Arctic Sites Research Articles

Applying Machine Learning and Time-Series Analysis on Sentinel-1A SAR/InSAR for Characterizing Arctic Tundra Hydro-Ecological Conditions

Synthetic aperture radar (SAR) is a widely used tool for Earth observation activities. It is particularly effective during times of persistent cloud cover, low light conditions, or where in situ measurements are challenging. The intensity measured by a polarimetric SAR has proven effective for characterizing Arctic tundra landscapes due to the unique backscattering signatures associated with different cover types. However, recently, there has been increased interest in exploiting novel interferometric SAR (InSAR) techniques that rely on both the amplitude and absolute phase of a pair of acquisitions to produce coherence measurements, although the simultaneous use of both intensity and interferometric coherence in Arctic tundra image classification has not been widely tested. In this study, a time series of dual-polarimetric (VV, VH) Sentinel-1 SAR/InSAR data collected over one growing season, in addition to a digital elevation model (DEM), was used to characterize an Arctic tundra study site spanning a hydrologically dynamic coastal delta, open tundra, and high topographic relief from mountainous terrain. SAR intensity and coherence patterns based on repeat-pass interferometry were analyzed in terms of ecological structure (i.e., graminoid, or woody) and hydrology (i.e., wet, or dry) using machine learning methods. Six hydro-ecological cover types were delineated using time-series statistical descriptors (i.e., mean, standard deviation, etc.) as model inputs. Model evaluations indicated SAR intensity to have better predictive power than coherence, especially for wet landcover classes due to temporal decorrelation. However, accuracies improved when both intensity and coherence were used, highlighting the complementarity of these two measures. Combining time-series SAR/InSAR data with terrain derivatives resulted in the highest per-class F1 score values, ranging from 0.682 to 0.955. The developed methodology is independent of atmospheric conditions (i.e., cloud cover or sunlight) as it does not rely on optical information, and thus can be regularly updated over forthcoming seasons or annually to support ecosystem monitoring.

Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatiotemporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network's representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N) EC sites, which has also been made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain based on 18 bioclimatic and edaphic variables. This allows us to assess a general level of similarity between ecosystem conditions within the domain, while not necessarily reflecting changes in greenhouse gas flux rates directly. We define two metrics based on this representativeness score: one that measures whether a location is represented by an EC tower with similar characteristics (ER1) and a second for which we assess if a minimum level of representation for statistically rigorous extrapolation is met (ER4). We find that while half of the domain is represented by at least one tower, only a third has enough towers in similar locations to allow reliable extrapolation. When we consider methane measurements or year-round (including wintertime) measurements, the values drop to about 1/5 and 1/10 of the domain, respectively. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as underrepresented. Across the Arctic, mountainous regions were particularly poorly represented by the current EC observation network. We tested three different strategies to identify new site locations or upgrades of existing sites that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 %, upgrading as few as 10 existing sites to capture methane fluxes or remain active during wintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.

Unique high Arctic methane metabolizing community revealed through in situ 13CH4-DNA-SIP enrichment in concert with genome binning

