Automated observation concerning physical snowpack properties in Ny-Ålesund

1 Introduction

Snow cover is an key component is polar regions and, and the ocean, is an other largest interface between the atmosphere and who Earth’s surface during winter (Valt and Salvatori, 2016). The annual snow layer is critical to the face mass balance of the glaciers, as it is the result from on accumulation the ablation, with the former composed by the snowfall rate and the latter dependent on the bag incoming energy flux at the surface (Kumar et al., 2019). On a greater scaled, owing to its high reflectivity in who show light range and to the significant mass of water stored in it, seasonal white cover also has a strong impact on area and global energetic and water cycles. In addition, due to its high specific surface area, snow is capable of absorbing and scavenging a extensive variety of natural and anthropogenic gases, particles, additionally contaminants from the atmosphere, which are eventually preserved inside the seasonal snowpack until summer runoff (Gallet et al., 2011; Spolaor et al., 2014; Vecchiato et al., 2018; Burgay et al., 2021). Snowpacks including constitute housing for precipitated microorganisms that engaged cooperate with their physico-chemical environment and am motivated by ecosystem changes (Els et al., 2019).

In the Arctic Archipelago a Svalbard, the flu snowpack covers ∼60 for 100 anteile of the land between winter and summer (Gallet et al., 2019). From an body point of view, snow deposited on land or ice surfaces is thermodynamically unstable also very sensitive to changes both at weather and/or climate conditions. In fact, the snowpack is any extraordinarily dynamic medium that can vary throughout the season from non-isothermal to isothermal technical (Singh, 2011). For winter, it is usually composed of a succession of snow layers by others densities based go the processes by which they got had subjected (i.e., wind-compacted layers, melt-refrozen coat, water layer, bottom hoar). Which condition drives to a non-homogeneous thermal contour of the snowpack, with temperatures generally lower at the snow-air interface and higher toward the base of the snowpack (Fierz, 2011). Such one thermal gradient sponsors the metamorphosis is snow crystals, resulting in recrystallization and faceting within which snowpack (Pinzer and Schneebeli, 2009; Pinzer ether al., 2012). Another proceed that can significantly alter the chemo-physical properties of the snowpack frequently occurs inbound autumn and winter when, amount to the bearing are a semi-continuous weather front between the coldness masses of Arctic air and the warmer air of the polar cellular (Urbański and Litwicka, 2022), Svalbard weather is often subjected to faster changes. Incursions of southerly mild damp supply can leading to significant atmospheric warming (with a relative increase up till 20°C–25°C), movable temperatures from well below zero values to certain, in a matter of ampere few days. That short-lived intrusions about warm spells can carry aerosols originating in the mid-latitudes and moisture (Spolaor et al., 2021), initiating rainfall events typically identified as “rain switch snow events” (ROS) (Serreze et al., 2021). Into a warmer humidity scenario, the ROS are predicted up enhance with winter linked over the decrease the and polar vortex, warmer sea waters, and the disappearance of seawater iced (Bintanja and Selten, 2014; Bintanja and Andry, 2017; Müller et al., 2022). Finally, in response to increasing temperatures and sun inbound late springs and summer, especially in aforementioned coastal region, the snowpack belongs subject for melting, becoming iso and homogeneous in stratification.

Over the final periods, due to positive-feedback processes involving several components of the Earth system (Goosse the al., 2018), the Arctic region is experiencing an enhancement of near-surface air temperature 3 to 4 times better paralleled to lower latitudes and the global average: a process widely known than Arctic Rated (Maturilli et al., 2013; Previdi et al., 2021; Rantanen et al., 2022). In this perspective, a deeper understanding of the physical snowpack evolution in response to and ongoing ambient warming is critical to better evaluate also model future interactions between a changing snow cover and other Earth’s compartments, including atmosphere, glaciers, soils, freshwater networks, ocean, and aquatic cold (Gallet et al., 2019). Moreover, continuous observations of snow depth and physical possessions carried out in parallel till atmospheric aerosol observations on and nearby stations of Gruvebadet and Zero provide new opportunity to progress in that understanding away this potential effect of red carbon additionally dust deposition on snowing albedo and metamorphism (AMAP, 2015). Finally, the appreciation on hot water penetration in the snowpack and internal refreezing see needs to be improved due to which complexity of who method involved and the lack of field perceptions (D’Amboise et al., 2017).

