Oskar Landgren

Arctic climate projections are characterized by pronounced uncertainty, stemming mainly from structural uncertainties related to the representation of Arctic processes and feedbacks, including those associated with permafrost, cryosphere–atmosphere coupling, and sea ice. Within the PolarRES project’s framework, we apply a storyline-based approach to address parts of these uncertainties and investigate how different physically plausible Arctic futures manifest in high-resolution regional climate simulations. We analyze an ensemble of five regional climate models (RCMs) at 11 km resolution over the Arctic, each driven by two CMIP6 global climate models representing contrasting storylines of Arctic change: CNRM-ESM2-1 and NorESM2-MM, under the high-emission scenario SSP3-7.0. The two driving GCMs differ in their representation of Arctic climate change mechanisms, with NorESM2-MM exhibiting stronger lower-tropospheric Arctic amplification and CNRM-ESM2-1 showing comparatively weaker atmospheric amplification but enhanced surface warming in the Barents–Kara Sea region.Climate change signals are assessed by comparing end-of-century conditions (2070–2099) to a present-day reference period (1985–2014) for near-surface 2 m air temperature, total precipitation, and the seasonal number of freezing (ice) days. Across all variables, the RCMs broadly reproduce the large-scale spatial patterns imposed by their driving GCMs, but also introduce pronounced regional modifications and inter-model spread, particularly over the ice covered parts of the Arctic ocean.The strongest warming occurs in winter, exceeding 15 K over parts of the Arctic Ocean, with several RCMs amplifying the Barents–Kara Sea warming relative to the driving models. Summer warming is comparatively weak and consistent across both storylines, whereas spring and autumn exhibit enhanced inter-RCM variability, pointing to sensitivities in snow-albedo feedbacks and melt–freeze processes. Changes in freezing days reveal substantial ensemble spread in summer, despite similar mean temperature change signals, highlighting the nonlinear dependence of threshold-based metrics on absolute temperature levels.Projected precipitation increases are largest in winter and autumn, particularly over the Arctic Ocean and the Barents–Kara region, with relative increases often exceeding 80–100%. While overall patterns resemble those of the driving GCMs, individual RCMs exhibit notable deviations, especially over sea-ice loss regions.These results demonstrate that regional climate models add important, physically meaningful structure to Arctic climate change signals, emphasizing the role of regional processes in shaping plausible future Arctic climates within a storyline framework.

In an era characterized by urban densification and increasing pressures on urban space, along with the costs and availability of construction materials, the optimal design of infrastructure has become a critical focus. Furthermore, cold climate regions are experiencing the impacts of climate change, which manifest in altered precipitation patterns, resulting in more extreme storm events, including rain-on-snow events and increased freeze-thaw cycles. According to Maurin et al. (2024), rain-on-snow events have been identified as the leading cause of the highest observed runoff from green roofs, presenting significant challenges for urban areas in preventing flooding.The present study aims to enhance understanding of the effects of climate variability and change on the hydrological performance of nature-based infrastructure, with a particular emphasis on green roofs during winter, especially in relation to snow and rain-on-snow events in cold climate regions. The goal is to develop guidelines that assist stakeholders in optimizing the design of nature-based solutions (NBS) infrastructure, ensuring they are resilient over time and effectively manage stormwater in a changing climate. This initiative addresses the current gap in research, particularly the lack of location-specific regulations that incorporate future climate projections for stormwater infrastructure design, giving decision-makers accurate information regarding the requirements for long-term and robust infrastructure design.The study uses models of six different green and grey roof configurations developed in the SFI Klima 2050 project, calibrated for the winter season. These models utilize precipitation and temperature time series originated from high-resolution, convection-permitting climate models with hourly resolution and a 3x3 km gridded projection. Simulations for winter event separation (Melt, Rain and Rain-on-snow) are conducted following the methodology outlined in Maurin et al. (2024).Results indicate that the changing climate will influence stormwater management strategies during winter, including higher runoffs of urban infrastructure due to rain-on-snow event with effects unevenly distributed across Norway (9 different cities studied). This pinpoints the need to combine the local future climate with hydrological models able to capture rain-on-snow events when planning and designing stormwater managements solutions that must remain effective under future climate scenarios. The findings have laid the groundwork for local guidelines aimed at ensuring climate-resilient design of nature-based infrastructure.Maurin, N., Abdalla, E.H.M., Muthanna, T.M., Sivertsen, E., 2024. Understanding the hydrological performance of green and grey roofs during winter in cold climate regions. Science of The Total Environment 945, 174132. https://doi.org/10.1016/j.scitotenv.2024.174132

Storylines are physically plausible scenarios of future climate change, statistically derived from an ensemble of climate model projections and organized according to the magnitude of projected changes in two or more remote drivers that strongly influence the spatial pattern of the climate response. Here, we provide novel insights into the Arctic storylines identified by Levine et al. (2024), where Barents-Kara Sea warming and lower-tropospheric Arctic warming during the extended summer season (May–October) were remote drivers, as we identify a set of models from the Coupled Model Intercomparison Project phase 6 to represent the storylines. We do this by first identifying models that are similar to these storylines in terms of each remote driver response and quantifying this similarity. Second, we evaluate the model’s performance in terms of a simple performance score based on the mean normalized root-mean-square error for multiple climate variables of importance for the storylines. The normalized values vary between 0 and 1 for all variables, allowing them to exert a comparable influence on the score. The advantage of the score is that it provides an easily implementable and interpretable way of identifying models that are characterized by large errors relative to the rest of the ensemble. Finally, we combine the similarity estimate and the score to select models to represent the storylines. We focus on the Arctic during the extended summer season for which the storylines were designed, but also consider other seasons and regions. Through this exercise, we also document the methodology, benefits, and limitations of the score.