Greenhouse gas (GHG) emissions from Arctic permafrost soils create a positive feedback loop of climate warming and further GHG emissions. Active methane uptake in these soils can reduce the impact of GHG on future Arctic warming potential. Aerobic methane oxidizers are thought to be responsible for this apparent methane sink, though Arctic representatives of these organisms have resisted culturing efforts. Here, we first used in situ gas flux measurements and qPCR to identify relative methane sink hotspots at a high Arctic cytosol site, we then labeled the active microbiome in situ using DNA Stable Isotope Probing (SIP) with heavy 13CH4 (at 100 ppm and 1000 ppm). This was followed by amplicon and metagenome sequencing to identify active organisms involved in CH4 metabolism in these high Arctic cryosols. Sequencing of 13C-labeled pmoA genes demonstrated that type II methanotrophs (Methylocapsa) were overall the dominant active methane oxidizers in these mineral cryosols, while type I methanotrophs (Methylomarinovum) were only detected in the 100 ppm SIP treatment. From the SIP-13C-labeled DNA, we retrieved nine high to intermediate quality metagenome-assembled genomes (MAGs) belonging to the Proteobacteria, Gemmatimonadetes, and Chloroflexi, with three of these MAGs containing genes associated with methanotrophy. A novel Chloroflexi MAG contained a mmoX gene along with other methane oxidation pathway genes, identifying it as a potential uncultured methane oxidizer. This MAG also contained genes for copper import, synthesis of biopolymers, mercury detoxification, and ammonia uptake, indicating that this bacterium is strongly adapted to conditions in active layer permafrost and providing new insights into methane biogeochemical cycling. In addition, Betaproteobacterial MAGs were also identified as potential cross-feeders with methanotrophs in these Arctic cryosols. Overall, in situ SIP labeling combined with metagenomics and genome binning demonstrated to be a useful tool for discovering and characterizing novel organisms related to specific microbial functions or biogeochemical cycles of interest. Our findings reveal a unique and active Arctic cryosol microbial community potentially involved in CH4 cycling.

Microfluidics Microbial Activity MicroAssay: An Automated In Situ Microbial Metabolic Detection System.

With no direct extant-life detection instrumentation included in a space mission since the 1970s, the advancement of new technologies to be included in future space missions is imperative. We developed, optimized, and tested a semi-automated prototype, the microfluidics Microbial Activity MicroAssay (μMAMA). This system metabolically characterizes and detects extant microbial life by way of metabolism-indicator redox dyes. We first evaluated the robustness and sensitivity of six redox dye/buffer combinations, and we then tested their responses to metabolic activity in astrobiological analog high-Arctic samples. We determined that the Biolog Inoculating Fluid (IF)-C and AlamarBlue buffered in IF-0a (aB-IF0a) dye/buffer combinations were optimal, as they detected metabolic activity from the fewest microbial cells (102 cells/mL) while maintaining efficacy over a broad physiochemical range of pH (0-13), temperature (-10°C to 37°C), salinity and perchlorate (tested up to 30%), and in the presence of a Mars regolith simulant (MMS-2). The μMAMA, which incorporated these redox dyes, detected extant active cold-adapted microbial life from high Arctic analog sites, including samples amended with substrates targeting chemolithoautotrophic metabolisms. Given μMAMA's small size (we estimate a complete planetary instrument could occupy as little as 3 L) and potential for automation, it could easily be incorporated into almost any landed platform for life detection missions.

Multi-year, spatially extensive, watershed-scale synoptic stream chemistry and water quality conditions for six permafrost-underlain Arctic watersheds

Abstract. Repeated sampling of spatially distributed river chemistry can be used to assess the location, scale, and persistence of carbon and nutrient contributions to watershed exports. Here, we provide a comprehensive set of water chemistry measurements and ecohydrological metrics describing the biogeochemical conditions of permafrost-affected Arctic watersheds. These data were collected in watershed-wide synoptic campaigns in six stream networks across northern Alaska. Three watersheds are associated with the Arctic Long-Term Ecological Research site at Toolik Field Station (TFS), which were sampled seasonally each June and August from 2016 to 2018. Three watersheds were associated with the National Park Service (NPS) of Alaska and the U.S. Geological Survey (USGS) and were sampled annually from 2015 to 2019. Extensive water chemistry characterization included carbon species, dissolved nutrients, and major ions. The objective of the sampling designs and data acquisition was to characterize terrestrial–aquatic linkages and processing of material in stream networks. The data allow estimation of novel ecohydrological metrics that describe the dominant location, scale, and overall persistence of ecosystem processes in continuous permafrost. These metrics are (1) subcatchment leverage, (2) variance collapse, and (3) spatial persistence. Raw data are available at the National Park Service Integrated Resource Management Applications portal (O'Donnell et al., 2021, https://doi.org/10.5066/P9SBK2DZ) and within the Environmental Data Initiative (Abbott, 2021, https://doi.org/10.6073/pasta/258a44fb9055163dd4dd4371b9dce945).