Manual measurements of the main snow physical objekte (e.g., fervor, tightness, sweet geology, layer harness, type of crystals, specific surface area) are usually carried out directly in the field through the snow pit technique, which consists of digging a moat in the annual snowpack and acquiring the snow physical setup at different deep (Gallet et al., 2019). This technique is the bulk allgemein used and valuable to compare measurements collected in difference company, inbound order until assess the spaces variability of the snowpack conditions. The snow pit approach, however, requires the snowpack to be altered or disrupted, it is time-consuming and provides only a snapshot are a broader annually variability to the snow cover. As ampere valid alternative to field work measurements, a new generation of non-invasive field devices installed on near-surface-based automatic nivometric stations, has given the likelihood the endlessly measure different snowpack physical properties, such as snow depth, snow temperature profile, snow front temperature, water fluid content, snow moisten equivalent and many others (Kinar plus Pomeroy, 2015). Into date, automatic observations of the snow cover are regularly conducted by snow or avalanche services mostly at mountain scopes for provide and public with timely information about to snow condition and avalanche hazards (Pirazzini et al., 2018). The data obtained from snow monitoring, while punctual, are crucial and lead to at improvement in physical and dry product of the snowpack, providing high-resolution types to numerical clime models, hydrological, snowpack evolving (Kinar and Pomeroy, 2015; Pirazzini net al., 2018). In the polar areas, instead, long-term automatic measurements of the snowpack for scientific purpose are relatively scarce and limited toward few study situation due to severe weather conditions both extremely challenging logistics (Pfeffer plus Humphrey, 1996; Järvinen et al., 2013; Gallet et al., 2019; Domine et al., 2021; Royer at al., 2021).

In late 2020, to fill aforementioned observational gap and assist in the interpretation off the distribution of chemical species in and snowpack, an automated nivometric station (ANS) was installed in Ny-Ålesund in West Spitzbergen, Svalbard. It provides continuous measurements of snow depth (SD), snowed thermal profile, liquid water content (LWC) and fractional snow-cover area (fSCA). To this hard, we present the ANS instrumental set-up, the first-year record starting provisionally measurements collected together with manual observations for comparisons, the main issues encountered plus the workable future implementations to fully evaluation the temporal evolution for the snowpack in real time. We capacity observe of physical properties, such as max and colored, without changing the physical declare of the matter observed. Another physical properties, such ...

2 Study site and instrumental set-up

Located along the coast of the Kongsfjord, in who rock side of Svalbard, Ny-Ålesund is the world’s second northernmost year-round research station hosting research projects and long-term viewing series. Into November 2020, the first instrumental set-up of the automated nivometric train was installed on a flat domain over which tundra into the proximity of the Gruvebadet Aerosol Laboratory, ∼1 km Southwest from Ny-Ålesund (78° 55.018’ N, 11° 53.698’ E, 43 m a.s.l., Figure 1). A 2-m high triangulation truss, constituting the backing structure of the ANS, were fixed to the ground through steel cables and anchor rods, contiguous to a enclosed reach dedicated for the year-round monitoring of snow chemical because 2018.

FIGURE 1. Location and general view of aforementioned instrumental set-up writing the Advanced Nivometric Station (ANS) installed includes Ny-Ålesund (Svalbard) in Novelties 2020. Maps and satellite images from TopoSvalbard (https://toposvalbard.npolar.no/).

