Influence of sea ice on Arctic precipitation

Bioclimatic atlas of the terrestrial Arctic

The Arctic is the region on Earth that is warming at the fastest rate. In addition to rising means of temperature-related variables, Arctic ecosystems are affected by increasingly frequent extreme weather events causing disturbance to Arctic ecosystems. Here, we introduce a new dataset of bioclimatic indices relevant for investigating the changes of Arctic terrestrial ecosystems. The dataset, called ARCLIM, consists of several climate and event-type indices for the northern high-latitude land areas > 45°N. The indices are calculated from the hourly ERA5-Land reanalysis data for 1950-2021 in a spatial grid of 0.1 degree (~9 km) resolution. The indices are provided in three subsets: (1) the annual values during 1950-2021; (2) the average conditions for the 1991-2020 climatology; and (3) temporal trends over 1951-2021. The 72-year time series of various climate and event-type indices draws a comprehensive picture of the occurrence and recurrence of extreme weather events and climate variability of the changing Arctic bioclimate.

Sufficient conditions for rapid range expansion of a boreal conifer

Unprecedented modern rates of warming are expected to advance boreal forest into Arctic tundra¹, thereby reducing albedo^2–4, altering carbon cycling⁴ and further changing climate^1–4, yet the patterns and processes of this biome shift remain unclear⁵. Climate warming, required for previous boreal advances^6–17, is not sufficient by itself for modern range expansion of conifers forming forest–tundra ecotones^{5,12–15,17–20}. No high-latitude population of conifers, the dominant North American Arctic treeline taxon, has previously been documented⁵ advancing at rates following the last glacial maximum (LGM)^6–8. Here we describe a population of white spruce (Picea glauca) advancing at post-LGM rates⁷ across an Arctic basin distant from established treelines and provide evidence of mechanisms sustaining the advance. The population doubles each decade, with exponential radial growth in the main stems of individual trees correlating positively with July air temperature. Lateral branches in adults and terminal leaders in large juveniles grow almost twice as fast as those at established treelines. We conclude that surpassing temperature thresholds^1,6–17, together with winter winds facilitating long-distance dispersal, deeper snowpack and increased soil nutrient availability promoting recruitment and growth, provides sufficient conditions for boreal forest advance. These observations enable forecast modelling with important insights into the environmental conditions converting tundra into forest.

A boreal conifer is advancing northwards into Arctic tundra, with this treeline advance facilitated by climate warming together with winter winds, deeper snow and increased soil nutrient availability.

Scandinavian Forest Fire Activity Correlates with Proxies of the Baffin Bay Ice Cover

Understanding factors driving fire activity helps reveal the degree and geographical variability in the resilience of boreal vegetation to large scale climate forces. We studied the association between sea ice cover in the Baffin Bay and the Labrador Sea and observational records of forest fires in two Nordic countries (Norway and Sweden) over 1913–2017. We found a positive correlation between ice proxies and regional fire activity records suggesting that the Arctic climate and the associated changes in North Atlantic circulation exercise an important control on the levels of fire activity in Scandinavia. Changes in the sea cover are likely correlated with the dynamic of the North Atlantic Current. These dynamics may favor the development of the drought conditions in Scandinavia through promoting persistent high-pressure systems over the Scandinavian boreal zone during the spring and summer. These periods are, in turn, associated with an increased water deficit in forest fuels, leading to a regionally increased fire hazard. The Arctic climate will likely be an important future control of the boreal fire activity in the Nordic region.

Varying response of vegetation to sea ice dynamics over the Arctic

Recent reduction of sea ice may have contributed to vegetation growth over the Arctic through albedo feedback effects to atmospheric warming. Understanding the varying response of vegetation to sea ice dynamics is critical for predicting future climate change over the Arctic and middle-high latitudes. Instead of looking at the direct response characteristics, we perform a systematic analysis of the time-lag and time-cumulation responses of vegetation to sea ice dynamics, using a long-term Arctic Normalized Difference Vegetation Index (NDVI) dataset and three sea ice indices (sea ice concentration (SIC), sea ice area (SIA) and sea ice extent (SIE)) from 1982 to 2015. The results show that annual NDVI in the Arctic has exhibited a significant (p < 0.05) increase during 1982 to 2015, while a significant (p < 0.05) decrease is detected for annual SIC, SIA and SIE. The results of a regression analysis on NDVI identify a lag time of 7-months, 8-months and 9-months for vegetation response to SIC, SIA and SIE in February, March and April, respectively, while no evident lag response is observed in summer except for August. For the cumulation response, NDVI in February, March and April shows the largest response to the previous 5, 7 and 9 months of sea ice variations, respectively, while a short cumulation response of 1 to 3 months is found in summer. The differences in the spatial patterns of lagged time are usually not statistically significant in autumn and winter. A shorter lag response (1-3 month) is found in the Yamalia region in June. Further analysis suggests that vegetation response to sea ice dynamics depends on bio - climatic characteristics and soil pH, with vegetation responding faster to sea ice changes in acidic soil. This study provides observational evidences on the varying response of vegetation to sea ice dynamics over the Arctic, which has great implications for predicting vegetation-climate feedback and climate change.