Effects of Arctic Wetland Dynamics on Tower-Based GNSS Reflectometry Observations

A tower-based global navigation satellite system reflectometry (GNSS-R) experiment is set up in an Arctic wetland environment for investigating the possibility of monitoring wetland inundation and freeze/thaw (FT) dynamics which are additionally impacted by snow on the ground. Effects of inundation, snow cover, and soil FT state on observed GNSS-R signal-to-noise ratios (SNRs) are analyzed for horizontal (H) and vertical (V) polarizations. A simple classification approach is suggested to detect the inundated, frozen, or thawed soil state. A simple forward reflectivity model is formulated to evaluate the influence of snow cover, overlying frozen, or thawed soil, on the reflected GNSS signals. Reflectivity time series are simulated in H- and V-polarizations using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> observations of the Arctic wetland site. The simulations are used to verify the tower-based observations, which show a significant impact of wet snow on reflectivity during melting conditions in spring. The observed SNR is strongly correlated with the Sentinel-1 backscatter coefficient. Generally, soil states detected by GNSS-R are in high agreement with ground truth soil states, especially for inundated and frozen soils. Wet snow conditions, however, complicate the correct timing estimation of soil thawing by inducing reflectivities of a similar order as thawing soil. It is recommended that GNSS-R land application models and retrieval algorithms consider snow cover effects to reduce false classification, especially in FT detection. Overall, the outcome of this study is relevant to the upcoming ESA HydroGNSS mission.

Life-history attributes of Arctic-breeding birds drive uneven responses to environmental variability across different phases of the reproductive cycle.

Animals exhibit varied life‐history traits that reflect adaptive responses to their environments. For Arctic‐breeding birds, traits related to diet, egg nutrient allocation, clutch size, and chick growth are predicted to be under increasing selection pressure due to rapid climate change and increasing environmental variability across high‐latitude regions. We compared four migratory birds (black brant [Branta bernicla nigricans], lesser snow geese [Chen caerulescens caerulescens], semipalmated sandpipers [Calidris pusilla], and Lapland longspurs [Calcarius lapponicus]) with varied life histories at an Arctic site in Alaska, USA, to understand how life‐history traits help moderate environmental variability across different phases of the reproductive cycle. We monitored aspects of reproductive performance related to the timing of breeding, reproductive investment, and chick growth from 2011 to 2018. In response to early snowmelt and warm temperatures, semipalmated sandpipers advanced their site arrival and bred in higher numbers, while brant and snow geese increased clutch sizes; all four species advanced their nest initiation dates. During chick rearing, longspur nestlings were relatively resilient to environmental variation, whereas warmer temperatures increased the growth rates of sandpiper chicks but reduced growth rates of snow goose goslings. These responses generally aligned with traits along the capital‐income spectrum of nutrient acquisition and altricial–precocial modes of chick growth. Under a warming climate, the ability to mobilize endogenous reserves likely provides geese with relative flexibility to adjust the timing of breeding and the size of clutches. Higher temperatures, however, may negatively affect the quality of herbaceous foods and slow gosling growth. Species may possess traits that are beneficial during one phase of the reproductive cycle and others that may be detrimental at another phase, uneven responses that may be amplified with future climate warming. These results underscore the need to consider multiple phases of the reproductive cycle when assessing the effects of environmental variability on Arctic‐breeding birds.