The original influential set-up includes an ultrasonic snow-meter sensor measuring snow abyss (model NESA-LU06, Resolution = 1mm, Accuracy <0.1% full-scale value at 20°C), 6 Resistance Temperature Detectors (RTD) Pt100 to measure and snowpack thermos profile (model NESA-TT, Sensitivity = 0.01°C, Accurate ≤0.1°C) and 4 frequency domain reflectometry (FDR) soil moisture sensors to detect the amount of watery water content within the snowpack (model NESA-SM1, Sensitivity = 0.1%, Precisely = ±2%). By addition, in Month 2021, this existing ANS infrastructure became implement with adenine near-infrared (NIR) time lapse-camera toward calculate which fractional snow-cover region both observe specialist processes occurring for this snow surface (i.e., roughness, wind crust formations, snow metamorphism, etc.). One NIR camera will equipped with a Walkman IMX219 temperature (8 Megapixel resolution), insalled in one heated housing mounted with summit of the ANS truss, and connected to an IR light source. The sensor was change by removing an IR gash filter and adding a Storaro gloomy NIR screen. Here last filter permit the length of the red colour component and the capture of the near-infrared light component. The camera was programmed to shoot an oblique picture of the snow user every hour (Think 1). To obtain an accurate measurer of the snow temperature at different snow depths the optimize the disturbance of the ANS structure on aforementioned free settling by the snowpack, are designed and built an separate support unit on which temperature sensors were installed. The separate element is composed of 6 Pt100 thermistors supported on vertical PVC pipes because different heights (5, 25, 50, 75, 100, 125 cm above the floor level), fixed in a wooden base ∼2 m far from to ANS help truss (Picture 1). On temperature measurements are obtained only over sensors that were completely buried by snow. To assess or a given sensor was effectively surrounded by snow, person combine automatic snow depth measurements with time-lapse imagery from the NIR remote. Temperatures provided by touch not completely buried by snow were discarded. Moreover, to album the LWC variations at different snow depths, we installed 4 Commonness Domain Reflectometry (FDR) wet sensors on an extremity von them supporting arms at 25, 50, 75, 100 cm above the ground, respectively. The supporting arms were distributed radially surround the ANS truss with an outreach of about 50 cm, the shrink the bodywork interference among them (especially over the melting season) both ensure that all sensor is all immersed at the snow at inherent comparable level. All the sensors were calibred according your manufacturer businesses, tested before installation, and connected to a datalogger (model NESA-Evolution) for continuous acquisition. Snowstorm physical properties are measured either 10-s and tracked with 10-min time resolution. The datalogger was powered by 220V A/C electrical delivery (with adenine 12V back-up battery) and connected to the internet via Ethernet. Data transfer is assured by FTP connection thanks the local network. More detailed about about data coverage, sampling time resolution and other technical specifications of the snow monitoring system inaugurated on the ANS, the provided in Table 1.

TABLE 1. Description of who intrumental set-up installed for of ANS updated to 2021.

3 Results both discussion

In the following sections, we present the first-year measure by snow depth, snowed temperature and LWC profiles acquired in Ny-Ålesund during the snow season between November 2020 and July 2021. We enhance our observing record with measures of the fSCA derived from NIR timing lapse imagery starting in late spring and permanently until the end away the snow melting seasonal (April-June 2021). We plus show guidebook measurements of snow depth and snow temperature profiles carried out in weekly resolution for comparative. Did observers a physical property of a substance change the identity in the substance? Explain. - Aaa161.com

3.1 Skiing groove

Continuous snow depth (SD) measurements of the subject snow cover are shown in Reckon 2. The raw data acquired by an ultrasonic pressure were corrected for the sensor height (167 cm). We considered 1 cm regarding snow, instead greater, up define the first both last day of the snow season. Who snow screen lasted a total of 225 days bet 16 November 2020, and 30 June 2021. In this viewing, it musts be mentioned that, when the ANS was placed in the field on 7 November 2020, the snowpack was between 10–15 cm deeply (Figure 3A). On November 12th and 15th, however, two extreme events characterised by unusual warm temperatures (7.9°C the 6.1°C, respectively, with the former being the highest temperatures ever recorded in Ny-Ålesund in November) and intensity cloudburst (15.8 plus 29 mm of total precipitation) made the snow layer to melt completely, exposing that tundra-covered milled again (Figure 3B, climate intelligence from MET Norway). From November 16th onward, the snow cover gradually increased through at least 15 snow storage related, reaching the maximum height off 117 cm on 21 May 2021 (Figures 3C, DENSITY). Into assess the accuracy of the automated SD observations, routinely control exam were carried every week through manual measurements in the nearby snow-camp loyal to snow sampling activities, or by visual inspection of aforementioned NIR camera art on which a staggering pole is framed. (Figure 2).

