten, Isaksen, Łupikasza, Niedźwiedź and Przybylak2020) published the central climatic-quality instrumental temperature records. In addition, two atmospheric reanalysis datasets are available: The Sval-Imp dataset with 1 km × 1 km spatial resolution, which is derived from downscaling the ERA40 and ERA-Interim reanalyses, and the COSMO climate model simulations with 2.5 km × 2.5 km spatial resolution which are driven with ERA-Interim reanalysis data.

Insights into Longyearbyen’s local climate dynamics: physical mechanisms and climate localisation

Certain regions are experiencing more pronounced effects of climate change due to specific primary physical mechanisms. Climate change localisation is notably linked to the absence of atmospheric mixing, which maintains the spatial patchiness of surface physical and geomorphological properties in the atmosphere immediately above the surface. For example, adjacent land patches of snow and bare soil can maintain climatically significant temperature differences of several degrees (Johansen & Tømmervik, Reference Johansen and Tømmervik2014). Significant climatic differences exist between open water, sea ice, land, and glacier surface adjacent to each other. Figure 2 shows the local climate perspective in Longyearbyen and highlights the different elements, such as the vegetation index and land surface temperature. At low latitudes and more open terrain, spatial climatic differences are suppressed by intensive air convection or turbulence. The surface energy balance fails to sustain intensive turbulent mixing at high latitudes. This deficiency in mixing entraps local climatic differences near their points of origin, thereby gradually accumulating the impact of these differences on other components of the environment. The Normalised Difference Vegetation Index (NDVI) reveals how sensitive vegetation productivity is to the local climate variations (Fig. 2, domains A, B, and C). The active soil layer and permafrost accumulate the local temperature changes over decades, making knowledge of those differences necessary to predict changes. The complex terrain around Longyearbyen further contributes to climate localisation. Mountains trap air pockets within valleys and channel airflow in an intricate way that only fine-scale simulations could reveal (Kilpeläinen et al., Reference Kilpeläinen, Vihma, Manninen, Sjöblom, Jakobson, Palo and Maturilli2012; Mayer et al., Reference Mayer, Jonassen, Sandvik and Reuder2012; Hancock et al., Reference Hancock, Prokop, Eckerstorfer and Hendrikx2018).

Figure 2. Elements (vegetation index and land surface temperature) of the local climate perspective in Longyearbyen. Land Surface Temperature (LST) and Normalised Vegetation Difference Index (NDVI) are retrieved from satellite observations. The domains (A) and (B) are taken from (Bartsch et al., Reference Bartsch, Pointner, Nitze, Efimova, Jakober, Ley and Schweitzer2021) and present the Sentinel-1 and −2 NDVI trend data. The domains (C) and (D) are own analysis and present the Landsat-8 images: LST – from the bands 10 and 11 (100 m spatial resolution); NDVI – from the bands 4 and 5 (30 m spatial resolution). The base layer shows urban infrastructure from OpenStreetMap data (https://download.geofabrik.de/).

Both static and dynamic physical factors play a significant role in contributing to the local climate. The static factors, which collectively refer to physical processes and feedback attributed to the heterogeneity of the surface types (Goosse et al., Reference Goosse, Kay, Armour, Bodas-Salcedo, Chepfer, Docquier and Vancoppenolle2018), are crucial. They relate to the diversity of radiative properties and heat capacity of the surfaces. However, these static factors cannot realise their potential without constraints from the dynamic factors. The most crucial dynamic factor is the restrictions on vertical and horizontal atmospheric mixing (Stuecker et al., Reference Stuecker, Bitz, Armour, Proistosescu, Kang, Xie and Jin2018). These dynamical restrictions result in decorrelation (decoupling) between the local (boundary layer) and the regional (free atmosphere) climate processes. The atmospheric boundary layer decoupling is frequently observed in Longyearbyen (Mayer et al., Reference Mayer, Jonassen, Sandvik and Reuder2012). Decoupling contributes to developing a set of local weather phenomena, such as winds, clouds, and turbulent air mixing. They are difficult to capture through meteorological modelling but influential enough for climate change adaptation solutions, e.g. for wind energy potential assessment (Henkies et al., Reference Henkies, Høyland, Shestov, Duscha and Sjöblom2023). Figure 2 illustrates this high degree of climate localisation. The regional climate was determined by the temperature contrast between Isfjorden, glaciers, and narrow valleys. Solar radiation absorbed by slopes is trapped near the surface as the atmospheric mixing weakens and cannot redistribute the heat. It allows temperature anomalies to be more persistent and significant than observed over more open landscapes.

Insights into Longyearbyen’s local climate dynamics: factors, trends, and implications

Drivers and trends in Longyearbyen’s climate dynamics

Two pivotal factors – the extent of open waters in Isfjorden and the persistence of cyclonic atmospheric circulation patterns – shape the local climate in Longyearbyen (Frank et al., Reference Frank, Jonassen, Skogseth and Vihma2023). While interconnected, these factors exhibit distinct links to the atmosphere and the ocean, engaging in the most intensive interactions across vastly different time scales. (Gulev, Latif, Keenlyside, Park, & Koltermann, Reference Gulev, Latif, Keenlyside, Park and Koltermann2013; Outten, Esau, & Otterå, Reference Outten, Esau and Otterå2018). The warm water penetration in the fjord is insensitive to seasonal atmospheric variability, whereas, by contrast, the local air temperature is sensitive to the presence of the open water surface (Nilsen et al., Reference Nilsen, Cottier, Skogseth and Mattsson2008; Skogseth et al., Reference Skogseth, Olivier, Nilsen, Falck, Fraser, Tverberg and Falk-Petersen2020). Cold winters occur when the penetration is limited and sea ice advances in the fjord; each 10% increase in the sea ice cover causes the mean winter temperature to drop by 0.4°C (Isaksen et al., Reference Isaksen, Nordli, Førland, Łupikasza, Eastwood and Niedźwiedź2016).

The local climate in Longyearbyen is experiencing a warming trend at a faster rate than the Arctic’s on average, with the only place with even more extreme warming being within the marginal ice zone to the north and east of Svalbard (Isaksen et al., Reference Isaksen, Nordli, Ivanov, Køltzow, Aaboe, Gjelten and Karandasheva2022b). The surface air temperature has risen sharply since the 1990s, influenced by quasi-periodic patterns lasting between 15 and 40 years (Årthun et al., Reference Årthun, Eldevik, Viste, Drange, Furevik, Johnson and Keenlyside2017). Warming trends have been observed across all seasons throughout the entire period of observation, with statistically significant findings (Nordli, Reference Nordli2010; Nordli, Przybylak, Ogilvie, & Isaksen, Reference Nordli, Przybylak, Ogilvie and Isaksen2014; Nordli et al., Reference Nordli, Wyszyński, Gjelten, Isaksen, Łupikasza, Niedźwiedź and Przybylak2020). The winter/spring season has the most significant trend (0.43°C per decade), whereas the annual mean trend is 0.32°C per decade. Since 1991, Svalbard airport’s temperature record has shown a warming trend of 1.7°C per decade. Between 1991 and 2018, the number of days colder than −20°C has decreased by 27 (62%). Since 1997, no mean summer temperature has been below the climate average from 1960 to 1990. Between 1991 and 2018, the number of days warmer than 0°C has increased by 25 (21%). According to (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019), local warming will continue in the 21st century. Additionally, in the RCP4.5 scenario, which is now considered a “business as usual” scenario, the temperature will increase by 5.4 ± 1.2°C by 2,100 (Hausfather & Peters, Reference Hausfather and Peters2020).

