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1.
To better assess the spatiotemporal variations of the snow shielding effect on surface exposure dating, we compiled a dataset of 1341 10Be ages from alpine moraines and glacially eroded valleys across western North America, and conducted a sensitivity test with both modern and time-integrated snow data covering the same region. Our analyses reveal significant differences in snow shielding both across our geographic domain and through time. In our time-integrated experiments we find snow-based exposure age corrections as low as 3.5% in the Great Basin region and high as 28.4% in the Pacific Northwest for samples dating to the Last Glacial Maximum (LGM) when no wind-sweeping is assumed. As demonstrated with our time-varying snow conditions with a global climate model and a positive degree day model, modern snow conditions across western North America cannot account for the varying snow patterns under large scale climate shifts since the LGM. The snow-based exposure age corrections from the modern data differ from those calculated by our time-varying model by up to 17% across our model domain. In addition, we find that the 10Be ages calculated under two end-member scenarios regarding wind-sweeping effects, specifically whether boulders were shielded only when the total snow accumulation exceeded boulder heights or were always shielded when the snow was present, can differ by ∼7.6% on average for LGM aged samples. Our analyses provide a model-based estimates of the spatiotemporal variability and complexity of snow shielding effects on surface exposure dates across western North America and highlight the need to consider snow depth variations both spatially and temporally when conducting surface exposure dating in terrains where snowfall accumulation is significant.  相似文献   

2.
The net surface snow accumulation on the Antarctic ice sheet is determined by a combination of precipitation, sublimation and wind redistribution. We present a one-year record of hourly snow-height measurements at LGB69 (70°50'S, 77°04'E, 1850 m a.s.l.). east side of Lambert Glacier basin (LGB), and 4 year record at G3 (70°53'S, 69°52'E, 84 m a.s.l.), Amery Ice Shelf (AIS). The measurements were made with ultrasonic sensors mounted on automatic weather stations installed at two sites. The snow accumulation at LGB69 is approximately 70 cm. Throughout the winter, between April and September, there was little change in surface snow height (SSH) at the two sites. The negative SSH change is due to densification at LGB69, and is due to both ablation and densification at G3. The strongest accumulation at two sites occurred during the period between October and March (accounting for 101.6% at LGB69), with four episodic increasing events occurring during 2002 for LGB69, and eight events during 1999-2002 for G  相似文献   

3.
Transportation, sublimation and accumulation of snow dominate snow cover development in the Arctic and produce episodic high evaporative fluxes. Unfortunately, blowing snow processes are not presently incorporated in any hydrological or meteorological models. To demonstrate the application of simple algorithms that represent blowing snow processes, monthly snow accumulation, relocation and sublimation fluxes were calculated and applied in a spatially distributed manner to a 68-km2 catchment in the low Arctic of north-western Canada. The model uses a Landsat-derived vegetation classification and a digital elevation model to segregate the basin into snow ‘sources’ and ‘sinks’. The model then relocates snow from sources to sinks and calculates in-transit sublimation loss. The resulting annual snow accumulation in specific landscape types was compared with the result of intensive surveys of snow depth and density. On an annual basis, 28% of annual snowfall sublimated from tundra surfaces whilst 18% was transported to sink areas. Annual blowing snow transport to sink areas amounted to an additional 16% of annual snowfall to shrub–tundra and an additional 182% to drifts. For the catchment, 19·5% of annual snowfall sublimated from blowing snow, 5·8% was transported into the catchment and 86·5% accumulated on the ground. The model overestimated snow accumulation in the catchment by 6%. The application demonstrates that winter precipitation alone is insufficient to calculate snow accumulation and that blowing snow processes and landscape patterns govern the spatial distribution and total accumulation of snow water equivalent over the winter. These processes can be modelled by relatively simple algorithms, and, when distributed by landscape type over the catchment, produce reasonable estimates of snow accumulation and loss in wind-swept regions. © 1997 John Wiley & Sons, Ltd.  相似文献   

4.
In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km2). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.  相似文献   