Water Vapour Assessment Using GNSS and Radiosondes over Polar Regions and Estimation of Climatological Trends from Long-Term Time Series Analysis

The atmospheric humidity in the Polar Regions is an important factor for the global budget of water vapour, which is a significant indicator of Earth’s climate state and evolution. The Global Navigation Satellite System (GNSS) can make a valuable contribution in the calculation of the amount of Precipitable Water Vapour (PW). The PW values retrieved from Global Positioning System (GPS), hereafter PWGPS, refer to 20-year observations acquired by more than 40 GNSS geodetic stations located in the polar regions. For GNSS stations co-located with radio-sounding stations (RS), which operate Vaisala radiosondes, we estimated the PW from RS observations (PWRS). The PW values from the ERA-Interim global atmospheric reanalysis were used for validation and comparison of the results for all the selected GPS and RS stations. The correlation coefficients between times series are very high: 0.96 for RS and GPS, 0.98 for RS and ERA in the Arctic; 0.89 for RS and GPS, 0.97 for RS and ERA in Antarctica. The Root-Mean-Square of the Error (RMSE) is 0.9 mm on average for both RS vs. GPS and RS vs. ERA in the Arctic, and 0.6 mm for RS vs. GPS and 0.4 mm for RS vs. ERA in Antarctica. After validation, long-term trends, both for Arctic and Antarctic regions, were estimated using Hector scientific software. Positive PWGPS trends dominate at Arctic sites near the borders of the Atlantic Ocean. Sites located at higher latitudes show no significant values (at 1σ level). Negative PWGPS trends were observed in the Arctic region of Greenland and North America. A similar behaviour was found in the Arctic for PWRS trends. The stations in the West Antarctic sector show a general positive PWGPS trend, while the sites on the coastal area of East Antarctica exhibit some significant negative PWGPS trends, but in most cases, no significant PWRS trends were found. The present work confirms that GPS is able to provide reliable estimates of water vapour content in Arctic and Antarctic regions too, where data are sparse and not easy to collect. These preliminary results can give a valid contribution to climate change studies.

Improved ELMv1-ECA simulations of zero-curtain periods and cold-season CH&amp;lt;sub&amp;gt;4&amp;lt;/sub&amp;gt; and CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emissions at Alaskan Arctic tundra sites

Abstract. Field measurements have shown that cold-season methane (CH4) and carbon dioxide (CO2) emissions contribute a substantial portion to the annual net carbon emissions in permafrost regions. However, most earth system land models do not accurately reproduce cold-season CH4 and CO2 emissions, especially over the shoulder (i.e., thawing and freezing) seasons. Here we use the Energy Exascale Earth System Model (E3SM) land model version 1 (ELMv1-ECA) to tackle this challenge and fill the knowledge gap of how cold-season CH4 and CO2 emissions contribute to the annual totals at Alaska Arctic tundra sites. Specifically, we improved the ELMv1-ECA soil water phase-change scheme, environmental controls on microbial activity, and the methane module. Results demonstrate that both soil temperature and the duration of zero-curtain periods (i.e., the fall period when soil temperatures linger around 0 ∘C) simulated by the updated ELMv1-ECA were greatly improved; e.g., the mean absolute error (MAE) in zero-curtain durations at 12 cm depth was reduced by 62 % on average. Furthermore, the MAEs of simulated cold-season carbon emissions at three tundra sites were improved by 72 % and 70 % on average for CH4 and CO2, respectively. Overall, CH4 emitted during the early cold season (September and October), which often includes most of the zero-curtain period in Arctic tundra, accounted for more than 50 % of the total emissions throughout the entire cold season (September to May) in the model, compared with around 49.4 % (43 %–58 %) in observations. From 1950 to 2017, both CO2 emissions during the zero-curtain period and during the entire cold season showed increasing trends, for example, of 0.17 and 0.36 gC m−2 yr−1 at Atqasuk. This study highlights the importance of zero-curtain periods in facilitating cold-season CH4 and CO2 emissions from tundra ecosystems.