Impacts of sea ice reduction and permafrost dynamics on climate and geohazards in Longyearbyen

The sea ice cover dramatically influences the local temperature increase in the surrounding area of Adventfjorden and the wider Svalbard region. Research shows that the mean annual temperature can increase by 8°C when sea ice concentration is reduced from 50% to 0% in the Svalbard region (Isaksen et al., Reference Isaksen, Nordli, Ivanov, Køltzow, Aaboe, Gjelten and Karandasheva2022b). Locally, the mean winter temperature difference between the Svalbard Airport and Janssonhaugen stations increases by 5°C when fast sea ice disappears from Adventfjorden (Dahlke et al., Reference Dahlke, Hughes, Wagner, Gerland, Wawrzyniak, Ivanov and Maturilli2020). It is worth noting that fast ice is a type of stationary sea ice that is anchored to the coastline and forms in shallow coastal areas. Unlike drifting sea ice that moves along with the water, fast ice significantly impacts the local climate as it reduces the air-sea heat and moisture exchange by 10× or more. Therefore, the disappearance of fast ice can drastically change the climatic conditions along the coast. Between 1974 and 2008, fast ice was present yearly at Barentsburg, closer to the fjord mouth (Zhuravskiy, Ivanov, & Pavlov, Reference Zhuravskiy, Ivanov and Pavlov2012). However, since 2006, there has been a significant decrease in fast ice periods (from November to May) due to late freezing (Dahlke et al., Reference Dahlke, Hughes, Wagner, Gerland, Wawrzyniak, Ivanov and Maturilli2020; Skogseth et al., Reference Skogseth, Olivier, Nilsen, Falck, Fraser, Tverberg and Falk-Petersen2020). Although the transition to ice-free winters in Isfjorden improves marine logistics, it also makes the coastal area more vulnerable for erosion, landslides, and permafrost thaw (Jaskólski et al., Reference Jaskólski, Pawłowski and Strzelecki2018; Bartsch et al., Reference Bartsch, Pointner, Nitze, Efimova, Jakober, Ley and Schweitzer2021).

In the past 50 years, there has been an increase of 30–45% in annual precipitation, likely due to Arctic warming and increased moisture transport (Pithan et al., Reference Pithan, Svensson, Caballero, Chechin, Cronin, Ekman, Neggers and Wendisch2018; Gimeno, Vazquez, Eiras-Barca, Sori, Algarra, & Nieto, Reference Gimeno, Vázquez, Eiras-Barca, Sorí, Algarra and Nieto2019; Rinke et al., Reference Rinke, Segger, Crewell, Maturilli, Naakka, Nygård and Keller2019; Førland et al., Reference Førland, Isaksen, Lutz, Hanssen-Bauer, Schuler, Dobler and Vikhamar-Schuler2020). The reduction in sea ice is also a significant factor affecting local air temperature and precipitation variability, with the amount of precipitation often corresponding with the level of sea ice retreat (Wickström et al., Reference Wickström, Jonassen, Cassano and Vihma2020). Rising temperatures and precipitation increase the risks of landslides and snow avalanches (Hestnes et al., Reference Hestnes, Bakkehøi and Jaedicke2016; Hancock et al., Reference Hancock, Prokop, Eckerstorfer and Hendrikx2018). Climate simulations predict that precipitation will continue to increase by at least 28% or more (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019). Snow avalanches and land sliding are the most significant geohazards in Longyearbyen (Hestnes et al., Reference Hestnes, Bakkehøi and Jaedicke2016). The Norwegian Water and Energy Directorate (NVE) has created a hazard zonation map for area planning (Fig. 3), which shows that the most populated eastern slopes are in the high-risk zone for snow avalanches. Figure 2 (panel C) shows that this area also experiences the most significant land warming. Snowdrift across the extensive barren plateaus builds significant cornices on eastern slopes. These cornices eventually break down as cornice fall avalanches (45.2% of all avalanches). Slab avalanches are also frequent (32.6%) and account for the most significant observed avalanches, with more than 80% of the total snow mass (Eckerstorfer & Christiansen, Reference Eckerstorfer and Christiansen2011). Although the hazard warning system has been significantly improved (Engeset, Landrø, Indreiten, Müller, Mikkelsen & Hoseth, Reference Engeset, Landrø, Indreiten, Müller, Mikkelsen and Hoseth2020), a perspective hazard assessment that uses climate change projections has not yet been realised. Predicting snow avalanches requires mapping local snow cover differences in thickness (snow accumulation and drift) and density.

Figure 3. Hazard zonation map for Longyearbyen available from NVE (https://temakart.nve.no/link/?link=faresoner&layer=5&field=KOMMNAVN&value=Spitsbergen&buffer=100), see also methods in (Engeset et al., Reference Engeset, Landrø, Indreiten, Müller, Mikkelsen and Hoseth2020); inserts show two major snow slab avalanches in the town on December 19, 2015 and February 21, 2017. Both avalanches occur after severe snowstorms with easterly winds. Pictures are from the NVE report (Landrø et al., Reference Landrø, Mikkelsen and Jaedicke2017); the avalanche location assessment is after (Eckerstorfer & Christiansen, Reference Eckerstorfer and Christiansen2011).

The active soil layer and permafrost are the most localised and inertial elements in the local climate perspective. Permafrost is continuous and usually 100 m thick in Longyearbyen (Hjort et al., Reference Hjort, Karjalainen, Aalto, Westermann, Romanovsky, Nelson and Luoto2018). Since regular temperature monitoring began in 1998, permafrost at 15 m depth has warmed by 2°C over 20 years. This rise threatens permafrost stability as its temperature (varying between −2.6°C and −5.2°C depending on the site’s landforms and snow cover) is already high and may reach the thawing point in a few decades (Winther & Gudmestad, Reference Winther and Gudmestad2023). Accumulating warming signals in inertial systems is well understood in climatology, but details are specific to each case (Instanes & Rongved, Reference Instanes and Rongved2017; Isaksen et al., Reference Isaksen, Lutz, Sørensen, Godøy, Ferrighi, Eastwood and Aaboe2022a; Smith, O’Neill, Isaksen, Noetzli, & Romanovsky, Reference Smith, O’Neill, Isaksen, Noetzli and Romanovsky2022). Data from the Ny Ålesund station (Westermann, Lüers, Langer, Piel, & Boike, Reference Westermann, Lüers, Langer, Piel and Boike2009; Westermann, Langer, & Boike, Reference Westermann, Langer and Boike2011) show that during clear-sky conditions in July, temperature disparities in wet and dry soil patches can extend up to 10°C, enabling the differentiation of frozen and thawing grounds. Weekly and monthly mean differences are minor but still reach 3–4°C. These temperature differences between frozen and thawing ground illustrate how human infrastructure, buildings, and land disturbances affect the local climate. Studies show that the accumulated degree-day totals of the snow-free period can differ by more than 60% within the town, reflecting significant microclimatic variations influenced by urbanisation and land-use changes (Westermann et al., Reference Westermann, Langer and Boike2011)

Temperature inversions and their implications on the complexity of local climate

The study in Longyearbyen found that during July and August, there was a positive turbulent sensible heat flux of +22.5 W m−2. However, for the rest of the year, the mean annual turbulent sensible heat flux was negative (−6.9 W m−2). This results in temperature inversions, where the air temperature increases with altitude because the surface is colder than the air above it. These temperature inversions occur due to the local climate’s dynamic factors, significantly the persistence of temperature inversions in the valleys (Valkonen et al., Reference Valkonen, Stoll, Batrak, Køltzow, Schneider, Stigter and Jonassen2020).

The area is unfortunately also prone to accumulating atmospheric pollutants at the surface level due to temperature inversions. In 2007, a 2-month monitoring campaign found high transitional concentrations of aromatic hydrocarbons, including benzene, toluene, and C2-benzenes (Reimann, Kallenborn, & Schmidbauer, Reference Reimann, Kallenborn and Schmidbauer2009). The levels of these pollutants were comparable to those found in European towns during local rush hour (two diurnal peaks) in April and May, which is caused by snowmobile activity. Although snowmobiles emit relatively low levels of pollutants, diesel-fuelled heavy-duty vehicles, permanently used for coal transport from the adjacent coal mines, are the primary source of emissions.

