Time Of Snowfall Research Articles

Unveiling High Mountain Communities’ Perception of Climate Change Impact on Lives and Livelihoods in Gilgit-Baltistan: Evidence from People-Centric Approach

ABSTRACT Climate change poses a significant threat to the lives and livelihoods of the local communities in high mountain regions. This study examines the perception of climate change and its impact on the lives and livelihoods of high mountain communities in Gilgit-Baltistan. Empirical evidence was gathered through four focused group discussions and thirty in-depth interviews with the local communities in Darkut and Shishkat areas. This study found that the local communities perceive a noticeable change in temperature patterns in terms of an increase in average temperatures and shorter winters. Such changes lead to the melting of glaciers and subsequently frequent floods during summer. The communities argue that a decrease in snowfall and alterations in the timing of snowfall directly affect the region's water supply. These changes impact the region's key livelihood activities, such as livestock rearing and agriculture, leading to reduced productivity, and an increased reliance on external food sources. This study emphasizes the urgent need for community-based adaptation strategies and support for climate-resilient livelihoods in these regions. It underscores the importance of incorporating the perspectives and experiences of high mountain communities when formulating policies and strategies to address the multifaceted impacts of climate change in mountainous areas.

CONCEPT “SNOW” IN THE LINGUISTIC AND FOLKLORE PICTURE OF THE WORLD OF THE INDIGENOUS PEOPLES OF YAKUTIA

The article undertakes a comparative analysis of the concept “Snow” in the linguistic and folklore worldview of the indigenous peoples of Yakutia. The purpose of the study is to identify the specific features of representation of this concept in the linguistic and folklore worldview of the Yakuts, Evens, Evenki, Yukaghirs. The methods used in the paper include linguocultural analysis, continuous sampling, comparison and collation. Following the research of verbalisation of the concept “Snow”, it was revealed that it is universal and significant in the conceptual framework “Natural phenomena”. It was found that the concept “Snow” in the Yakut linguistic and folkloric world image represents a complex, multilayer formation going beyond the framework of natural phenomena, being capable of expressing figurative meanings involving negative connotations, when designating failure, loss of orientation, deception, tears, as well as measure, quantity, time; act as part of an anthroponym, etc. It was established that the most relevant features are the makeup, depth of snow, time of snowfall, etc., which is important in horse husbandry, cattle breeding and hunting. It was revealed that the concept “Snow” in the Even, Evenki and Yukaghir linguistic world image is presented mainly as a component of the concept “Natural phenomena”, characterising snow in terms of various qualitative, temporal and spatial attributes associated with reindeer breeding and hunting. The explored folklore materials reflecting the life of the Evens, Evenki, Yukaghirs showed that this concept serves mainly as a marker of winter onset, colour white, a component of everyday life activities, of time, sometimes of danger, transience. The work results can be used in the development of theoretical provisions of cultural linguistics, in comparative research of ethno-cultural features of the linguistic and folklore picture of the world of the indigenous peoples of Yakutia.

Synoptic control over winter snowfall variability observed in a remote site of Apennine Mountains (Italy), 1884–2015

Abstract. This work presents a new, very long snowfall time series collected in a remote site of Italian Apennine mountains (Montevergine Observatory, 1280 m above sea level). After a careful check, based on quality control tests and homogenization procedures, the available data (i.e. daily height of new snow) have been aggregated over winter season (December–February) to study the long-term variability for the period 1884–2020. The main evidence emerging from this analysis lies in (i) the strong interannual variability of winter snowfall amounts, (ii) the absence of a relevant trend from the late 19th century to the mid-1970s, (iii) the strong reduction in the snowfall amount and frequency of occurrence from the mid-1970s to the end of the 1990s and (iv) the increase in average snowfall amount and frequency of occurrence in the past 20 years. Moreover, this study shed light on the relationship between the snowfall variability observed in Montevergine and the large-scale atmospheric circulation. Six different synoptic types, describing the meteorological scenarios triggering the snow events in the study area, have been identified by means of a cluster analysis, using two essential atmospheric variables, the 500 hPa geopotential height and the sea level pressure (both retrieved from the third version of the Twentieth Century Reanalysis dataset, which is available for the 1884–2015 period). Such patterns trace out scenarios characterized by the presence of a blocking high-pressure anomaly over Scandinavia or the North Atlantic and by a cold air outbreak involving both maritime and continental cold air masses. A further analysis demonstrates that the identified synoptic types are strongly related with different teleconnection patterns, i.e. the Arctic Oscillation (AO), the Eastern Atlantic Western Russia (EAWR), the Eastern Mediterranean Pattern (EMP), the North Atlantic Oscillation (NAO) and the Scandinavian pattern (SCAND), that govern the European winter atmospheric variability. The relevant decline in snowfall frequency and amounts between the 1970s and 1990s can be mainly ascribed to the strong positive trend of AO and NAO indices, which determined, in turn, a decrease in the incidence of patterns associated with the advection, in central Mediterranean area, of moist and cold arctic maritime air masses. The recent increase in average snowfall amounts can be explained by the reverse trend of the AO index and by the prevalence of a neutral or negative EAWR pattern.