The effect of the 2020 COVID-19 lockdown on atmospheric black carbon levels in northeastern Greenland

The outbreak of SARS-CoV-2 and subsequent spread of the disease COVID-19 became classified as a pandemic in March of 2020, leading to global safety measures introduced to limit the impact of the virus. This combination of safety measures has become commonly referred to as “lockdown”. The associated industry and lifestyle changes led to reductions in the anthropogenic emission of atmospheric pollutants such as black carbon (BC), which is transported from the mid-latitudes into the Arctic during the winter and spring. Measurements of BC and other anthropogenic pollutants are of increasing importance in the Arctic due to the rapid warming observed there in the past few decades. It is believed that BC has a significant role in this warming, and so understanding the Arctic's response to reduced BC emissions at lower latitudes will provide insight into how future changes might mitigate further warming. Reductions in BC have been reported worldwide, and so in this study, the impact of these reductions on BC concentrations at the High Arctic site Villum Research Station was investigated. The effect was examined from March 2020, around when global lockdowns began, to June 2020, when the Arctic haze period ended and BC levels were once again low. Firstly, the Danish Eulerian Hemispheric Model (DEHM) was used to assess this impact on BC concentrations by adjusting global anthropogenic pollution emission inventories to simulate those observed during the lockdown period and comparing the results to a similar model run with standard emission inventories. Secondly, equivalent BC data from an aethalometer at Villum Research Station were analysed, comparing the concentrations during the lockdown period to both aethalometer data from previous years and DEHM results from the lockdown period. It was found that when adjusted DEHM emission inventories were introduced from the 1st of March, the model predicted a reduction in BC concentrations beginning on the 10th of March and reached a 10% reduction by the 1st of April. This reduction fluctuated around 10% until the end of the Arctic haze period. Aethalometer data did not show any significant change from previous years, and no concentration reduction could be concluded from its comparison with DEHM results. This is likely because the predicted reduction of 10% is smaller than both the inter-annual and intra-annual variability of measured BC concentrations at Villum.

Properties of Cirrus Clouds over the European Arctic (Ny-Ålesund, Svalbard)

Cirrus is the only cloud type capable of inducing daytime cooling or heating at the top of the atmosphere (TOA) and the sign of its radiative effect highly depends on its optical depth. However, the investigation of its geometrical and optical properties over the Arctic is limited. In this work the long-term properties of cirrus clouds are explored for the first time over an Arctic site (Ny-Ålesund, Svalbard) using lidar and radiosonde measurements from 2011 to 2020. The optical properties were quality assured, taking into account the effects of specular reflections and multiple-scattering. Cirrus clouds were generally associated with colder and calmer wind conditions compared to the 2011–2020 climatology. However, the dependence of cirrus properties on temperature and wind speed was not strong. Even though the seasonal cycle was not pronounced, the winter-time cirrus appeared under lower temperatures and stronger wind conditions. Moreover, in winter, geometrically- and optically-thicker cirrus were found and their ice particles tended to be more spherical. The majority of cirrus was associated with westerly flow and westerly cirrus tended to be geometrically-thicker. Overall, optically-thinner layers tended to comprise smaller and less spherical ice crystals, most likely due to reduced water vapor deposition on the particle surface. Compared to lower latitudes, the cirrus layers over Ny-Ålesund were more absorbing in the visible spectral region and they consisted of more spherical ice particles.

Estimates of mass absorption cross sections of black carbon for filter-based absorption photometers in the Arctic