The local climate is a complex and highly varied system characterised by the different surface properties that have a static impact on it. The effects of these static factors are less pronounced in lower latitudes, where atmospheric mixing and local air flows can help to dilute them. However, in the Arctic, where atmospheric stability is high, and the surface energy balance is negative, the impact of these static factors is more significant and dynamic. The local climate perspective is further complicated by the influence of temperature differences on the stability of snow cover and frozen ground, as well as on air quality and various geohazards. These geohazards pose significant risks to human activity, such as infrastructure damage, landslides, and other environmental hazards. Therefore, understanding the local climate is crucial for designing sustainable responses to geohazard risks and human activity. Accurately predicting the local climate’s behaviour is essential for modelling the impact of human activity and making informed decisions about land use, resource management, and other critical issues.

Navigating sustainable development pathways in arctic towns while considering the local climate

Social sciences and humanities play significant roles in identifying sustainable and resilient development pathways for Arctic towns (Berman & Orttung, Reference Berman and Orttung2020; Orttung et al., Reference Orttung, Laruelle, Anisimov, Streletskiy, Shiklomanov and Cooper2017, Reference Orttung, Anisimov, Badina, Burns, Cho, DiNapoli and Zhiltcova2021; Petrov et al., Reference Petrov, BurnSilver, Chapin, Fondahl, Graybill, Keil and Schweitzer2016). For Longyearbyen and Svalbard in general, tourism, education, and research are the three socio-economic pillars to which the transition from the coal-mining industry is stipulated (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020). We organise the discussion along three (industrial, public, and tourism and conservation) pathways. This categorisation is abstract and subject to criticism, but it distinguishes impacts and feedback from the local climate effects. In our defence, we refer to three scenarios for the macro-development of Russian Arctic towns: Resource-Dependent, Self-Reliant, and Harmonious Arctic (Petrov et al., Reference Petrov, Rozanova Smith, Krivorotov, Klyuchnikova, Mikheev, Pelyasov and Zamyatina2021). The main difference between these scenarios is the amount of human intervention in the physical environment. The industrial pathway directly exploits economic opportunities such as energy resources and fisheries. On the other hand, the other two pathways involve more nuanced human interactions with the environment.

Svalbard governance requires the tourism sector to preserve a fragile environment and protect the archipelago from the impacts of global change. The development focus on tourism, research, and education is a national priority for Svalbard. It distinguishes the adaptation context in Longyearbyen from other Arctic communities, as Hovelsrud et al. (Reference Hovelsrud, Kaltenborn and Olsen2020) state. The Norwegian policy “supports extensive tourism while also stipulating strict protection of the environment that attracts tourists” (Hovelsrud et al., Reference Hovelsrud, Olsen, Nilsson, Kaltenborn and Lebel2023). The problem is that geomorphological and climatic conditions in the Arctic, generally and in Longyearbyen specifically, do not allow for highly concentrated human activity. Such activity inevitably destroys the place’s environment – its frozen state and cold climate. This is because the sum of the favourable climate feedback, which amplify climate warming, outweighs the negative feedback (Goosse et al., Reference Goosse, Kay, Armour, Bodas-Salcedo, Chepfer, Docquier and Vancoppenolle2018). Indeed, any aerosol and black carbon (soot) sedimentation on pristine snow decreases its reflectivity (albedo) and accelerates melting; a darker surface absorbs more solar heat, which, with time, warms the ground and the lower atmosphere. Tourism is a component of industrial development, necessitating corresponding investments in public services and infrastructure. At the same time, the localisation of strong climate change in the Arctic could help protect its environment. The climatic impact of human activity is significant in the town but could also be limited to the town. The challenge lies in limiting the sprawl of activities to undisturbed areas, thus achieving a harmonious integration of these pathways to promote sustainable development in Svalbard. Figure 4 and Table 1 summarise the local climate factors and their impact.

Figure 4. Graphical presentation of the study connecting three development pathways to influential climate factors. The Svalbard cartoon map from (https://www.subpng.com; by Vskuagtekt) is free for non-commercial use. Photos are taken by the authors. The cruise ship is “M/S Roald Amundsen.”

Table 1. Consequences of climate change in Longyearbyen – a summary inspired by Table 2 in Hovelsrud et al. (Reference Hovelsrud, Kaltenborn and Olsen2020); updated and corrected to account for the local climate perspective

The tourism and conservation pathway seeks to benefit from increasing interest in the Arctic environment (Aldao & Mihalic, Reference Aldao and Mihalic2020; Kugiejko, Reference Kugiejko2021). This is the most complex and controversial pathway as it involves balancing the value of pristine Arctic nature with the threat of climate change. A dominant perception of Svalbard is that it is Europe’s last wilderness. The most valued environmental components are untouched nature, landscape, and cultural heritage left by the Arctic pioneers (Holmgaard, Thuestad, Myrvoll, & Barlindhaug, Reference Holmgaard, Thuestad, Myrvoll and Barlindhaug2019). The increasing pressure of visitors on the natural environment along popular routes poses a challenge in protecting the nature tourists want to experience. Svalbard’s policies aim to balance development with the conservation of nature. However, increased tourist activities make it vulnerable to local climate extremes. (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020). Tourist operators must be flexible and adapt to the ever-changing demands of their customers. To achieve this, they extend the cruise season, change routes, and develop new tourism products (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020: Dannevig et al., Reference Dannevig, Søreide, Sveinsdóttir, Olsen, Hovelsrud, Rusdal and Dale2023). However, it is essential to have organised activity to ensure safety. The scale of this challenge has been demonstrated through the analysis of snow avalanches along snowmobile routes (Eckerstorfer & Christiansen, Reference Eckerstorfer and Christiansen2011; Hancock et al., Reference Hancock, Prokop, Eckerstorfer and Hendrikx2018). The local climate perspective is indispensable in identifying and quantifying related vulnerabilities. Immediate and local impacts, such as snowmobile tracks, should be considered from a climate perspective, such as accelerated permafrost degradation, as observed elsewhere (Gibson, Brinkman, Cold, Brown, & Turetsky, Reference Gibson, Brinkman, Cold, Brown and Turetsky2021). Improvements in specific climatic comfort indices could benefit Arctic tourism (Huang et al., Reference Huang, Zhang, Zhang, Zhang, Zhang, Ren and Chen2021).

The industrial pathway must diversify and provide various economic services while sensitive to the local physical, environmental, and climate conditions. According to climate projections (Hanssen-Bauer et al., Reference Hanssen-Bauer, Førland, Hisdal, Mayer, Sandø and Sorteberg2019), the Arctic warming scenario is expected to bring some benefits. These include the continued retreat of sea ice, which could make fisheries more economically viable. Longyearbyen is expected to become an increasingly crucial Arctic logistic and industry hub (Stocker et al., Reference Stocker, Renner and Knol-Kauffman2020). A recent study states that having a modern port in Longyearbyen is crucial (Nyman, Galvao, Mileski, & Tiller, Reference Nyman, Galvao, Mileski and Tiller2020). Statistics for the Port of Longyearbyen (SPL, 2020) indicate that in 2019, the port was visited by 446 cruise and tourist ships, 78 cargo ships, and 16 fishing vessels.

The economic adaptation should prioritise self-sufficiency, cost reduction, and flagship projects for territorial status maintenance (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020). A nexus sustainable renewable energy system is a feasible option in this direction. Ringkjøb et al. (Reference Ringkjøb, Haugan and Nybø2020) demonstrated the theoretical feasibility and economic viability of such a system. Solar radiation and wind energy resources enormously vary on local spatial scales and seasons (Solbakken, Babar, & Bostrøm, Reference Solbakken, Babar and Boström2016). The local climate is essential for the system’s implementation as it would provide information for balancing capacity. This system’s observed increasing winter storminess could enhance energy generation, particularly in winter. In the 2022 state budget, a new energy plan for Longyearbyen urges the transition to renewable energy sources to overcome as the primary energy supply (Ødegaard, Reference Ødegaard2022). The coast between the new port and the river delta – the most scenic part of the town – is particularly vulnerable and requires monitoring and protection. Further to the east, increased sediment supply to the tidal flat system in the Advent Valley may create difficulties for large ship operations near the town. The total assessment and accounting for coastal vulnerability and changing climate risks is still required. As the “Svalbard Project” and its instrument “Store Norske” are tied to exercising sovereignty through administration, research, education, and minor economic activities, the cost-effective maintenance of the infrastructure under climate change challenges set to be necessary for the community existence in the future (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020; Ødegaard, Reference Ødegaard2022).