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere

The Arctic sea ice has retreated rapidly in the past few decades, which is believed to be driven by various dynamic and thermodynamic processes in the atmosphere. The newly open water resulted from sea ice decline in turn exerts large influence on the atmosphere. Therefore, this study aims to investigate the causality between multiple atmospheric processes and sea ice variations using three distinct data-driven causality approaches that have been proposed recently: Temporal Causality Discovery Framework Non-combinatorial Optimization via Trace Exponential and Augmented lagrangian for Structure learning (NOTEARS) and Directed Acyclic Graph-Graph Neural Networks (DAG-GNN). We apply these three algorithms to 39 years of historical time-series data sets, which include 11 atmospheric variables from ERA-5 reanalysis product and passive microwave satellite retrieved sea ice extent. By comparing the causality graph results of these approaches with what we summarized from the literature, it shows that the static graphs produced by NOTEARS and DAG-GNN are relatively reasonable. The results from NOTEARS indicate that relative humidity and precipitation dominate sea ice changes among all variables, while the results from DAG-GNN suggest that the horizontal and meridional wind are more important for driving sea ice variations. However, both approaches produce some unrealistic cause-effect relationships. Additionally, these three methods cannot well detect the delayed impact of one variable on another in the Arctic. It also turns out that the results are rather sensitive to the choice of hyperparameters of the three methods. As a pioneer study, this work paves the way to disentangle the complex causal relationships in the Earth system, by taking the advantage of cutting-edge Artificial Intelligence technologies.

Glacio-Nival Regime Creates Complex Relationships between Discharge and Climatic Trends of Zackenberg River, Greenland (1996–2019)

Arctic environments experience rapid climatic changes as air temperatures are rising and precipitation is increasing. Rivers are key elements in these regions since they drain vast land areas and thereby reflect various climatic signals. Zackenberg River in northeast Greenland provides a unique opportunity to study climatic influences on discharge, as the river is not connected to the Greenland ice sheet. The study aims to explain discharge patterns between 1996 and 2019 and analyse the discharge for correlations to variations in air temperature and both solid and liquid precipitation. The results reveal no trend in the annual discharge. A lengthening of the discharge period is characterised by a later freeze-up and extreme discharge peaks are observed almost yearly between 2005 and 2017. A positive correlation exists between the length of the discharge period and the Thawing Degree Days (r=0.52,p<0.01), and between the total annual discharge and the annual maximum snow depth (r=0.48,p=0.02). Thereby, snowmelt provides the main source of discharge in the first part of the runoff season. However, the influence of precipitation on discharge could not be fully identified, because of uncertainties in the data and possible delays in the hydrological system. This calls for further studies on the relationship between discharge and precipitation. The discharge patterns are also influenced by meltwater from the A.P. Olsen ice cap and an adjacent glacier-dammed lake which releases outburst floods. Hence, this mixed hydrological regime causes different relationships between the discharge and climatic trends when compared to most Arctic rivers.

Acceleration of western Arctic sea ice loss linked to the Pacific North American pattern

Recent rapid Arctic sea-ice reduction has been well documented in observations, reconstructions and model simulations. However, the rate of sea ice loss is highly variable in both time and space. The western Arctic has seen the fastest sea-ice decline, with substantial interannual and decadal variability, but the underlying mechanism remains unclear. Here we demonstrate, through both observations and model simulations, that the Pacific North American (PNA) pattern is an important driver of western Arctic sea-ice variability, accounting for more than 25% of the interannual variance. Our results suggest that the recent persistent positive PNA pattern has led to increased heat and moisture fluxes from local processes and from advection of North Pacific airmasses into the western Arctic. These changes have increased lower-tropospheric temperature, humidity and downwelling longwave radiation in the western Arctic, accelerating sea-ice decline. Our results indicate that the PNA pattern is important for projections of Arctic climate changes, and that greenhouse warming and the resultant persistent positive PNA trend is likely to increase Arctic sea-ice loss.