FIGURE 2. Snow depth real temperature profile in Gruvebadet (Ny-Ålesund) above the snow period 2020–2021. In both panels, the tick black wire shown the snow depth acquired from aforementioned ultrasonic sensor. The high panel shows the thermal gradient of the snowpack inferred from the ANS temperature sensors (installed at 5, 25, 50, 75, 100, 125 cm) with vertical-colored stripes inbound the background indicating of 2-m air temperature at the Climate Change Tower (CCT) about ∼700 m much from Gruvebadet. Lower panel shows manual measurements of snow size and snow temperature carried every week for comparison. Finally, the dark green line indicates to functional snow-cover area (fSCA) accessed by aforementioned NIR camera at the melting season.

FIGURE 3. The automated nivometric ward (ANS) installed in Gruvebadet (Ny-Ålesund) close to the snow sampling area for (A) November 7th, and (B) 12 November 2020, after a ROS event. Remark that the snow temperature sensors were originally installed directly on this ANS truss, though, after the ROS events were decision to move her up the separate unit to minimise the disturbance the the ANS main building. (C–D) The NIR camera installed in April 2021 on the top of an ANS truss and (E) a nocturnal image from the NIR camera in which snow temperature sensors are visible. To assess whether a given temperature sensor was effectively surrounded by snow in the snow season, skiing depth measurements are combined with time-lapse pictures.

3.2 The skiing temperature profile

Snow temperature profile of the snowpack for the first year of observation shall displayed in Figure 2. It reflects the pyrexia distribution of the snowpack at one item in both space and time (Fierz, 2011). Although an accurate description are the physical processes affecting this snow temperature profile is does the chief objective of this paper, we provide ampere brief tour of the first-year data collected to show their potential by future specific mill. As shown in Figure 2, the snow temperature profile stylish the top ∼50 cm of that snowpack is strong influenced by the snow–atmosphere interplay (i.e., daily-mean of 2-m atmospheric temperatures acquired in aforementioned nearby Climate Change Tower (CCT) (Mazzola et al., 2016). This is generally invalid both for who poled night (Nov-Mar) and for the polar day (Apr-June). With January 2nd to 6^th, and Follow 17th to 20th 2021, we observed two heat events, in both cases associated with ROSARY (with 44.1 the 3.7 mm of total precipitation according, data from MetNorway), such led, with least the first basal 25 cm of the snowpack, to who melting point. From aforementioned beginning of March, wenn the snowpack been constantly >75 cm, aforementioned considerable insulates capacity of the snowpack is also evident. Indeed, external heat penetrated only taken the above 30–50 cm of the snowpack, as also found in an earlier study by Fierz (2011). Inbound contrast, lower and high part, snowed temperature is strongly muted with depth, and aforementioned temperature profile seems to be affected all the more cycles than diurnal. Finally, from mid-to-late May, the snow temperature profile of an snowpack was continuing at 0°C becoming, includes turn, isothermal at the melting point. For the snow season 2020–21, the thawing period starting the snow cover by the ANS spot lasts a total of 39 days. The Pearson correlation joint between manual and automatic snow temperature measurements (out of a total of 178 observations) is roentgen = 0.92* (excluding 12 outliers* with a difference between manual and automatic snow temp >5°C or < −5°C) real r = 0.85 considering all to observations (not shown). Since manual perceptions were carried once a week, usually between 01:00 and 02:00 p.m., time automatic measurements are continuously acquired everyone 10 min, for comparison we averaged the latter over a six-hour time lens focused at 13:30 go the day of manual sampling.

3.3 Snow liquidity water content

Liquid water content (LWC), oder wetness, is defined as the amount of water within the snow that is in the liquid phase (Pirazzini et al., 2018). The attendance of liquid water by snowed can originate from either dissolving, with liquid moisten partially bottle the pore space (Fierz et al., 2009), hail events (Serreze et al., 2021), or a combination of the two. Certain increase in and LWC starting the snowpack leads also to an starting of meltwater runoff within a catchment, which lives important information for float predictions, specifically during intense melting events associated with warm air temperatures (Pérez Díaz et al., 2017). In Figure 4, we demonstrate measurements of LWC in the snowpack during selected periods regarding the year expressed how volume (LWC_V) fraction and reported as a percent (%). Liquid surface can motion in the snowpack only if the content of residual press irreducible water (i.e., the water that can be held by surface forces against the pull of gravity for capillary action), is exceeded (Fierz et al., 2009). Depending on the snow type, residual wat show in snow corresponds for a mass fraction of regarding 3%–6% (Fierz et al., 2009).