The public pathway emphasises the development of administration, research, and educational hubs. It is not capitalising on the benefits of the Arctic warming but is also not very vulnerable to its detrimental effects. Along this pathway, administrative functions and research activity are to be strengthened in the town (Misund, Reference Misund2017). Furthermore, the region´s increasing militarisation influences civilian interests (Pedersen, Reference Pedersen2019). The local climate perspective is needed to make adequate adjustments at minimal cost. It might look at approaches to integrate the Arctic town with its harsh but vulnerable Arctic climate; such an integration concept has become known as a “winter city” (Pressman, Reference Pressman1996). Weak place connections have complicated the integration due to short residence times; on average, dwellers stay for less than four years (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020).

The critical challenges from the local climate perspective are snow avalanches and permafrost thaw in the eastern Longyearbyen areas. The local authorities have developed building codes and contingency plans, moved houses, and implemented zoning restrictions (see Fig. 3). The waterfront is a highly valued area with enhanced public attention to infrastructure development. In Longyearbyen, the coastal zone is also highly valued but underdeveloped. New buildings and walking routes are planned in this zone. At the same time, a coastal zone is where environmental changes impact the town’s infrastructure the most. Significant ice content in frozen soils leads to local surface depressions, coastal erosion, and sliding (Jaskólski et al., Reference Jaskólski, Pawłowski and Strzelecki2018).

Conclusions

A local climate perspective refers to a viewpoint that focuses on understanding the specific climate conditions and patterns within a particular geographical area. In the Longyearbyen context, this perspective considers the unique features and characteristics of the local cold climate, including temperature variations, inversions, snow and permafrost features, sea ice patterns, and other environmental factors. Notably, a local climate perspective often considers the interactions between these features and their impact on the social, economic, and ecological aspects of the specific region or community under study. Longyearbyen is a place where the combination of local climate factors has a compound effect; temperature change, sea ice retreat, soil wetting, and permafrost thaw reinforce each other, sustaining local climate anomalies larger than anomalies found in the region. Our synthesis can be summarised by presenting the ranking of climate factors for each pathway, considering industrial, public, tourism, and conservation aspects (Fig. 4). The industrial pathway is sensitive to the dynamic climate factors that act on regional and local scales. The extent of the sea ice is the most critical factor here, as it determines the port´s accessibility. At seasonal time scales, the sea ice edge is controlled by the balance between Atlantic Waters penetration into Isfjorden and local circulation patterns. At longer, interannual time scales, it is factored by the hemispheric Arctic amplification processes and local physical feedback (Goosse et al., Reference Goosse, Kay, Armour, Bodas-Salcedo, Chepfer, Docquier and Vancoppenolle2018; Previdi, Smith, & Polvani, Reference Previdi, Smith and Polvani2021). Permafrost and snowpack stability, temperature, and precipitation changes are of lesser importance, as they could be tamed through technological solutions. However, more than traditional techno-fix solutions may be required if the local climate anomalies exceed certain thresholds, such as permafrost collapse (Winther & Gudmestad, Reference Winther and Gudmestad2023). Various measures to protect the infrastructure from damage include new buildings on steel pillars anchored in the underlying bedrock, avalanche barriers, and thermosyphons to stabilise permafrost. Permafrost is also protected by lifting facilities above the ground, reducing thermal radiation from the surface under buildings.

The public pathway is sensitive to geotechnical (infrastructural) safety factors in the settlement (Hjort et al., Reference Hjort, Karjalainen, Aalto, Westermann, Romanovsky, Nelson and Luoto2018). The immediate risks are related to permafrost and snowpack stability, which are factored in by local changes in temperature and precipitation. There is increasing awareness of this locality, manifested by setting geo-test sites and considering downscaling climate change projections (Instanes, Reference Instanes2016).

Is more sustainable acclimation of the town feasible? Hovelsrud et al. (Reference Hovelsrud, Kaltenborn and Olsen2020) emphasise emerging adaptation dilemmas for Longyearbyen: climate change creates hazardous conditions with urgent safety planning measures, but “the strict environmental protection limits the action space.” Although physical climatology still undervalues the local climate perspective, it becomes clear that specific physical mechanisms in the Arctic can sustain large and significant local variations in the climate factors (Table 1). The Environmental Policy Act places environmental concerns above economic interests, and the Svalbard Act stipulates that the natural environment remains undeveloped (Hovelsrud et al., Reference Hovelsrud, Kaltenborn and Olsen2020). These stipulated policy restrictions call for a more spatially detailed climate assessment that might identify less vulnerable geographical areas for prospective development. We conclude that the local climate perspective has a considerable environmental impact and is indispensable for sustainable development at the local level. Hovelsrud et al. (Reference Hovelsrud, Kaltenborn and Olsen2020) noted: “Proactive adaptation includes adjustments in behavior and acceptance of increasingly adverse weather conditions.”

Financial support

This work is prepared with the support of the Norwegian Research Council project “URban Sustainability in Action: Multi-disciplinary Approach through Jointly Organized Research schools” (project number 322317) and the Belmont Forum project “Biocultural Heritage in Arctic Cities: Resource for Climate Adaptation? (ARCA).”

Competing interests

The authors declare none.