Hydronic Road-Heating Systems: Environmental Performance and the Case of Ingolstadt Ramps

Abstract Snowfall and ice formation on road surface significantly impact the safety of driving conditions. To resolve this, every year salt and de-icing chemicals are sprinkled on roads. However, use of salts and snow ploughing have environmental as well as economical disadvantages. To resolve these problems, hydronic road heating systems are valid alternatives. Heat transfer fluid, i.e. mixture of ethanol and water, is pumped into a tubular circulation system under the asphalt. By this technology, the road and pavements shall stay ice-free even in times of snowfall and temperatures below the freezing point. The system can also be used to cool the asphalt in case of extreme heat, which – besides the heating effect – could also prevent road from damages in extreme summers. This study aims to compare the environmental impact of use of salts and road-heating system in terms of GHG emissions. To assess the environmental impact, an operational road heating system for a ramp in Ingolstadt, Germany, is considered. A cradle-to-grave analysis technique is used to determine the environmental effects based on a life-cycle assessment (LCA) framework. The analysis includes nine components solemnly responsible for hydronic heating of asphalt surface such as local heating pipe, insulation, pumps, and heat meters. Comparison is performed in terms of relative and total impact over 50-year lifetime of three heated ramps having 1989 m2 surface area in total. The results show that the asphalt and heating-circuit causes the major fraction (65 %) of overall GHG emissions, with total life-time emissions of 28.10 kg CO2 eq./m2 of heated surface. During an operational life of 50 years, road heating systems emit 18 % less CO2 eq./m2 as compared to the use of salts.

Modelling climate change impact on water resources of the Upper Indus Basin

Abstract Climate change has implications for water resources by increasing temperature, shifting precipitation patterns and altering the timing of snowfall and glacier melt, leading to shifts in the seasonality of river flows. Here, the Soil & Water Assessment Tool was run using downscaled precipitation and temperature projections from five global climate models (GCMs) and their multi-model mean to estimate the potential impact of climate change on water balance components in sub-basins of the Upper Indus Basin (UIB) under two emission (RCP4.5 and RCP8.5) and future (2020–2050 and 2070–2100) scenarios. Warming of above 6 °C relative to baseline (1974–2004) is projected for the UIB by the end of the century (2070–2100), but the spread of annual precipitation projections among GCMs is large (+16 to −28%), and even larger for seasonal precipitation (+91 to −48%). Compared to the baseline, an increase in summer precipitation (RCP8.5: +36.7%) and a decrease in winter precipitation were projected (RCP8.5: −16.9%), with an increase in average annual water yield from the nival–glacial regime and river flow peaking 1 month earlier. We conclude that predicted warming during winter and spring could substantially affect the seasonal river flows, with important implications for water supplies.

Assessing the importance of bi-directional melting when modeling boreal peatland freeze/thaw dynamics