5.
The small scale distribution of the snowpack in mountain areas is highly heterogeneous, and is mainly controlled by the interactions between the atmosphere and local topography. However, the influence of different terrain features in controlling variations in the snow distribution depends on the characteristics of the study area. As this leads to uncertainties in high spatial resolution snowpack simulations, a deeper understanding of the role of terrain features on the small scale distribution of snow depth is required. This study applied random forest algorithms to investigate the temporal evolution of snow depth in complex alpine terrain using as predictors various topographical variables and in situ snow depth observations at a single location. The high spatial resolution (1 m x 1 m) snow depth distribution database used in training and evaluating the random forests was derived from terrestrial laser scanner (TLS) devices at three study sites, in the French Alps (2 sites) and the Spanish Pyrenees (1 site). The results show the major importance of two topographic variables, the topographic position index and the maximum upwind slope parameter. For these variables the search distances and directions depended on the characteristics of each site and the TLS acquisition date, but are consistent across sites and are tightly related to main wind directions. The weight of the different topographic variables on explaining snow distribution evolves while major snow accumulation events still take place and minor changes are observed after reaching the annual snow accumulation peak. Random forests have demonstrated good performance when predicting snow distribution for the sites included in the training set with R2 values ranging from 0.82 to 0.94 and mean absolute errors always below 0.4 m. Oppositely, this algorithm failed when used to predict snow distribution for sites not included in the training set, with mean absolute errors above 0.8 m.  相似文献   

6.
Blowing snow events control the evolution of the snow pack in mountainous areas and cause inhomogeneous snow distribution. The goal of this study is to identify the main features of blowing snow events at an alpine site and assess the ability of the detailed snowpack model Crocus to reproduce the occurrence of these events in a 1D configuration. We created a database of blowing snow events observed over 10 years at our experimental site. Occurrences of blowing snow events were divided into cases with and without concurrent falling snow. Overall, snow transport is observed during 10.5% of the time in winter and occurs with concurrent falling snow 37.3% of the time. Wind speed and snow age control the frequency of occurrence. Model results illustrate the necessity of taking the wind-dependence of falling snow grain characteristics into account to simulate periods of snow transport and mass fluxes satisfactorily during those periods. The high rate of false alarms produced by the model is investigated in detail for winter 2010/2011 using measurements from snow particle counters.  相似文献   

7.
Collecting spatially representative data over large areas is a challenge within snow monitoring frameworks. Identifying consistent trends in snow accumulation properties enables increased sampling efficiency by minimizing field collection time and/or remote sensing costs. Seasonal snowpack depth estimations during mid-winter and melt onset conditions were derived from airborne Lidar over the West Castle Watershed in the southern Canadian Rockies on three dates. Each dataset was divided into five sets of snow depth driver classes: elevation, aspect, topographic position index, canopy cover and slope. Datasets were quality controlled by eliminating snow depth values above the 99th percentile value, which had a negligible effect on average snow depths. Consistent trends were observed among driver classes with peak snow accumulation occurring within the treeline ecotone, north-facing aspects, open canopies, topographic depressions and areas with low slope angle. Although mid-winter class trends for each driver were similar and watershed-scale snow depth distributions were significantly correlated (0.76, p < .01), depth distributions within the same driver class of the three datasets were not correlated due to recent snowfall events, redistribution and settling processes. Trends in driver classes during late season melt onset were similar to mid-winter conditions but watershed scale distribution correlation results varied with seasonality (0.68 mid-winter 2014 and melt onset 2016; 0.65 mid-winter 2017 and melt onset 2016, p < .1). This is due to the differing stages of accumulation or ablation and the upward migration in the 0°C isotherm during spring, when snow depth can be declining in valley bottoms while still increasing at higher elevations. The observed consistency in depth driver controls can be used to guide future integrated snow monitoring frameworks.  相似文献   

8.
Snow samples were taken from a 5-m-deep pit located near the South Pole station in January 1975 and continuous deuterium, tritium and β activity profiles have been obtained from them. These three measurements and the stratigraphic observations allow us to deduce a precise chronology of the pit from 1950 to 1975, providing a continuous record of artificial tritium fallout in the southern hemisphere; this record has been extended to 1978 using samples from a second pit taken this last year. Taking advantage of the unusual 1957–1958 stable isotope content in the snow, we have demonstrated that an important part of the isotopic signal in the precipitation is retained in the snow in spite of the low accumulation rate (8.2 g cm?2 yr?1).The first artificial tritium, due to the 1952 Ivy experiments was detected during 1954. A two-year delay between explosions and fallout is well established and allows us to relate the tritium fallout to the main nuclear tests from 1952 to 1960. This delay appears longer for the large 1961–1962 devices. A stratospheric half residence time equal to 20 months is deduced from the fallout decrease occurring after the 1966 peak. For the French southern hemisphere experiments, it is about one year. A sharp tritium decrease is observed after a high 1973 peak, providing a new tritium reference level for future glaciological studies in Antarctica.The β and tritium peaks occur respectively during the Antarctic summer and the Antarctic winter, showing different injection mechanisms. This winter input and the high tritium values registered at the South Pole indicate a preferential tritium transfer over the pole area. Two mechanisms, stratospheric-tropospheric exchange and direct stratospheric cloud precipitation could account for this injection.  相似文献   