References

Aftret, H. M., & Daleng, V. M. (2022). Suitability of Thermosyphon as a ground freezing technology in Longyearbyen [NTNU]. https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/3019954/no.ntnu:inspera:114862279:37517736.pdf?sequence=1 (accessed 30 August 2024).Google Scholar
Aldao, C., & Mihalic, T. A. (2020). New frontiers in travel motivation and social media: The case of Longyearbyen, the High Arctic. Sustainability, 12(15), 119. doi: 10.3390/SU12155905 CrossRefGoogle Scholar
Årthun, M., Eldevik, T., Viste, E., Drange, H., Furevik, T., Johnson, H. L., & Keenlyside, N. S. (2017). Skillful prediction of northern climate provided by the ocean. Nature Communications, 8, 19. doi: 10.1038/ncomms15875 Google ScholarPubMed
Bartsch, A., Pointner, G., Nitze, I., Efimova, A., Jakober, D., Ley, S., … Schweitzer, P. (2021). Expanding infrastructure and growing anthropogenic impacts along Arctic coasts. Environmental Research Letters, 16(11), 115013. doi: 10.1088/1748-9326/ac3176 CrossRefGoogle Scholar
Bauer, P., Dueben, P. D., Hoefler, T., Quintino, T., Schulthess, T. C., & Wedi, N. P. (2021). The digital revolution of Earth-System science. Nature Computational Science 1, 104113. doi: 10.1038/s43588-021-00023-0 Google ScholarPubMed
Bekele, Y., & Sinitsyn, A. (2017). Impact of changing climate on infrastructure in Longyearbyen: stability of foundations on slope terrain – Case study. (Popular science report), https://www.miljovernfondet.no/wp-content/uploads/2020/01/16-87-popular-science-presentation-of-the-fst-project.pdf (accessed 26 September 2024).Google Scholar
Berman, M., & Orttung, R. W. (2020). Measuring progress toward Urban sustainability: Do global measures work for Arctic cities? Sustainability, 12(9), 3708. doi: 10.3390/su12093708 Google Scholar
Box, J. E., Colgan, W. T., Christensen, T. R., Schmidt, N. M., Lund, M., Parmentier, F. J. W., … Olsen, M. S. (2019). Key indicators of Arctic climate change: 1971–2017. Environmental Research Letters, 14(4), 45010. doi: 10.1088/1748-9326/aafc1b CrossRefGoogle Scholar
Bystrowska, M. (2019). The impact of sea ice on cruise tourism on Svalbard. Arctic, 72(2), 151165. doi: 10.14430/arctic68320 CrossRefGoogle Scholar
Colloff, M. J., Wise, R. M., Palomo, I., Lavorel, S., & Pascual, U. (2020). Nature’s contribution to adaptation: Insights from examples of the transformation of social-ecological systems. Ecosystems and People, 16(1), 137150. doi: 10.1080/26395916.2020.1754919 CrossRefGoogle Scholar
Dahlke, S., Hughes, N. E., Wagner, P. M., Gerland, S., Wawrzyniak, T., Ivanov, B., & Maturilli, M. (2020). The observed recent surface air temperature development across Svalbard and concurring footprints in local sea ice cover. International Journal of Climatology, 40(12), 52465265. doi: 10.1002/joc.6517 CrossRefGoogle Scholar
Dannevig, H., Søreide, J.E., Sveinsdóttir, A.G., Olsen, J., Hovelsrud, G.K., Rusdal, T., & Dale, R. F. (2023). Coping with rapid and cascading changes in Svalbard: The case of nature-based tourism in Svalbard. Frontiers in Human Dynamics 5. doi: 10.3389/fhumd.2023.1178264 CrossRefGoogle Scholar
Dobricic, S., Russo, S., Pozzoli, L., Wilson, J., & Vignati, E. (2020). Increasing occurrence of heat waves in the terrestrial Arctic. Environmental Research Letters, 15(2), 024022. doi: 10.1088/1748-9326/ab6398 CrossRefGoogle Scholar
Duncan, B. N., Ott, L. E., Abshire, J. B., Brucker, L., Carroll, M. L., Carton, J., … Wu, D. L. (2020). Space-based observations for understanding changes in the Arctic-Boreal zone. Reviews of Geophysics, 58(1), 195. doi: 10.1029/2019RG000652 CrossRefGoogle Scholar
Eckerstorfer, M., & Christiansen, H. H. (2011). Topographical and meteorological control on snow avalanching in the Longyearbyen area, central Svalbard 2006–2009. Geomorphology, 134(3–4), 186196. doi: 10.1016/j.geomorph.2011.07.001 CrossRefGoogle Scholar
Engeset, R. V., Landrø, M., Indreiten, M., Müller, K., Mikkelsen, O., & Hoseth, K. (2020). Avalanche Warning in Svalbard. Norwegian Water Resources and Energy Directorate, NVE Rapport Nr 35/2020. doi: 10.25607/OBP-933 CrossRefGoogle Scholar
Esau, I., Argentini, S., Przybylak, R., Repina, I., & Sjöblom, A. (2012). Svalbard meteorology. Advances in Meteorology, 2012. doi: 10.1155/2012/818473 CrossRefGoogle Scholar
Esau, I., Pettersson, L. H., Cancet, M., Chapron, B., Chernokulsky, A., Donlon, C., … Johannesen, J. A. (2023). The Arctic amplification and its impact: A synthesis through satellite observations. Remote Sensing, 15(5), 1354. doi: 10.3390/rs15051354 CrossRefGoogle Scholar
Fedorov, R. (2019). Cryogenic resources: Ice, snow, and permafrost in traditional subsistence systems in Russia. Resources, 8(1), 110. doi: 10.3390/resources8010017 CrossRefGoogle Scholar
Feldl, N., Bordoni, S., & Merlis, T. M. (2017). Coupled high-latitude climate feedbacks and their impact on atmospheric heat transport. Journal of Climate, 30(1), 189201. doi: 10.1175/JCLI-D-16-0324.1 CrossRefGoogle Scholar
Ford, J. D., McDowell, G., & Pearce, T. (2015). The adaptation challenge in the Arctic. Nature Climate Change, 5(12), 10461053. doi: 10.1038/nclimate2723 CrossRefGoogle Scholar
Førland, E. J., Isaksen, K., Lutz, J., Hanssen-Bauer, I., Schuler, T. V., Dobler, A., … Vikhamar-Schuler, D. (2020). Measured and modeled historical precipitation trends for Svalbard. Journal of Hydrometeorology, 21(6), 12791296. doi: 10.1175/JHM-D-19-0252.1 CrossRefGoogle Scholar
Frank, L., Jonassen, M. O., Skogseth, R., & Vihma, T. (2023). Atmospheric climatologies over Isfjorden, Svalbard. Journal of Geophysical Research: Atmospheres, 128(22), 117. doi: 10.1029/2022JD038011 Google Scholar
Gibson, C. M., Brinkman, T., Cold, H., Brown, D., & Turetsky, M. (2021). Identifying increasing risks of hazards for northern land-users caused by permafrost thaw: Integrating scientific and community-based research approaches. Environmental Research Letters, 16(6), 064047. doi: 10.1088/1748-9326/abfc79 Google Scholar
Gimeno, L., Vázquez, M., Eiras-Barca, J., Sorí, R., Algarra, I., & Nieto, R. (2019). Atmospheric moisture transport and the decline in Arctic sea ice. WIREs Climate Change, 10(4). doi: 10.1002/wcc.588 CrossRefGoogle Scholar
Gjelten, H. M., Nordli, Ø., Isaksen, K., Førland, E. J., Sviashchennikov, P. N., Wyszynski, P., … Urazgildeeva, A. V. (2016). Air temperature variations and gradients along the coast and fjords of western Spitsbergen. Polar Research, 35. doi: 10.3402/polar.v35.29878 CrossRefGoogle Scholar
Goosse, H., Kay, J. E., Armour, K. C., Bodas-Salcedo, A., Chepfer, H., Docquier, D., … Vancoppenolle, M. (2018). Quantifying climate feedbacks in polar regions. Nature Communications, 9(1), 1919. doi: 10.1038/s41467-018-04173-0 CrossRefGoogle ScholarPubMed
Gulev, S. K., Latif, M., Keenlyside, N., Park, W., & Koltermann, K. P. (2013). North Atlantic ocean control on surface heat flux on multidecadal timescales. Nature, 499(7459), 464467. doi: 10.1038/nature12268 CrossRefGoogle ScholarPubMed
Hancock, H., Prokop, A., Eckerstorfer, M., & Hendrikx, J. (2018). Combining high spatial resolution snow mapping and meteorological analyses to improve forecasting of destructive avalanches in Longyearbyen, Svalbard. Cold Regions Science and Technology, 154, 120132. doi: 10.1016/j.coldregions.2018.05.011 CrossRefGoogle Scholar
Hanssen-Bauer, I., Førland, E. J., Hisdal, H., Mayer, S., Sandø, A. B., & Sorteberg, A. (Eds.) (2019). Climate in Svalbard 2100 – A Knowledge Base for Climate Adaptation. Norway: Norwegian Centre of Climate Services for Norwegian Environment Agency, 208 pp. NCCS report 1/2019. doi: 10.25607/OBP-888 Google Scholar
Hausfather, Z., & Peters, G. P. (2020). Emissions – the ‘business as usual’ story is misleading. Nature, 577(7792), 618620. doi: 10.1038/d41586-020-00177-3 CrossRefGoogle ScholarPubMed
Henkies, M., Høyland, K. V., Shestov, A., Duscha, C., & Sjöblom, A. (2023). The Arctic Fjord Breeze: Characteristics of a combined sea breeze and valley wind in a Svalbard Fjord valley. Boundary-Layer Meteorology, 189(1–3), 281304. doi: 10.1007/s10546-023-00840-y CrossRefGoogle Scholar
Hestnes, E., Bakkehøi, S., & Jaedicke, C. (2016). Longyearbyen, Svalbard – vulnerability and risk management of an arctic settlement under changing climate – a challenge to authorities and experts. Proceedings, International Snow Science Workshop, Breckenridge, CO: Montana State University Library. 363370. https://arc.lib.montana.edu/snow-science/item/2293 Google Scholar
Hintz, K. S., McNicholas, C., Randriamampianina, R., Williams, H. T. P., Macpherson, B., Mittermaier, M., … Szintai, B. (2021). Crowd-sourced observations for short-range numerical weather prediction: Report from EWGLAM/SRNWP meeting 2019. Atmospheric Science Letters, 22(6). doi: 10.1002/asl.1031 CrossRefGoogle Scholar