The modeling of seasonal ground ice (SGI) freeze/thaw a common feature in boreal peatlands, has often been completed using a unidirectional approach, where melting is driven by energy inputs from the surface. However, bi-directional melt is known to occur, and can potentially increase the spring melt rate. Accurate modelling of the timing of ice-free conditions in peatlands is important because SGI can impede spring infiltration and lead to substantial spring snowmelt runoff from peatlands. However, when modelling melt only from above, erroneous results in the model estimation of ice-free conditions can occur, which can lead to knock on-effects for modelling peatland hydrological function. Furthermore, as the climate warms, it is unclear how this role of SGI may change in the future. This study used the Stefan Equation to model unidirectional and bi-directional melt to assess which performed better in modelling the timing of ice-free conditions compared to observed values (BI: 3.9 ± 2.1 days, UNI: 9.0 ± 4.7). Including bi-directional melt improved model performance by reducing this difference by approximately 5 days. Model performance for SGI freeze/thaw cycles were similar, with BI being slightly more accurate in freezing (RMSE:2.7 cm versus 3.3 cm) and melting (RMSE: 2.6 cm vs 3.7 cm) compared to the unidirectional approach. While the model improvement in the timing of ice-free conditions was substantial, careful consideration is needed in determining when a peatland is functionally ice free in future modelling studies. The Stefan Equation was found to be most sensitive to changes in soil moisture, compared to ground surface temperature and peat porosity, likely due to the relationship between thermal conductivity and frozen and liquid water content. Comparisons with future climate change projections suggest that the timing of ice-free conditions could shift by as much as 2 weeks earlier in the 2050′s and by almost a month earlier in the 2080′s. However, the timing of snowfall, and rain on snow events continues to be a source of model uncertainty. Future studies should work to investigate the potential positive feedbacks this could create. In conclusion, the Stefan Equation presents a relatively easy path for incorporating bi-directional melt into peatland models. This process should be included in peatland ecohydrological models in order to properly model the timing of melt and ice-free conditions.

Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images

Mountain regions have experienced above-average warming in the 20th century and this trend is likely to continue. These accelerated temperature changes in alpine areas are causing reduced snowfall and changes in the timing of snowfall and melt. Snow is a critical component of alpine areas - it drives hibernation of animals, determines the length of the growing season for plants and the soil microbial composition. Thus, changes in snow patterns in mountain areas can have serious ecological consequences. Here we use 35 years of Landsat satellite images to study snow changes in the Mocho-Choshuenco Volcano in the Southern Andes of Chile. Landsat images have 30 m pixel resolution and a revisit period of 16 days. We calculated the total snow area in cloud-free Landsat scenes and the snow frequency per pixel, here called “snow persistence” for different periods and seasons. Permanent snow cover in summer was stable over a period of 30 years and decreased below 20 km2 from 2014 onward at middle elevations (1,530–2,000 m a.s.l.). This is confirmed by negative changes in snow persistence detected at the pixel level, concentrated in this altitudinal belt in summer and also in autumn. In winter and spring, negative changes in snow persistence are concentrated at lower elevations (1,200–1,530 m a.s.l.). Considering the snow persistence of the 1984–1990 period as a reference, the last period (2015–2019) is experiencing a −5.75 km2 reduction of permanent snow area (snow persistence > 95%) in summer, −8.75 km2 in autumn, −42.40 km2 in winter, and −18.23 km2 in spring. While permanent snow at the high elevational belt (>2,000 m a.s.l.) has not changed through the years, snow that used to be permanent in the middle elevational belt has become seasonal. In this study, we use a probabilistic snow persistence approach for identifying areas of snow reduction and potential changes in alpine vegetation. This approach permits a more efficient use of remote sensing data, increasing by three times the amount of usable scenes by including images with spatial gaps. Furthermore, we explore some ecological questions regarding alpine ecosystems that this method may help address in a global warming scenario.

윈드쉴드 와이퍼 강설 시험법 연구

Purpose: I propse a method to test a wiper system in snowfall. I conducted a field test on user conditions and vehicle design conditions. After that, I suggest developing a wiper system that meets domestic standards.<BR>Methods: I analyzed the user conditions by condecting a survey. Moreover, I analyzed the characteristics using the reappearance test of the vehicle’s exterior design. I defined snow type to be used while reproducing snowfall and suggest how to reproduce the snow using a chamber.<BR>Result: The amount of snow accumulation depends on the design conditions of the vehicle. The amount can be different for the same vehicle depending on the type of snow. Moreover, snow accumulation was found to be different for different heater usage conditions.<BR>Conclusion: Is able to apply user condition that add condition of using heater for automobile. Also able to apply vehicle design condition. I recommend to use during snow density of 0.3g/cm³. And would control capacity of water. Using chamber recommend to soaking of 30℃ more than 4 hours. Determining test time that using safety factor, time of snowfall per year, average of vehicle velocity, average of driving time, heavy snow warning standard of domestic mountain area.

Assessing Multi-Temporal Snow-Volume Trends in High Mountain Asia From 1987 to 2016 Using High-Resolution Passive Microwave Data

High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.