Arctic Snow Isotope Hydrology: A Comparative Snow-Water Vapor Study

The Arctic’s winter water cycle is rapidly changing, with implications for snow moisture sources and transport processes. Stable isotope values (δ18O, δ2H, d-excess) of the Arctic snowpack have potential to provide proxy records of these processes, yet it is unclear how well the isotope values of individual snowfall events are preserved within snow profiles. Here, we present water isotope data from multiple taiga and tundra snow profiles sampled in Arctic Alaska and Finland, respectively, during winter 2018–2019. We compare the snowpack isotope stratigraphy with meteoric water isotopes (vapor and precipitation) during snowfall days, and combine our measurements with satellite observations and reanalysis data. Our analyses indicate that synoptic-scale atmospheric circulation and regional sea ice coverage are key drivers of the source, amount, and isotopic composition of Arctic snowpacks. We find that the western Arctic tundra snowpack profiles in Alaska preserved the isotope values for the most recent storm; however, post depositional processes modified the remaining isotope profiles. The overall seasonal evolution in the vapor isotope values were better preserved in taiga snow isotope profiles in the eastern Arctic, where there is significantly less wind-driven redistribution than in the open Alaskan tundra. We demonstrate the potential of the seasonal snowpack to provide a useful proxy for Arctic winter-time moisture sources and propose future analyses.

Coupled impacts of sea ice variability and North Pacific atmospheric circulation on Holocene hydroclimate in Arctic Alaska

Arctic Alaska lies at a climatological crossroads between the Arctic and North Pacific Oceans. The modern hydroclimate of the region is responding to rapidly diminishing sea ice, driven in part by changes in heat flux from the North Pacific. Paleoclimate reconstructions have improved our knowledge of Alaska's hydroclimate, but no studies have examined Holocene sea ice, moisture, and ocean-atmosphere circulation in Arctic Alaska, limiting our understanding of the relationship between these phenomena in the past. Here we present a sedimentary diatom assemblage and diatom isotope dataset from Schrader Pond, located ∼80 km from the Arctic Ocean, which we interpret alongside synthesized regional records of Holocene hydroclimate and sea ice reduction scenarios modeled by the Hadley Centre Coupled Model Version 3 (HadCM3). The paleodata synthesis and model simulations suggest the Early and Middle Holocene in Arctic Alaska were characterized by less sea ice, a greater contribution of isotopically heavy Arctic-derived moisture, and wetter climate. In the Late Holocene, sea ice expanded and regional climate became drier. This climatic transition is coincident with a documented shift in North Pacific circulation involving the Aleutian Low at ∼4 ka, suggesting a Holocene teleconnection between the North Pacific and Arctic. The HadCM3 simulations reveal that reduced sea ice leads to a strengthened Aleutian Low shifted west, potentially increasing transport of warm North Pacific water to the Arctic through the Bering Strait. Our findings demonstrate the interconnectedness of the Arctic and North Pacific on multimillennial timescales, and are consistent with future projections of less sea ice and more precipitation in Arctic Alaska.

High cloud coverage over melted areas dominates the impact of clouds on the albedo feedback in the Arctic

Warming in the Arctic is larger than the global average. A primary reason for this Arctic Amplification is the albedo feedback. The contrasting albedo of sea ice and dark melted surface areas is the key component of albedo feedback. Cloud coverage over the changing surface and the response of the clouds to the changing surface conditions will modify the change in planetary albedo when sea ice melts. Space-based lidar measurements provide a unique opportunity for cloud measurements in the Arctic. The response of clouds to the changing sea ice concentration was directly observed. Based on CALIPSO satellite observations of cloud properties, this study found that cloud coverage in ice-free regions in the Arctic linearly increased with the area of ice-free water during the melt seasons in the past 10 years, while sea ice coverage varies significantly year-to-year. The observations suggest that when sea-ice retreats, cloud fraction of the ice-free region remains fixed at nearly 81%. The high cloud coverage over melted areas significantly reduces the albedo feedback. These results indicate that space-based lidar cloud and surface observations of the Arctic can help constrain and improve climate models.