Hjort, J., Karjalainen, O., Aalto, J., Westermann, S., Romanovsky, V. E., Nelson, F. E., … Luoto, M. (2018). Degrading permafrost puts Arctic infrastructure at risk by mid-century. Nature Communications, 9(1). doi: 10.1038/s41467-018-07557-4 CrossRefGoogle ScholarPubMed
Holmgaard, S. B., Thuestad, A. E., Myrvoll, E. R., & Barlindhaug, S. (2019). Monitoring and managing human stressors to coastal cultural heritage in Svalbard. Humanities, 8(1), 21. doi: 10.3390/h8010021 CrossRefGoogle Scholar
Hovelsrud, G. K., Kaltenborn, B. P., & Olsen, J. (2020). Svalbard in transition: adaptation to cross-scale changes in Longyearbyen. Polar Journal, 10(2), 420442. doi: 10.1080/2154896X.2020.1819016 CrossRefGoogle Scholar
Hovelsrud, G. K., Olsen, J., Nilsson, A. E., Kaltenborn, B., & Lebel, J. (2023). Managing Svalbard tourism: Inconsistencies and conflicts of interest. Arctic Review on Law and Politics, 14, 86106. doi: 10.23865/arctic.v14.5113 CrossRefGoogle Scholar
Huang, Y., Zhang, X., Zhang, D., Zhang, L., Zhang, W., Ren, C., … Chen, Y. (2021). Spatial-temporal characteristics of arctic summer climate comfort level in the context of regional tourism resources from 1979 to 2019. Sustainability, 13(23). doi: 10.3390/su132313056 CrossRefGoogle Scholar
Instanes, A. (2016). Incorporating climate warming scenarios in coastal permafrost engineering design – Case studies from Svalbard and northwest Russia. Cold Regions Science and Technology, 131, 7687. doi: 10.1016/j.coldregions.2016.09.004 CrossRefGoogle Scholar
Instanes, A., & Rongved, J. L. (2017). Forventede klimaendringers påvirkning på byggegrunn i Longyearbyen-området. Delrapport 2 “Bygging og forvaltning på Svalbard i et langsiktig Klimaperspektiv”. 36. https://dok.statsbygg.no/wp-content/uploads/2020/10/samlerapportByggingForvaltningSvalbard.pdf (accessed 26 September 2024).Google Scholar
Isaksen, K., Lutz, J., Sørensen, A. M., Godøy, Ø., Ferrighi, L., Eastwood, S., & Aaboe, S. (2022a). Advances in operational permafrost monitoring on Svalbard and in Norway. Environmental Research Letters, 17(9). doi: 10.1088/1748-9326/ac8e1c Google Scholar
Isaksen, K., Nordli, Ø., Førland, E. J., Łupikasza, E., Eastwood, S., & Niedźwiedź, T. (2016). Recent warming on Spitsbergen—Influence of atmospheric circulation and sea ice cover. Journal of Geophysical Research: Atmospheres, 121(20). doi: 10.1002/2016JD025606 Google Scholar
Isaksen, K., Nordli, Ø., Ivanov, B., Køltzow, M. A. Ø., Aaboe, S., Gjelten, H. M., … Karandasheva, T. (2022b). Exceptional warming over the Barents area. Scientific Reports, 12(1), 9371. doi: 10.1038/s41598-022-13568-5 CrossRefGoogle ScholarPubMed
Jaskólski, M. W., Pawłowski, Ł., & Strzelecki, M. C. (2018). High Arctic coasts at risk-the case study of coastal zone development and degradation associated with climate changes and multidirectional human impacts in Longyearbyen (Adventfjorden, Svalbard). Land Degradation & Development, 29(8), 25142524. doi: 10.1002/ldr.2974 CrossRefGoogle Scholar
Jawak, S. D., Pohjola, V., Kääb, A., Andersen, B. N., Błaszczyk, M., Salzano, R., … Fjæraa, A. M. (2023). Status of earth observation and remote sensing applications in Svalbard. Remote Sensing, 15(2), 513. doi: 10.3390/rs15020513 Google Scholar
Johansen, B., & Tømmervik, H. (2014). The relationship between phytomass, NDVI and vegetation communities on Svalbard. International Journal of Applied Earth Observation and Geoinformation, 27(PARTA), 2030. doi: 10.1016/j.jag.2013.07.001 CrossRefGoogle Scholar
Jonassen, T. (2020). Hope for Svalbard mine: “A Great Job Has Been Done!” High North News. https://www.highnorthnews.com/en/hope-svalbard-mine-great-job-has-been-done. (accessed 26 September 2024).Google Scholar
Kilpeläinen, T., Vihma, T., Manninen, M., Sjöblom, A., Jakobson, E., Palo, T., & Maturilli, M. (2012). Modelling the vertical structure of the atmospheric boundary layer over Arctic fjords in Svalbard. Quarterly Journal of the Royal Meteorological Society, 138(668), 18671883. doi: 10.1002/qj.1914 Google Scholar
Kotov, P. I., & Khilimonyuk, V. Z. (2021). Building stability on permafrost in Vorkuta, Russia. Geography, Environment, Sustainability, 14(4), 6774. doi: 10.24057/2071-9388-2021-043 CrossRefGoogle Scholar
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259263. doi: 10.1127/0941-2948/2006/0130 CrossRefGoogle Scholar
Kugiejko, M. (2021). Increase of tourist traffic on Spitsbergen: An environmental challenge or chance for progress in the region? Polish Polar Research, 128. doi: 10.24425/ppr.2021.136601 Google Scholar
Landrø, M., Mikkelsen, O.-A., & Jaedicke, C. (2017). Gjennomgang og evaluering av skredhendelsen i Longyearbyen 21.02.2017. Norges Vassdrag og Energidirektorat, Oslo, Rapport nr 31-2017. https://publikasjoner.nve.no/rapport/2017/rapport2017_31.pdf (accessed 26 September 2024).Google Scholar
Liu, Y., Key, J. R., Wang, X., & Tschudi, M. (2020). Multidecadal Arctic sea ice thickness and volume derived from ice age. The Cryosphere, 14(4), 13251345. doi: 10.5194/tc-14-1325-2020 CrossRefGoogle Scholar
Łupikasza, E. B., Niedźwiedź, T., Przybylak, R., & Nordli, Ø. (2021). Importance of regional indices of atmospheric circulation for periods of warming and cooling in Svalbard during 1920–2018. International Journal of Climatology, 41(6), 34813502. doi: 10.1002/joc.7031 CrossRefGoogle Scholar
Lynch, A. H., & Brunner, R. D. (2007). Context and climate change: An integrated assessment for Barrow, Alaska. Climatic Change, 82(1–2), 93111. doi: 10.1007/s10584-006-9165-8 CrossRefGoogle Scholar
Mayer, S., Jonassen, M. O., Sandvik, A., & Reuder, J. (2012). Profiling the Arctic stable boundary layer in advent valley, Svalbard: Measurements and simulations. Boundary-Layer Meteorology, 143(3), 507526. doi: 10.1007/s10546-012-9709-6 Google Scholar
Meyer, A. (2022). Physical and feasible: Climate change adaptation in Longyearbyen, Svalbard. Polar Record, 58(2). doi: 10.1017/S0032247422000079 CrossRefGoogle Scholar
Misund, O. A. (2017). Academia in Svalbard: An increasingly important role for research and education as tools for Norwegian policy. Polar Research, 36(1). doi: 10.1080/17518369.2017.1308131 Google Scholar
Muckenhuber, S., Nilsen, F., Korosov, A., & Sandven, S. (2016). Sea ice cover in Isfjorden and Hornsund, Svalbard (2000–2014) from remote sensing data. Cryosphere 10, 149158. doi: 10.5194/tc-10-149-2016 CrossRefGoogle Scholar
Myers-smith, I. H., Kerby, J. T., Phoenix, G. K., Bjerke, J. W., Epstein, H. E., Assmann, J. J., … Wilmking, M. (2020). Complexity revealed in the greening of the Arctic. Nature Climate Change, 10. doi: 10.1038/s41558-019-0688-1 CrossRefGoogle Scholar
Nilsen, F., Cottier, F., Skogseth, R., & Mattsson, S. (2008). Fjord–shelf exchanges controlled by ice and brine production: The interannual variation of Atlantic Water in Isfjorden, Svalbard. Continental Shelf Research, 28(14), 18381853. doi: 10.1016/j.csr.2008.04.015 CrossRefGoogle Scholar
Nilsen, T. (2022). Midnight Sun heat wave. Barents Observer. https://thebarentsobserver.com/en/climate-crisis/2022/06/heatwave-northern-edge-europe (accessed 26 September 2024).Google Scholar
Nordli, Ø. (2010). The Svalbard Airport. Bulletin of Geography – Physical Geography Series, 3(3), 525.CrossRefGoogle Scholar
Nordli, Ø., Przybylak, R., Ogilvie, A. E. J., & Isaksen, K. (2014). Long-term temperature trends and variability on Spitsbergen: The extended Svalbard Airport temperature series, 1898–2012. Polar Research, 33(1), 21349. doi: 10.3402/polar.v33.21349 CrossRefGoogle Scholar
Nordli, Ø., Wyszyński, P., Gjelten, H. M., Isaksen, K., Łupikasza, E., Niedźwiedź, T., & Przybylak, R. (2020). Revisiting the extended Svalbard Airport monthly temperature series, and the compiled corresponding daily series 1898–2018. Polar Research. doi: 10.33265/polar.v39.3614 Google Scholar
Nyman, E., Galvao, C. B., Mileski, J., & Tiller, R. (2020). The Svalbard archipelago: An exploratory analysis of port investment in the context of the new arctic routes. Maritime Studies, 19, 113. doi: 10.1007/s40152-019-00143-4 CrossRefGoogle Scholar
Ødegaard, C. V. (2022). Returning to nature. Social Analysis, 66(2), 122. doi: 10.3167/sa.2022.660201 CrossRefGoogle Scholar
Orttung, R. W., Anisimov, O., Badina, S., Burns, C., Cho, L., DiNapoli, B., … Zhiltcova, Y. (2021). Measuring the sustainability of Russia’s Arctic cities. Ambio, 50(11), 20902103. doi: 10.1007/s13280-020-01395-9 Google ScholarPubMed
Orttung, R. W., Laruelle, M., Anisimov, O., Streletskiy, D., Shiklomanov, N., … Cooper, L. W. (2017). Urban Sustainability in the Arctic: Visions, Contexts, and Challenges. Washington, DC: IERES. https://www.academia.edu/33989516/Edited_Urban_Sustainability_in_the_Arctic_Visions_Contexts_Challenges_Washington_DC_IERES_2017_co_edited_with_Robert_Orttung (accessed 26 September 2024).Google Scholar
Osuch, M., & Wawrzyniak, T. (2017). Inter- and intra-annual changes in air temperature and precipitation in western Spitsbergen. International Journal of Climatology, 37(7), 30823097. doi: 10.1002/joc.4901 CrossRefGoogle Scholar