Permafrost thermal conditions are sensitive to shifts in snow timing

Changes in snow precipitation at high latitudes can significantly affect permafrost thermal conditions and thaw depth, potentially exposing more carbon-laden soil to microbial decomposition. A fully coupled process-based surface/subsurface thermal hydrology model with surface energy balance is used to analyze the impact of intra-annual variability in snow on permafrost thermal regime and the active layer thickness. In the four numerical scenarios considered, simulations were forced by the same meteorological data, except the snow precipitation, which was systematically altered to change timing of snowfall. The scenarios represent subtle shifts in snow timing, but the snow onset/melt days, the end of winter snowpack depth, and total annual snow precipitation are unchanged among scenarios. The simulations show that small shifts in the timing of snow accumulation can have significant effects on subsurface thermal conditions leading to active layer deepening and even talik formation when snowfall arrives earlier in the winter. The shifts in snow timing have a stronger impact on wetter regions, especially soil underneath small ponds, as compared to drained regions. This study highlights the importance of understanding potential changes in winter precipitation patterns for reliable projections of active-layer thickness in a changing Arctic climate.

Análisis multi-criterio sobre barreras biogeográficas para la movilidad humana en Patagonia meridional

Much of the discussion on the human biogeography of the lake system south of Lago Argentino (southern Patagonia) has been focused on the “dead ends”, near the Andean lakes, its link with continental ice as an important barrier to human movement, and the Baguales Range immediately to the east. Other minor barriers were discussed recently. Among the latter, here we add the plateaus, their edges and the small fluvial valleys at the foot of the plateaus locally called ensenadas or "inlets". The methodology includes a least-cost pathways analysis based on multi-criteria cost surfaces, a hierarchical spatial model based on landscape resistance to human circulation, the use of GIS (Geographic Information Systems) tools and remote sensing techniques on satellite images. A scheme of priority and alternative pathways is derived, whose availability and potential spatial disconnections at times of snowfall, reinforce the logistical exploitation of the area. Thus, the key to the intensity of human occupation in this sector has very likely been linked to the increase or decrease of costs movements, also articulated with land-use strategies centered on other ecologically complementary spaces.

Snow Depth Estimation on Slopes Using GPS-Interferometric Reflectometry.

Snow is one of the most critical sources of freshwater, which influences the global water cycle and climate change. However, it is difficult to monitor global snow variations with high spatial–temporal resolution using traditional techniques due to their costly and labor-intensive nature. Nowadays, the Global Positioning System Interferometric Reflectometry (GPS-IR) technique can measure the average snow depth around a GPS antenna using its signal-to-noise ratio (SNR) data. Previous studies focused on the use of GPS data at sites located in flat areas or on very gentle slopes. In this contribution, we propose a strategy called the Tilted Surface Strategy (TSS), which uses the SNR data reflected only from the flat quadrants to estimate the snow depth instead of the conventional strategy, which employs all the SNR data reflected from the whole area around a GPS antenna. Three geodetic GPS sites from the Plate Boundary Observatory (PBO) project were chosen in this experimental study, of which GPS sites p683 and p101 were located on slopes with their gradients up to 18% and the site p025 was located on a flat area. Comparing the snow depths derived with the GPS-IR TSS method with the snow depth results provided with the GPS-PBO, i.e., GPS-IR with the conventional strategy, the Snowpack Telemetry (SNOTEL) network measurements and gridded Snow Data Assimilation System (SNODAS) estimates, it was found that the snow depths derived with the four methods had a good agreement, but the snow depth time series with the GPS-IR TSS method were closer to the SNOTEL measurements and the SNODAS estimates than those with GPS-PBO method. Similar observations were also obtained from the cumulative snowfall time series. Results generally indicated that for those GPS sites located on slopes, the TSS strategy works better.

Understanding Spatio-temporal Pattern of Grassland Phenology in the western Indian Himalayan State

The present study has analysed grassland phenology: start of greening (SOG), end of greening (EOG) and length of greening (LOG), and their rate of change in the western Himalaya in India (Himachal Pradesh) using MODIS NDVI time series data (2001–2015). These metrics were inspected at different stratification levels: state, elevation, climatic zones and bio-geographic provinces. Delayed SOG was observed over 44.87% (P < 0.1), and delayed EOG over 63.3% (P < 0.1) of grassland grids. LOG was shortened in 24.37% (P < 0.1) and extended in 58.04% (P < 0.1) of the grids. At the state level, when statistically significant pixels (SSP) and all the pixels (AP) are used (given as SSP:AP), SOG is delayed by 20.27:6.28 days year−15, while EOG is delayed by 38.02:14.97 days year−15 and LOG is extended by 35.07:8.70 year−15 days. Extended LOG is observed over the temperate and cold arid regions, and shortened LOG is observed over sub-alpine and alpine regions. Variations in SOG and EOG are not uniform across different climatic and bio-geographic regions. However, in the sub-alpine and alpine zones, SOG and EOG followed elevation gradients, i.e. late SOG with early EOG over higher elevations, and early SOG with late EOG over lower elevations. Our study has revealed an interesting pattern of translational phenology (i.e. late SOG and late EOG) of grasslands which hints towards shifting winter period. Overall, it is observed that variations in timing of snowfall and snow cover extent are the reasons for inter-annual variations in the grassland phenology.