Relationship between Winter Precipitation in Barents–Kara Seas and September–October Eastern Siberian Sea Ice Anomalies

In this study, we applied the 1988–2017 monthly average sea ice concentration data from the Met Office Hadley Centre and the 1988–2017 monthly average reanalysis data from the National Centers for Environmental Prediction/Department of Energy (NCEP/DOE) Reanalysis II to analyze the relationship between the winter precipitation in the Barents and Kara Seas (BKS) and the previous autumn eastern Siberian Sea ice anomalies. Through the correlation analysis, we found that the correlation between eastern Siberian Sea ice and the BKS winter precipitation was strongest in September and weakest in November. The results indicated that, when the eastern Siberian Sea ice extent decreased in September–October, a significant positive geopotential height anomaly would occur in the coming winter (December–February) in the Norwegian–Barents region. This result in turn caused anomalies in the northward meridional wind. Consequently, the anomalous water vapor from the mid-latitude Atlantic to the Arctic passed through the Greenland Sea before finally reaching the BKS. The meridional wind also caused the temperature in said seas to increase and the BKS ice to melt, leading to an increase of winter precipitation. We also found that the increase of the Siberian high (SH) in winter was related to the decrease of autumn East Siberian Sea ice extent and the increase of the winter BKS precipitation anomaly. Further research still needs to be refined for this issue in future studies.

Disentangling the coupling between sea ice and tundra productivity in Svalbard

The rapid decline in Arctic sea ice poses urgent questions concerning its ecological effects, such as on tundra terrestrial productivity. However, reported sea ice/terrestrial productivity linkages have seldom been constrained, and the mechanism governing them remains elusive, with a diversity of spatial scales and metrics proposed, at times in contradiction to each other. In this study, we use spatially explicit remotely sensed sea ice concentration and high-resolution terrestrial productivity estimates (Normalised Difference Vegetation Index, NDVI) across the Svalbard Archipelago to describe local/sub-regional and large-scale components of sea ice/terrestrial productivity coupling. Whereas the local/sub-regional component is attributed to sea breeze (cold air advection from ice-covered ocean onto adjacent land during the growing season), the large-scale component might reflect co-variability of sea ice and tundra productivity due to a common forcing, such as large-scale atmospheric circulation (North Atlantic Oscillation, NAO). Our study clarifies the range of mechanisms in sea ice/terrestrial productivity coupling, allowing the generation of testable hypotheses about its past, present, and future dynamics across the Arctic.

Arctic sea ice melt leads to atmospheric new particle formation

Atmospheric new particle formation (NPF) and growth significantly influences climate by supplying new seeds for cloud condensation and brightness. Currently, there is a lack of understanding of whether and how marine biota emissions affect aerosol-cloud-climate interactions in the Arctic. Here, the aerosol population was categorised via cluster analysis of aerosol size distributions taken at Mt Zeppelin (Svalbard) during a 11 year record. The daily temporal occurrence of NPF events likely caused by nucleation in the polar marine boundary layer was quantified annually as 18%, with a peak of 51% during summer months. Air mass trajectory analysis and atmospheric nitrogen and sulphur tracers link these frequent nucleation events to biogenic precursors released by open water and melting sea ice regions. The occurrence of such events across a full decade was anti-correlated with sea ice extent. New particles originating from open water and open pack ice increased the cloud condensation nuclei concentration background by at least ca. 20%, supporting a marine biosphere-climate link through sea ice melt and low altitude clouds that may have contributed to accelerate Arctic warming. Our results prompt a better representation of biogenic aerosol sources in Arctic climate models.

Integrating physiology, behavior, and energetics: Biologging in a free-living arctic hibernator

The use of animal-borne instruments (ABIs), including biologgers and biotransmitters, has played an integral role in advancing our understanding of adjustments made by animals in their physiology and behavior across their annual and daily cycles and in response to weather and environmental change. Here, we review our research employing body temperature (Tb), light, and acceleration biologgers to measure patterns of physiology and behavior of a free-living, semi-fossorial hibernator, the arctic ground squirrel (Urocitellus parryii). We have used these devices to address a variety of physiological, ecological, and evolutionary questions within the fields of hibernation physiology, phenology, behavioral ecology, and chronobiology. We have also combined biologging with other approaches, such as endocrinology and tracking the thermal environment, to provide insights into the physiological mechanisms that underlie fundamental questions in biology including physiological performance trade-offs, timing and functional energetics. Finally, we explore the practical and methodological considerations that need to be addressed in biologging studies of free-living vertebrates and discuss future technological advancements that will increase the power and potential of biologging as a tool for assessing physiological function in dynamic and changing environments.