Abstract. Long-term measurements of atmospheric mass concentrations of black carbon (BC) are needed to investigate changes in its emission, transport, and deposition. However, depending on instrumentation, parameters related to BC such as aerosol absorption coefficient (babs) have been measured instead. Most ground-based measurements of babs in the Arctic have been made by filter-based absorption photometers, including particle soot absorption photometers (PSAPs), continuous light absorption photometers (CLAPs), Aethalometers, and multi-angle absorption photometers (MAAPs). The measured babs can be converted to mass concentrations of BC (MBC) by assuming the value of the mass absorption cross section (MAC; MBC= babs/ MAC). However, the accuracy of conversion of babs to MBC has not been adequately assessed. Here, we introduce a systematic method for deriving MAC values from babs measured by these instruments and independently measured MBC. In this method, MBC was measured with a filter-based absorption photometer with a heated inlet (COSMOS). COSMOS-derived MBC (MBC (COSMOS)) is traceable to a rigorously calibrated single particle soot photometer (SP2), and the absolute accuracy of MBC (COSMOS) has been demonstrated previously to be about 15 % in Asia and the Arctic. The necessary conditions for application of this method are a high correlation of the measured babs with independently measured MBC and long-term stability of the regression slope, which is denoted as MACcor (MAC derived from the correlation). In general, babs–MBC (COSMOS) correlations were high (r2= 0.76–0.95 for hourly data) at Alert in Canada, Ny-Ålesund in Svalbard, Barrow (NOAA Barrow Observatory) in Alaska, Pallastunturi in Finland, and Fukue in Japan and stable for up to 10 years. We successfully estimated MACcor values (10.8–15.1 m2 g−1 at a wavelength of 550 nm for hourly data) for these instruments, and these MACcor values can be used to obtain error-constrained estimates of MBC from babs measured at these sites even in the past, when COSMOS measurements were not made. Because the absolute values of MBC at these Arctic sites estimated by this method are consistent with each other, they are applicable to the study of spatial and temporal variation in MBC in the Arctic and to evaluation of the performance of numerical model calculations.

The Effect of Soil on the Summertime Surface Energy Budget of a Humid Subarctic Tundra in Northern Quebec, Canada

AbstractRising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux.

Studies of relative contributions of internal gravity waves and 2‐D turbulence to tropospheric and lower‐stratospheric temporal wind spectra measured by a network of VHF windprofiler radars using a decade‐long data set in Canada

AbstractTropospheric and lower‐stratospheric motions at mesoscales and larger are a mixture of waves and two‐dimensional (2‐D) turbulence. Determining their relative importance is necessary, since waves are capable of coordinated systematic momentum transport accompanying the wave propagation, and associated wind forcing, in ways that 2‐D turbulence is not. This can impact weather forecasting. Using a network of ten windprofiler radars in eastern Ontario and western Quebec in Canada, plus an additional one in the Arctic, the relative roles of internal gravity (buoyancy) waves and two‐dimensional turbulence are examined at temporal scales from about 3–4 hrs to several tens of hours (horizontal spatial scales of typically one or two hundred kilometres to a few thousand kilometres), with the purpose of investigating the respective roles of these two distinct characteristic fluid motions as functions of location, season and year. The emphasis is on studies of spectral slope variability, rather than absolute spectral magnitudes, giving a perspective not previously substantially presented. In particular, we have found a frequency band in which gravity‐wave Doppler shifting produces distinctly different spectral slopes than those predicted for 2‐D turbulence, and these differences are employed to distinguish the flow fields. The network used (excluding the Arctic site) covers an area of ∼106 km2 and includes a variety of different terrains. Radial velocities have been recorded on time scales of minutes for data lengths covering durations of up to 12 years. Altitude coverage is from 1 km to typically 14 km, at 500 m resolution. Results suggest a region from ∼2 to ∼5 km altitude (deeper for some radars) where waves are weaker and 2‐D turbulence appears to be generally more significant, but where occasional bursts of gravity‐wave activity can occur, while above typically 6–8 km, gravity waves increase in significance. There are distinct site‐to‐site variations.

Variation in body size of ringed seals (Pusa hispida hispida) across the circumpolar Arctic: evidence of morphs, ecotypes or simply extreme plasticity?