Climatic and environmental signals recorded in the EGRIP snowpit, Greenland

Polar ice sheets conserve atmospheric mineral dust (aerosols) at the time of snowfall, and this material can be used to reconstruct historical climate and environmental conditions. Snowpit samples were obtained from the East Greenland Ice Core Project (EGRIP) site in July 2017. Mineral dust concentrations as well as stable water isotope (δ18O, δD, and deuterium excess) and major ion (F−, Cl−, $${\text{NO}}_{2}^{-}$$ , $${\text{NO}}_{3}^{-}$$ , $${\text{SO}}_{4}^{2-}$$ , methanesulfonic acid (MSA), Na+, $${\text{NH}}_{\text{4}}^{\text{+}}$$ , Mg2+ and Ca2+) concentrations were analyzed in this study. The seasonal δ18O and δD cycles indicate that the snowpit samples covered the period from winter 2012 to summer 2017. The concentrations of mineral dust and Ca2+ showed seasonal deposition events with maxima in the spring layers. The concentrations of MSA exhibited maxima in the summer layers, making them useful indicators for the summer season. Moreover, an anomalous non-sea salt $${\text{SO}}_{4}^{2-}$$ (nss $${\text{SO}}_{4}^{2-}$$ ) event was recorded at a depth of 130 − 85 cm that corresponded to the Holuhraun eruption (31 August 2014). In addition, a significant short-term cooling effect was observed. A back-trajectory analysis suggests that a major ash event from Iceland contributed to the Greenland ice sheet (GrIS). These results provide insight for future studies of the EGRIP ice core.

Multifractal Analysis of Snowfall Recorded Using a 2D Video Disdrometer

Abstract Universal multifractal (UM) analysis was used to investigate the scaling properties of snowfall at high temporal and spatial resolutions. Snowfall data were recorded using a 2D video disdrometer (2DVD) in the Swiss Alps. Six 1-h-long periods of snowfall, half in calm and half in light wind conditions, were selected for analysis. UM analysis was performed on reconstructed 35-m vertical columns of snowfall structure, snowfall time series at 100-ms resolution, and two-dimensional snowflake accumulation maps over a 5.12 5.12 cm2 area. Multifractal scaling was observed for the vertical structure of snow particle number concentration, for scales between about 35 and 4.4 m, and sometimes down to about 0.5 m. At smaller scales, no scaling was observed. In high-resolution time series of snowfall, evidence of scaling was found for scales between about 7 min and ~26 s in most of the analyzed hours. Snowflake accumulations within a subset of the small sampling area of the 2DVD showed no scaling properties, suggesting homogeneous structure in snowfall at the very small (~5 cm) scale, which agrees with the results for vertical structure and time series.

Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation

AbstractAccurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze‐thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers, the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Timely and effective soil thermal forecast, constrained through data assimilation that combines process‐based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.

Avalanche and Falling Rock Measurement Using Piezoelectric Dynamics and Static Sensors

Under certain weather conditions, avalanches can occur because of snow cover on a steep slope. Such avalanches can reach snow fences that are arranged as countermeasures. Furthermore, traffic is completely blocked when fences collapse and snow falls on a road. Therefore, prediction of avalanche occurrence is important, but such predictions are considered difficult. To resolve this difficulty, this study assessed measurement of the danger degree by measuring the risk to the avalanche fence at the time of snowfall and falling rock according to changes in the load and the impact of voltage proportional to the avalanche barrier deformation. This measurement system has fixed sensors attached with mounting brackets to a dedicated avalanche prevention measurement fence. It measures the pressure and vibration measurement of the snowfall at the time of avalanche or rock fall occurrence at the main structure of the fence. Furthermore, this fence made of lumber from thinned timber is useful as a defensive barrier countermeasure against avalanches and falling rock. It is designed to withstand a snow load of 3–5 [t / m²] during an avalanche.