Outten, S., Esau, I., & Otterå, O. H. (2018). Bjerknes compensation in the CMIP5 climate models. Journal of Climate, 31(21), 87458760. doi: 10.1175/JCLI-D-18-0058.1 CrossRefGoogle Scholar
Overland, J. E., & Wang, M. (2021). The 2020 Siberian heat wave. International Journal of Climatology, 41(S1), 23412346. doi: 10.1002/joc.6850 CrossRefGoogle Scholar
Overland, J. E., Wang, M., Walsh, J. E., & Stroeve, J. C. (2014). Future Arctic climate changes: Adaptation and mitigation time scales. Earth’s Future, 2(2), 6874. doi: 10.1002/2013EF000162 CrossRefGoogle Scholar
Pedersen, T. (2019). Polar research and the secrets of the Arctic. Arctic Review on Law and Politics, 10(0), 103. doi: 10.23865/arctic.v10.1501 CrossRefGoogle Scholar
Petrov, A. N., BurnSilver, S., Chapin, F. S., Fondahl, G., Graybill, J., Keil, K., … Schweitzer, P. (2016). Arctic sustainability research: toward a new agenda. Polar Geography, 39(3), 165178. doi: 10.1080/1088937X.2016.1217095 CrossRefGoogle Scholar
Petrov, A. N., Rozanova Smith, M. S., Krivorotov, A. K., Klyuchnikova, E. M., Mikheev, V. L., Pelyasov, A. N., & Zamyatina, N. Y. (2021). The Russian Arctic by 2050: Developing integrated scenarios. Arctic, 74(3), 306322. doi: 10.14430/arctic73242 Google Scholar
Pilguj, N., Kolendowicz, L., Kryza, M., Migała, K., & Czernecki, B. (2019). Temporal changes in wind conditions at Svalbard for the years 1986–2015. Geografiska Annaler, Series A: Physical Geography, 101(2), 136156. doi: 10.1080/04353676.2019.1572973 CrossRefGoogle Scholar
Pithan, F., Svensson, G., Caballero, R., Chechin, D., Cronin, T. W., Ekman, A. M. L., Neggers, R., … Wendisch, M. (2018). Role of air-mass transformations in exchange between the Arctic and mid-latitudes. Nature Geoscience, 11(11), 805812. doi: 10.1038/s41561-018-0234-1 CrossRefGoogle Scholar
Pressman, N. E. P. (1996). Sustainable winter cities: Future directions for planning, policy and design. Atmospheric Environment, 30(3), 521529. doi: 10.1016/1352-2310(95)00012-7 CrossRefGoogle Scholar
Previdi, M., Smith, K. L., & Polvani, L. M. (2021). Arctic amplification of climate change: A review of underlying mechanisms. Environmental Research Letters, 16(9), 093003. doi: 10.1088/1748-9326/ac1c29 CrossRefGoogle Scholar
Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., … Laaksonen, A. (2022). The Arctic has warmed nearly four times faster than the globe since 1979. Communications Earth and Environment, 3(1). doi: 10.1038/s43247-022-00498-3 Google Scholar
Reimann, S., Kallenborn, R., & Schmidbauer, N. (2009). Severe aromatic hydrocarbon pollution in the Arctic town of Longyearbyen (Svalbard) caused by Snowmobile emissions. Environmental Science & Technology, 43(13), 47914795. doi: 10.1021/es900449x CrossRefGoogle ScholarPubMed
Ringkjøb, H.-K., Haugan, P. M., & Nybø, A. (2020). Transitioning remote Arctic settlements to renewable energy systems – A modelling study of Longyearbyen, Svalbard. Applied Energy, 258, 114079. doi: 10.1016/j.apenergy.2019.114079 CrossRefGoogle Scholar
Rinke, A., Segger, B., Crewell, S., Maturilli, M., Naakka, T., Nygård, T., … Keller, A. J. (2019). Trends of vertically integrated water vapor over the Arctic during 1979–2016: Consistent moistening all over? Journal of Climate, 32(18), 60976116. doi: 10.1175/JCLI-D-19-0092.1 Google Scholar
Shiklomanov, N., Streletskiy, D., Suter, L., Orttung, R., & Zamyatina, N. (2020). Dealing with the bust in Vorkuta, Russia. Land Use Policy, 93, 103908. doi: 10.1016/j.landusepol.2019.03.021 CrossRefGoogle Scholar
Shiklomanov, N. I., Streletskiy, D. A., Grebenets, V. I., & Suter, L. (2017). Conquering the permafrost: urban infrastructure development in Norilsk, Russia. Polar Geography, 40(4), 273290. doi: 10.1080/1088937x.2017.1329237 CrossRefGoogle Scholar
Shiklomanov, N. I., Streletskiy, D. A., Swales, T. B., & Kokorev, V. A. (2016). Climate change and stability of urban infrastructure in Russian permafrost regions: Prognostic assessment based on GCM climate projections. Geographical Review, 118. doi: 10.1111/gere.12214 Google Scholar
Skogseth, R., Olivier, L. L. A., Nilsen, F., Falck, E., Fraser, N., Tverberg, V., … Falk-Petersen, S. (2020). Variability and decadal trends in the Isfjorden (Svalbard) ocean climate and circulation – An indicator for climate change in the European Arctic. Progress in Oceanography, 187, 102394. doi: 10.1016/j.pocean.2020.102394 Google Scholar
Smith, S. L., O’Neill, H. B., Isaksen, K., Noetzli, J., & Romanovsky, V. E. (2022). The changing thermal state of permafrost. Nature Reviews Earth & Environment, 3(1), 1023. doi: 10.1038/s43017-021-00240-1 CrossRefGoogle Scholar
Solbakken, K., Babar, B., & Boström, T. (2016). Correlation of wind and solar power in high-latitude arctic areas in Northern Norway and Svalbard. Renewable Energy and Environmental Sustainability, 1, 42. doi: 10.1051/rees/2016027 CrossRefGoogle Scholar
SPL. (2020). Statistics port of Longyearbyen. ähttps://portlongyear.no/wp-content/uploads/2020/02/Bättrafikk_2007_2012-2019.pdf (accessed 26 September 2024).Google Scholar
Stocker, A. N., Renner, A. H. H., & Knol-Kauffman, M. (2020). Sea ice variability and maritime activity around Svalbard in the period 2012–2019. Scientific Reports, 10(1), 17043. doi: 10.1038/s41598-020-74064-2 CrossRefGoogle ScholarPubMed
Streletskiy, D. A., Suter, L. J., Shiklomanov, N. I., Porfiriev, B. N., & Eliseev, D. O. (2019). Assessment of climate change impacts on buildings, structures and infrastructure in the Russian regions on permafrost. Environmental Research Letters, 14(2), 025003. doi: 10.1088/1748-9326/aaf5e6 CrossRefGoogle Scholar
Stuecker, M. F., Bitz, C. M., Armour, K. C., Proistosescu, C., Kang, S. M., Xie, S., … Jin, F.-F. (2018). Polar amplification dominated by local forcing and feedbacks. Nature Climate Change, 8(12), 10761081. doi: 10.1038/s41558-018-0339-y Google Scholar
Suter, L., Streletskiy, D., & Shiklomanov, N. (2019). Assessment of the cost of climate change impacts on critical infrastructure in the circumpolar Arctic. Polar Geography, 42(4), 267286. doi: 10.1080/1088937X.2019.1686082 CrossRefGoogle Scholar
Taylor, P. C., Boeke, R. C., Boisvert, L. N., Feldl, N., Henry, M., Huang, Y., … Tan, I. (2022). Process drivers, inter-model spread, and the path forward: A review of amplified Arctic warming. Frontiers in Earth Science, 9. doi: 10.3389/feart.2021.758361 CrossRefGoogle Scholar
Valkonen, T., Stoll, P., Batrak, Y., Køltzow, M., Schneider, T. M., Stigter, E. E., … Jonassen, M. O. (2020). Evaluation of a sub-kilometre NWP system in an Arctic fjord-valley system in winter. Tellus A: Dynamic Meteorology and Oceanography, 72(1), 1838181. doi: 10.1080/16000870.2020.1838181 Google Scholar
Vaughan, A. (2020). A warning cry from the Arctic. New Scientist, 247(3295), 1819. doi: 10.1016/S0262-4079(20)31399-3 Google Scholar
Vickers, H., Høgda, K. A., Solbø, S., Karlsen, S. R., Tømmervik, H., Aanes, R., & Hansen, B. B. (2016). Changes in greening in the high Arctic: Insights from a 30 year AVHRR max NDVI dataset for Svalbard. Environmental Research Letters, 11(10), 105004. doi: 10.1088/1748-9326/11/10/105004 Google Scholar
Vikhamar-Schuler, D., Lutz, J., & Gjelten, H. M. (2019). Evaluation of downscaled reanalysis and observations for Svalbard. NCCS report no. 4/2019, 57 pp.Google Scholar
Westermann, S., Langer, M., & Boike, J. (2011). Spatial and temporal variations of summer surface temperatures of high-arctic tundra on Svalbard — Implications for MODIS LST based permafrost monitoring. Remote Sensing of Environment, 115(3), 908922. doi: 10.1016/j.rse.2010.11.018 CrossRefGoogle Scholar
Westermann, S., Lüers, J., Langer, M., Piel, K., & Boike, J. (2009). The annual surface energy budget of a high-arctic permafrost site on Svalbard, Norway. The Cryosphere, 3(2), 245263. doi: 10.5194/tc-3-245-2009 CrossRefGoogle Scholar
Wickström, S., Jonassen, M. O., Cassano, J. J., & Vihma, T. (2020). Present temperature, precipitation and rain-on-snow climate in Svalbard. Journal of Geophysical Research: Atmospheres. doi: 10.1029/2019JD032155 CrossRefGoogle Scholar
Winther, S. N., & Gudmestad, O. T. (2023). Impact of and solutions to effects of climate changes for Longyearbyen, Svalbard, Norway. IOP Conference Series: Materials Science and Engineering, 1294(1), 012036. doi: 10.1088/1757-899X/1294/1/012036 CrossRefGoogle Scholar
Zhang, W., Miller, P. A., Jansson, C., Samuelsson, P., Mao, J., & Smith, B. (2018). Self-amplifying feedbacks accelerate greening and warming of the Arctic. Geophysical Research Letters, 45(14), 71027111. doi: 10.1029/2018GL077830 CrossRefGoogle Scholar
Zhuravskiy, D., Ivanov, B., & Pavlov, A. (2012). Ice conditions at Gronfjorden Bay, Svalbard, from 1974 to 2008. Polar Geography, 35(2), 169176. doi: 10.1080/1088937X.2012.662535 CrossRefGoogle Scholar
Figure 0