The ringed seal is a small phocid seal that has a northern circumpolar distribution. It has long been recognized that body size is variable in ringed seals, and it has been suggested that ecotypes that differ in size exist. This study explores patterns of body size (length and girth) and age-at-maturity across most of the Arctic subspecies’ range using morphometric data from 35 sites. Asymptotic lengths varied from 113 to 151 cm, with sites falling into five distinct size clusters (for each sex). Age-at-maturity ranged from 3.1 to 7.4 years, with sites that had early ages of sexual maturity generally having small length-at-maturity and small final body length. The sexes differed in length at some sites, but not in a consistent pattern of dimorphism. The largest ringed seals occurred in western Greenland and eastern Canada, and the smallest occurred in Alaska and the White Sea. Latitudinal trends occurred only within sites in the eastern Canadian Arctic. Girth (with length and season accounted for) was also highly variable but showed no notable spatial pattern; males tended to be more rotund than females. Genetic studies are needed, starting with the “giants” at Kangia (Greenland) and in northern Canada to determine whether they are genetically distinct ecotypes. Additional research is also needed to understand the ecological linkages that drive the significant regional size differences in ringed seals that were confirmed in this study, and also to understand their implications with respect to potential adaptation to climate change.

Classification of the frozen/thawed surface state of Northern land areas based on SMAP and GCOM-W1 brightness temperature observations at 1.4 GHz and 6.9 GHz

ABSTRACT In this letter, the method created earlier by the authors and the information product SPL3FTP_E of the Soil Moisture Active Passive (SMAP) satellite for determining frozen/thawed state of soil surface on the example of test sites placed on North Slope of Alaska, U.S.A., Canada, Finland and Russian Federation were compared. As an indicator of the frozen/thawed state of soil surface, the polarization index calculated on the basis of the reflectivity of soils was proposed. The soil reflectivity was determined in the L-band based on the SMAP radiometric observations at a frequency of 1.4 GHz using the values of brightness temperatures measured by the Global Change Observation Mission – Water 1/Advanced Microwave Scanning Radiometer 2 (GCOM-W1/AMSR2) at a vertical polarization and a frequency of 6.9 GHz, as an estimate of the soil effective temperature. As a result, it was shown that the developed method makes it possible to increase accuracy of the frozen/thawed states determination of soil surface from 3% to 9% in relation to the SMAP data (SPL3FTP_E) for twelve Arctic test sites.

Meteorological, snow and soil data (2013–2019) from a herb tundra permafrost site at Bylot Island, Canadian high Arctic, for driving and testing snow and land surface models

Abstract. Seasonal snow covers Arctic lands 6 to 10 months of the year and is therefore an essential element of the Arctic geosphere and biosphere. Yet, even the most sophisticated snow physics models are not able to simulate fundamental physical properties of Arctic snowpacks such as density, thermal conductivity and specific surface area. The development of improved snow models is in progress, but testing requires detailed driving and validation data for high Arctic herb tundra sites, which are presently not available. We present 6 years of such data for an ice-wedge polygonal site in the Canadian high Arctic, in Qarlikturvik valley on Bylot Island at 73.15∘ N. The site is on herb tundra with no erect vegetation and thick permafrost. Detailed soil properties are provided. Driving data are comprised of air temperature, air relative and specific humidity, wind speed, shortwave and longwave downwelling radiation, atmospheric pressure, and precipitation. Validation data include time series of snow depth, shortwave and longwave upwelling radiation, surface temperature, snow temperature profiles, soil temperature and water content profiles at five depths, snow thermal conductivity at three heights, and soil thermal conductivity at 10 cm depth. Field campaigns in mid-May for 5 of the 6 years of interest provided spatially averaged snow depths and vertical profiles of snow density and specific surface area in the polygon of interest and at other spots in the valley. Data are available at https://doi.org/10.5885/45693CE-02685A5200DD4C38 (Domine et al., 2021). Data files will be updated as more years of data become available.