This study explores the projected response of atmospheric circulation regimes, which are preferred and recurrent large-scale circulation patterns, to future climate change scenarios. We focus on the North Atlantic–Eurasian and Arctic regions in the boreal summer season. Using Simulated Annealing and Diversified Randomization (SAN) and K-means (KME) clustering methods, we analyse 20 global climate models from the CMIP6 ensemble to assess shifts in frequency of occurrence of circulation regimes for the end of the century under a high emission scenario. Additionally, storylines of summer Arctic climate change constrained by Barents–Kara Seas warming and Arctic Amplification are incorporated to contextualize potential future atmospheric behaviours. Despite slight differences between the SAN and KME methods in identifying spatial regime structures, the patterns remain largely unchanged under future climate scenarios. Our analysis highlights the changing frequency of atmospheric circulation regimes under climate change. A significant occurrence change is detected for the North Atlantic Oscillation (NAO) regime by both methods, where positive phases are projected to become more frequent, consistent with previous studies. In the Arctic region, both clustering algorithms predict an increase in circulation regimes linked to negative pressure anomalies above the Arctic. This aligns with the projected increased occurrence of the positive NAO regime over the North Atlantic–Eurasian sector. Our analysis underscores that, while storylines provide a nuanced approach to exploring plausible climate futures, no consistent shifts in the occurrence of atmospheric circulation regimes emerge across the two studied storylines, possibly due to the small number of models representing each storyline. Furthermore, influences from regional climate changes such as Barents–Kara seas warming and Arctic Amplification exhibit minimal impact on overarching circulation regimes. These findings contribute to an improved understanding of the sensitivity of atmospheric circulation regimes to climate change, with implications for predicting future extreme weather occurrences across these key regions.

Rain-on-snow (ROS) events in Svalbard are occurring more frequently during the winter season due to rapid and ongoing climate warming across the Arctic. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, specifically their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present-day analysis and km-scale climate projections from the HARMONIE Climate (HCLIM) regional model obtained by downscaling the Max Planck Institute for Meteorology Earth System Model Version 1.2 at Low Resolution. The HCLIM projections cover the near future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and positive trends in the mean duration, intensity and total precipitation of ROS events but these are confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in these characteristics. On the other hand, there are significant and positive trends in ROS frequency across most parts of the archipelago except for the highest lying glaciated areas in northern Spitsbergen and Nordaustlandet. Analysis of the HCLIM future projections showed that the largest changes relative to present day conditions in all ROS characteristics are projected to occur over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas are projected to experience a decrease. Moreover, while ROS has increased most in October and May in the present climate, the future climate simulations project a substantial increase in ROS events in April, which currently experiences very few, if any, ROS events. This may lead to considerable changes in snow hydrology. The frequency of ROS is projected to increase most over high elevation and glaciated areas in October, November, April and May by 2070, but with considerable reductions in low lying areas close to the western and southern coast as well as across many valleys in central Svalbard in October and May. While km-scale models, such as the model used here, reduces some of the uncertainty in projected changes in ROS through improved representation of important physical processes, their computational costs prohibit the use of model ensembles to address uncertainty in projected changes. We partially addressed the uncertainty associated with model parameterisation and internal climate variability by analysing two coarser-resolution, 11 km-scale climate projections under the moderate emissions SSP3-7.0 scenario. Our analysis indicated that there are areas of Svalbard where the change in all ROS characteristics carries greater uncertainty, as demonstrated by the opposite direction of change exhibited in the two additional global climate models. On the other hand, all three model projections showed agreement over the increase in ROS frequency over large parts of the archipelago in the 2050–2070 period. Further work should include analysing a larger ensemble of climate projections downscaled by several RCMs for Svalbard to produce a broader range of ROS scenarios, as well as carrying out a more in-depth analysis of the changes in relative contributions of local vs. remote moisture sources to changing patterns of precipitation, and analysing the hydrological impacts associated with the changes in ROS characteristics identified in this study.