Figure 1. The map of Longyearbyen and its surrounding area with identified locations of observational sites. The main station at the Svalbard airport is shown as a red dot with a black circle. Stations of the Norwegian Meteorological Institute (MET.NORWAY) are shown in red; stations of the University Centre in Svalbard (UNIS) – in blue; and the private citizens’ stations NETATMO – in grey. The background topographic map is taken from TopoSvalbard (https://toposvalbard.npolar.no; The Norwegian Polar Institute).

Figure 1

Figure 2. Elements (vegetation index and land surface temperature) of the local climate perspective in Longyearbyen. Land Surface Temperature (LST) and Normalised Vegetation Difference Index (NDVI) are retrieved from satellite observations. The domains (A) and (B) are taken from (Bartsch et al., 2021) and present the Sentinel-1 and −2 NDVI trend data. The domains (C) and (D) are own analysis and present the Landsat-8 images: LST – from the bands 10 and 11 (100 m spatial resolution); NDVI – from the bands 4 and 5 (30 m spatial resolution). The base layer shows urban infrastructure from OpenStreetMap data (https://download.geofabrik.de/).

Figure 2

Figure 3. Hazard zonation map for Longyearbyen available from NVE (https://temakart.nve.no/link/?link=faresoner&layer=5&field=KOMMNAVN&value=Spitsbergen&buffer=100), see also methods in (Engeset et al., 2020); inserts show two major snow slab avalanches in the town on December 19, 2015 and February 21, 2017. Both avalanches occur after severe snowstorms with easterly winds. Pictures are from the NVE report (Landrø et al., 2017); the avalanche location assessment is after (Eckerstorfer & Christiansen, 2011).

Figure 3

Figure 4. Graphical presentation of the study connecting three development pathways to influential climate factors. The Svalbard cartoon map from (https://www.subpng.com; by Vskuagtekt) is free for non-commercial use. Photos are taken by the authors. The cruise ship is “M/S Roald Amundsen.”

Figure 4

Table 1. Consequences of climate change in Longyearbyen – a summary inspired by Table 2 in Hovelsrud et al. (2020); updated and corrected to account for the local climate perspective