Mineral dust and major ion concentrations in snowpit samples from the NEEM site, Greenland

Polar ice sheets conserve atmospheric aerosols at the time of snowfall, which can be used to reconstruct past climate and environmental conditions. We investigated mineral dust and major ion records in snowpit samples obtained from the northwestern Greenland ice sheet near the North Greenland Eemian Ice Drilling (NEEM) camp in June 2009. We analyzed the samples for mineral dust concentrations as well as stable water isotopes (δ18O, δD, and deuterium excess) and major ions (Cl−, SO42-, methanesulfonic acid (MSA), Na+, and Ca2+). Seasonal δ18O and δD cycles indicate that the snowpit samples covered a six-year period from spring 2003 to early summer 2009. Concentrations of mineral dust, nss-Ca2+, and nss-SO42- showed seasonal deposition events with maxima in the winter–spring layers. On the other hand, the Cl−/Na+ ratio and the concentrations of MSA exhibited maxima in the summer layers, making them useful indicators for the summer season. Moreover, an anomalous atmospheric mineral dust event was recorded at a depth of 165–170 cm corresponding to late winter 2005 to spring 2006. A back trajectory analysis suggests that a major contributor to the Greenland aerosol was an air mass passing over the Canadian Arctic and North America. Several trajectories point to Asian regions as a dust source. The mineral dust deposited at NEEM was strongly influenced by long-range atmospheric transport and dust input from arid source areas in northern China and Mongolia.

Measuring soil frost depth in forest ecosystems with ground penetrating radar

Soil frost depth in forest ecosystems can be variable and depends largely on early winter air temperatures and the amount and timing of snowfall. A thorough evaluation of ecological responses to seasonally frozen ground is hampered by our inability to adequately characterize the frequency, depth, duration and intensity of soil frost events. We evaluated the use of ground penetrating radar to nondestructively delineate soil frost under field conditions in three forest ecosystems. Soil frost depth was monitored periodically using a 900MHz antenna in South Burlington, Vermont (SB), Sleepers River Watershed, North Danville, Vermont (SR) and Hubbard Brook Experimental Forest, New Hampshire (HBEF) during winter 2011–2012 on plots with snow and cleared of snow. GPR-based estimates were compared to data from thermistors and frost tubes, which estimate soil frost depth with a color indicating solution. In the absence of snow, frost was initially detected at a depth of 8–10cm. Dry snow up to 35cm deep, enhanced near-surface frost detection, raising the minimum frost detection depth to 4–5cm. The most favorable surface conditions for GPR detection were bare soil or shallow dry snow where frost had penetrated to the minimum detectable depth. Unfavorable conditions included: standing water on frozen soil, wet snow, thawed surface soils and deep snow pack. Both SB and SR were suitable for frost detection most of the winter, while HBEF was not. Tree roots were detected as point reflections and were readily discriminated from continuous frost reflections. The bias of GPR frost depth measurements relative to thermistors was site dependent averaging 0.1cm at SB and 1.1cm at SR, and was not significantly different than zero. When separated by snow manipulation treatment at SR, overestimation of soil frost depth (5.5cm) occurred on plots cleared of snow and underestimation (−1.5cm) occurred on plots with snow. Despite some limitations posed by site and surface suitability, GPR could be useful for adding a spatial component to pre-installed soil frost monitoring networks.

Snowfall time-series reconstruction in Italy over the last 300 years

Snow events are not a rare episode in Mediterranean area, especially in northern and hilly areas of Italy. However, snowfall occurring quasi-simultaneously in the whole peninsula is extraordinary. This study collects, reconstructs, and analyzes the extraordinary snowfall episodes that occurred simultaneously in the whole Italian peninsula since 1709. This is the longest snowfall time series in the central Mediterranean area. The data, obtained by several documentary sources (from ancient archival to online databases), have been analyzed using different statistical tests, in order to explore normality, homogeneity, and stationarity. The results are characterized by a time-series stationarity with a quasi 60- and 100-year-dominant oscillation. No clear trend in the snowfall episode records is found. The 60-year cycle roughly matches with global-scale oscillations linked to natural forces, such as the Atlantic Multidecadal Oscillation and the winter North Atlantic Oscillation. Particular attention was directed to analyze the impact of snowfall on pre-industrial society, underlining the differences among northern and central regions, where snow was a more usual phenomenon, and its impact was mainly on transports of supplies or exceptionally on buildings, and southern regions, where it had a stronger impact also on orchards and cattle.