Rain-on-snow (ROS) events in Svalbard are becoming a more frequent occurrence during the winter season due to rapid climate warming across the Arctic in recent decades. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, such as their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present day analysis and km-scale climate projections from a regional climate model for the future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and increasing trends in all characteristics but confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in all characteristics. Analysis of the future projections showed that the largest changes relative to present day conditions in all ROS characteristics will take place over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas will experience a decrease. This reduction is expected to be the result of fewer days with snow, shortening the season where rain can fall on an existing snow cover. Moreover, while ROS has increased most in November and February, the future climate simulation features a substantial increase in ROS events in April, which experiences very few, if any, ROS events in the present climate, which may lead to considerable changes in snow hydrology. Further work could include analysing an ensemble of climate projections for Svalbard to produce a range of ROS scenarios, as well as carrying out a more in-depth analysis of the hydrological impacts associated with the changes in ROS characteristics identified here.

Rain-on-snow (ROS) events in Svalbard are becoming a more frequent occurrence during the winter season due to rapid climate warming across the Arctic in recent decades. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, such as their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present day analysis and km-scale climate projections from a regional climate model for the future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and increasing trends in all characteristics but confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in all characteristics. Analysis of the future projections showed that the largest changes relative to present day conditions in all ROS characteristics will take place over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas will experience a decrease. This reduction is expected to be the result of fewer days with snow, shortening the season where rain can fall on an existing snow cover. Moreover, while ROS has increased most in November and February, the future climate simulation features a substantial increase in ROS events in April, which experiences very few, if any, ROS events in the present climate, which may lead to considerable changes in snow hydrology. Further work could include analysing an ensemble of climate projections for Svalbard to produce a range of ROS scenarios, as well as carrying out a more in-depth analysis of the hydrological impacts associated with the changes in ROS characteristics identified here.

Rain-on-snow (ROS) events in Svalbard are becoming a more frequent occurrence during the winter season due to rapid climate warming across the Arctic in recent decades. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, such as their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present day analysis and km-scale climate projections from a regional climate model for the future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and increasing trends in all characteristics but confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in all characteristics. Analysis of the future projections showed that the largest changes relative to present day conditions in all ROS characteristics will take place over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas will experience a decrease. This reduction is expected to be the result of fewer days with snow, shortening the season where rain can fall on an existing snow cover. Moreover, while ROS has increased most in November and February, the future climate simulation features a substantial increase in ROS events in April, which experiences very few, if any, ROS events in the present climate, which may lead to considerable changes in snow hydrology. Further work could include analysing an ensemble of climate projections for Svalbard to produce a range of ROS scenarios, as well as carrying out a more in-depth analysis of the hydrological impacts associated with the changes in ROS characteristics identified here.

Rain-on-snow (ROS) events in Svalbard are becoming a more frequent occurrence during the winter season due to rapid climate warming across the Arctic in recent decades. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, such as their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present day analysis and km-scale climate projections from a regional climate model for the future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and increasing trends in all characteristics but confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in all characteristics. Analysis of the future projections showed that the largest changes relative to present day conditions in all ROS characteristics will take place over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas will experience a decrease. This reduction is expected to be the result of fewer days with snow, shortening the season where rain can fall on an existing snow cover. Moreover, while ROS has increased most in November and February, the future climate simulation features a substantial increase in ROS events in April, which experiences very few, if any, ROS events in the present climate, which may lead to considerable changes in snow hydrology. Further work could include analysing an ensemble of climate projections for Svalbard to produce a range of ROS scenarios, as well as carrying out a more in-depth analysis of the hydrological impacts associated with the changes in ROS characteristics identified here.

Rain-on-snow (ROS) events in Svalbard are becoming a more frequent occurrence during the winter season due to rapid climate warming across the Arctic in recent decades. ROS events have gained increasing attention in recent decades due to their cascading impacts on the physical environment, and terrestrial and marine ecosystems that are impacted by snowmelt. While the frequency of ROS events in Svalbard has been well studied and documented, other characteristics of ROS, such as their duration, intensity and seasonal timing have received less attention. Such characteristics are equally important to quantify due to their potential consequences for the winter snowpack and snow-dependent ecosystems. This study addresses this knowledge gap using the Copernicus Arctic Regional Reanalysis (CARRA) for the present day analysis and km-scale climate projections from a regional climate model for the future period of 2030–2070 under the high emissions scenario SSP5-8.5. For the present climate, the results show significant and increasing trends in all characteristics but confined mainly to low-lying areas of Nordaustlandet and some areas in the east of the archipelago, while no statistically significant trend was found in the southern and western areas which typically exhibit the largest values in all characteristics. Analysis of the future projections showed that the largest changes relative to present day conditions in all ROS characteristics will take place over the mountainous and glaciated areas in the north and northeast of the archipelago, while some low lying western coastal areas will experience a decrease. This reduction is expected to be the result of fewer days with snow, shortening the season where rain can fall on an existing snow cover. Moreover, while ROS has increased most in November and February, the future climate simulation features a substantial increase in ROS events in April, which experiences very few, if any, ROS events in the present climate, which may lead to considerable changes in snow hydrology. Further work could include analysing an ensemble of climate projections for Svalbard to produce a range of ROS scenarios, as well as carrying out a more in-depth analysis of the hydrological impacts associated with the changes in ROS characteristics identified here.