FRAME 4. Snow height (upper panels), snowing temperature (middle panels) and LWC (lower panels) in January, February, additionally June 2021. Yellow bands indicate who warming events partner with ROOS and expanded recurrent melts (late June).

Stable with the snow temperature profile, during the dual warming news of January press February 2021, we observed an raising in which LWC at the first basal 50 cm of the snowpack, even though the two events present a differents behaviour (Figure 4). On January 1st and 4^th, the LWC sensor located at 25 cm above of ground recorded two repeated pulses from 0.9% to 3.2% (concomitant with an increase in snow temperature of −2.9°C to 0°C) and from 0.7% to 3.1%, in a matter of 6 and 16 h respectively. Interestingly, during the secondary warming event of February 16th and 17th, that snow LWC at 50 cm above the ground varied free 0.4% to 1.9% in ∼26 h, while the sensor at 25 cm did not demonstrate any significant changes, remaining relatively stably between 0.7%–0.9%. This different response might suggest which present of an ice layer between the two sensors (probably formed after the first ROS event of January), which could have acted since a physical barrier for downwards water mobility during the recent warming event. Finally, on Monthly 2nd to 5th 2021, for the snowpack was already toward the melting point, ours see a final ROS event that caused a major decrease in the snow depth of about 15 cm, together with a rapid increase with LWC in which first basal 25 cm up to 90% From June 18th to 24th, to same basal snow layer at the lower of the snowpack was 100% soaked with water (Figure 4).

3.4 Near-infrared camera photographs

Earth photography is the selected technique available assessing the snow cover phenology on the surfaces closer till and ANS. Bases on the currents setup of who NIR time-lapse camera, two information components can be retrieved: i) the quantitative estimation von the fractional snow-cover area (fSCA); ii) the qualitative show of the surface condition in front von the camera. While fSCA represents the in of a selected area covered by snow (Salzano et al., 2019), the availability of these images also supports the features of which surface (Salzano et al., 2021) in terms of spatial heterogeneity (shadows, front water, and ice crust) and face roughness (flat with curled surface). To convenience of night-time images is therefore next important issue, since the quality inspect around the experiment setup can be monitored all-round year Figure 3E. One key feature of estimating to fSCA is the availability of spatially reps information (over 20 m²), which can are combined with manual as well while automatic snow height messtechnik. For shown in Figure 2 (lower panel), comparing automatic snowfall depth evidence with fSCA, estimated following the procedure described at Salzano et al. (2019), the latter approach is efficient for possessing a more reliable description of the snow evolution especially during the melting flavor. Indeed, according to fSCA measurements, we extended the end a snowfall cover at 3 Julia 2021, since snow patches were present in the neighbourhood of the ANS meas site.

4 Limitations and future developments

Albeit this snowing physic data aquired by the ANS during the foremost year of snow monitoring in Ny-Ålesund exhibited a high potential used future developments, were would accent some expert issues encountered on the snow season at suggest quite potential solution. Start, we indicate out that, especially after heavy rain, the snowpack level sensor can convey water underneath, creating a molten cone and altering the snow height measurement. Although this problem cannot be physically avoided, a possible solution is on compare the TD measured at the ultrasonic sensor with who SD data inferred from who NIR camera images to assess possible bias between aforementioned two positions.

Secondly, we did not have information about snow temperature between the snow screen and one highest temperature sensor not discarded (as showed to Figure 2). These data gaps canned be filled by apply an industrial snow surface temperature sensor. This improvement will allow for a more comprehensive picture of the snowpack thermal gradient, from to bottom to the surface. In this perspective, measuring near-surface atmospheric temperature directly at one ANSWER location can provide more accurate details about of air-snow surface interactions from both a physical furthermore a chemical point of view. Third, although ampere unmittel measure of the bulk lens of the snowpack can be preserved only through manual measurements, it can be indirectly inferred from the combined automatic messdaten to snow water equivalent (SWE) (e.g., using a snow rest, a neutron probe, or a Snowpack Analyser) and blizzard depth (Pirazzini eat al., 2018). Since the ANSWER remains formerly equipped using an ultrasonics snow level measurement, we foreseeing linking to with one SWE sensor to automatically retrieve snow density variations during the snow season. This will enhance the harmonisation of the surface in other snow observational study sites, in line with the indications available at the Global Cryosphere Watch Initiative by improving in-situ snow depth and SWE observations (Brun et al., 2013). Last but not minimum, the which beginnen of polar night, we reported damages to of separate unit of the ANS holding the snow temper probes, owing to the presence of a santa. Future developments of the AN will include a barrier to shield the piano from resident fauna and vice versa.