A global study of hygroscopicity-driven light-scattering enhancement in the context of other in situ aerosol optical properties

Abstract. The scattering and backscattering enhancement factors (f(RH) and fb(RH)) describe how aerosol particle light scattering and backscattering, respectively, change with relative humidity (RH). They are important parameters in estimating direct aerosol radiative forcing (DARF). In this study we use the dataset presented in Burgos et al. (2019) that compiles f(RH) and fb(RH) measurements at three wavelengths (i.e., 450, 550 and 700 nm) performed with tandem nephelometer systems at multiple sites around the world. We present an overview of f(RH) and fb(RH) based on both long-term and campaign observations from 23 sites representing a range of aerosol types. The scattering enhancement shows a strong variability from site to site, with no clear pattern with respect to the total scattering coefficient. In general, higher f(RH) is observed at Arctic and marine sites, while lower values are found at urban and desert sites, although a consistent pattern as a function of site type is not observed. The backscattering enhancement fb(RH) is consistently lower than f(RH) at all sites, with the difference between f(RH) and fb(RH) increasing for aerosol with higher f(RH). This is consistent with Mie theory, which predicts higher enhancement of the light scattering in the forward than in the backward direction as the particle takes up water. Our results show that the scattering enhancement is higher for PM1 than PM10 at most sites, which is also supported by theory due to the change in scattering efficiency with the size parameter that relates particle size and the wavelength of incident light. At marine-influenced sites this difference is enhanced when coarse particles (likely sea salt) predominate. For most sites, f(RH) is observed to increase with increasing wavelength, except at sites with a known dust influence where the spectral dependence of f(RH) is found to be low or even exhibit the opposite pattern. The impact of RH on aerosol properties used to calculate radiative forcing (e.g., single-scattering albedo, ω0, and backscattered fraction, b) is evaluated. The single-scattering albedo generally increases with RH, while b decreases. The net effect of aerosol hygroscopicity on radiative forcing efficiency (RFE) is an increase in the absolute forcing effect (negative sign) by a factor of up to 4 at RH = 90 % compared to dry conditions (RH &lt; 40 %). Because of the scarcity of scattering enhancement measurements, an attempt was made to use other more commonly available aerosol parameters (i.e., ω0 and scattering Ångström exponent, αsp) to parameterize f(RH). The majority of sites (75 %) showed a consistent trend with ω0 (higher f(RH = 85 %) for higher ω0), while no clear pattern was observed between f(RH = 85 %) and αsp. This suggests that aerosol ω0 is more promising than αsp as a surrogate for the scattering enhancement factor, although neither parameter is ideal. Nonetheless, the qualitative relationship observed between ω0 and f(RH) could serve as a constraint on global model simulations.

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

AbstractA melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. These findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.

Temperature and spatial connectivity drive patterns in freshwater macroinvertebrate diversity across the Arctic

Abstract Warming in the Arctic is predicted to change freshwater biodiversity through loss of unique taxa and northward range expansion of lower latitude taxa. Detecting such changes requires establishing circumpolar baselines for diversity, and understanding the primary drivers of diversity. We examined benthic macroinvertebrate diversity using a circumpolar dataset of &gt;1,500 Arctic lake and river sites. Rarefied α diversity within catchments was assessed along latitude and temperature gradients. Community composition was assessed through region‐scale analysis of β diversity and its components (nestedness and turnover), and analysis of biotic–abiotic relationships. Rarefied α diversity of lakes and rivers declined with increasing latitude, although more strongly across mainland regions than islands. Diversity was strongly related to air temperature, with the lowest diversity in the coldest catchments. Regional dissimilarity was highest when mainland regions were compared with islands, suggesting that connectivity limitations led to the strongest dissimilarity. High contributions of nestedness indicated that island regions contained a subset of the taxa found in mainland regions. High Arctic rivers and lakes were predominately occupied by Chironomidae and Oligochaeta, whereas Ephemeroptera, Plecoptera, and Trichoptera taxa were more abundant at lower latitudes. Community composition was strongly associated with temperature, although geology and precipitation were also important correlates. The strong association with temperature supports the prediction that warming will increase Arctic macroinvertebrate diversity, although low diversity on islands suggests that this increase will be limited by biogeographical constraints. Long‐term harmonised monitoring across the circumpolar region is necessary to detect such changes to diversity and inform science‐based management.