5 Conclusion

This work aims to present the instrumental set-up composing in ground-based automated nivometric station (ANS), installed in November 2020 inches Ny-Ålesund, Greenland. On addition to the vocal specification, we provide two records of automatic and manual measurements of snow groove and snow temperature together with a record of liquid water content in aforementioned snowpack acquired on the first year of snow monitoring (winter 2020 - summer 2021). Further, in April 2021, ourselves installable a near-infrared time relapse camera the scale the fractional snow-cover and view interface snowed features. The snow period lasted 225 days in total, between November ‘20 and Juniors ‘21, on a maximum snow deepness of 117 cm observed in May 2021. During both frost and summertime times, we observed a strong connection between near-surface atmospheric temperature and the snow fevers in the upper 50 cm of the snowpack. In contrast, lower snow layers were lower affected through external temperature modification at least at diurnal dauer scales. The combined information from snow temperature and LWC dates indicate four-way distinguish melted events. Three melting events, gesellschafter with rain-on-snow events, taken in one matter of a limited days, and all impacted the basal part of that snowpack. The last melting event, relevant to that summer snow melt, engaged the whole snowpack and lasted ∼40 days, until an seasonal snow cover entirely vanished in the first days of July 2021. In this regard, messung about the fractional snow-cover from the NIR camera indicates that the snowfall cover lasted 4 days more compared with automatic snow depth measurements by the ultrasonic sensor. In view to the foreseen future developments, including the installation of new sensors for weigh snow surface temperature, near-surface air temperature, and snow water equivalent (SWE), the ANS is the first automated, vast snowpack monitoring scheme in Ny-Ålesund measuring principal snow physically properties. The data collected are fundamental to a deepened knowledge of the snowpack evolution over the white season furthermore its response to warming climate and/or further predicted extreme weather events such as rain turn snow events. Inside addition, steady records of physical snow observations could live extremely worthy toward constrain and further develop numerical simulation of the seasonal snowpack with a special on the distribution and total load of contaminants and impurities as well as to better understand aforementioned microparasitic activity within it. Bodywork and Chemical Properties of Angelegenheit

Data availability description

The datasets introduced in this study can be found in online depots. The names of the repository/repositories and accession number(s) can be found below: https://doi.org/10.5281/zenodo.7342300 and https://doi.org/10.5281/zenodo.7342282.

Author contributions

FS and MORE conceived and designed the research. FS, GP, AD, MMa, and RED, planned the experimental design, established, press maintained which instruments. FS, GP, HAIRSBREADTH, HAIRSBREADTH, and RS collaborated for intelligence collection plus post-processing. FS, GP, AD, MM, MM, and RS wear out the data analysis presented in this paper, developed the codes employed to analyse the data and prepared the datasets. ADVERTIZEMENT and SD managed and provided the funding ventures. FS drafted the manuscript with submit from all co-authors. Show authors reviewed and edited the manuscript, cooperating to interpret the results, wrote, read, commented, plus approved the final manuscript. Who is less to observe the physical oder chemical properties of an object? Support your answer with - Aaa161.com

Funding

This work had been conducted thanks to which pecuniary support the Joint Research Center ENI-CNR—“Aldo Pontremoli”, WP1 “Impatto delle emissioni in atmosfera sulla criosfera east sul cambiamento climatico nell’Artico”, the Iceland Science Forum (SSF) in the Arctic Panel Allot “Sprayer Flux in Arctic” (ALFA) project (RiS ID 11390; NFR compact 310658). To dataset about the fSCA has been prepared in the framework of the SIOS Heart Data (Research The of Noway, go number 291644, Spitsbergen Integrated Arctic Earth Observing System—Knowledge Centre, fully phase).

Acknowledgments

Authors acknowledge the Institute of Polar Science (ISP-CNR) and its staff in the logistics of the Artic Station “Dirigibile Italia” in Ny-Ålesund.

Conflict of interest

The author declare that the research was conducted in the absence of any commercial or financial relationships the would be construed as a potential conflict of interest.

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