9.
ABSTRACT

We present a new model extension for the Water balance Simulation Model, WaSiM, which features (i) snow interception and (ii) modified meteorological conditions under coniferous forest canopies, complementing recently developed model extensions for particular mountain hydrological processes. Two study areas in Austria and Germany are considered in this study. To supplement and constrain the modelling experiments with on-site observations, a network of terrestrial time-lapse cameras was set up in one of these catchments. The spatiotemporal patterns of snow depth inside the forest and at the adjacent open field sites were recorded along with snow interception dynamics. Comparison of observed and modelled snow cover and canopy interception indicates that the new version of WaSiM reliably reconstructs the variability of snow accumulation for both the forest and the open field. The Nash-Sutcliffe efficiency computed for selected runoff events in spring increases from ?0.68 to 0.71 and 0.21 to 0.87, respectively.  相似文献   

10.
The Antarctic ice sheet is the main sink for atmospheric pollution reaching the Antarctic atmosphere from other continents. The ice preserves a historical record of the atmosphere that can be recovered in ice cores. No increasing trend is observed over recent decades for nitrate and sulphate. There appears to have been an increase of perhaps eight-fold in lead concentrations in Antarctic snow, but the details of when the increase occurred have still to be defined. Many other species could be measured, but analytical problems have hampered such work. These studies would be impaired if emissions due to human activity in Antarctica became significant. The effect on snow concentrations of emissions from fuel and waste burning at Antarctic stations and from vehicles is still mainly confined to small areas around stations.  相似文献   

11.
We analyse spatial variability and different evolution patterns of snowpack in a mixed beech–fir stand in the central Pyrenees. Snow depth and density were surveyed weekly along six transects of contrasting forest cover during a complete accumulation and melting season; we also surveyed a sector unaffected by canopy cover. Forest density was measured using the sky view factor (SVF) obtained from digital hemispherical photographs. During periods of snow accumulation and melting, noticeable differences in snow depth and density were found between the open site and those areas covered by forest canopy. Principal component analysis provided valuable information in explaining these observations. The results indicate a high variability in snow accumulation within forest areas related to differences in canopy density. Maximum snow water equivalent (SWE) was reduced by more than 50% beneath dense canopies compared with clearings, and this difference increased during the melting period. We also found significant temporal variations: when melting began in sectors with low SVF, most of the snow had already thawed in areas with high SVF. However, specific conditions occasionally produced a different response of SWE to forest cover, with lower melting rates observed beneath dense canopies. The high values of correlation coefficients for SWE and SVF (r > 0·9) indicate the reliability of predicting the spatial distribution of SWE in forests when only a moderate number of observations are available. Digital hemispherical photographs provide an appropriate tool for this type of analysis, especially for zenith angles in the range 35–55 . Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

12.
Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r2 by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

13.
Snow in the McMurdo Dry Valleys is a potential source of moisture for subnivian soils in a cold desert ecosystem. In a water‐limited environment, enhanced soil moisture is expected to provide more favourable conditions for subnivian soil communities. In addition, snow cover insulates the underlying soil from air temperature extremes. Quantifying the spatial and temporal patterns of seasonal snow accumulation and ablation is necessary to understand these dynamics. Repeat high‐resolution imagery acquired for the 2009–2010 austral summer was used to map the seasonal distribution of snow across Taylor and Wright valleys, Southern Victorialand, Antarctica. An edge detection algorithm was used to perform an object‐based classification of snow‐covered area. Coupled with topographic parameters obtained from a 30‐m digital elevation model, unique distribution patterns were characterized for five regions within the neighbouring valleys. Time lapses of snow distribution in each region provide insight into spatially variable aerial ablation rates (change in area of landscape covered by snow) across the region. A strong coastal to interior gradient of decreasing snow‐covered area was evident for both Taylor and Wright valleys. The surrounding regions of Lake Fryxell, Lake Hoare, Lake Bonney, Lake Brownworth, and Lake Vanda exhibited losses of snow‐covered area of 9.61 km2 (?93%), 1.63 km2 (?72%), 1.07 km2 (?97%), 2.60 km2 (?82%), and 0.25 km2 (?96%), respectively, as measured from peak accumulation in October to mid‐January. Differences in aerial ablation rates within and across local regions suggest that both topographic variation and regional microclimates influence the ablation of seasonal snow cover. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

14.
Leaf area index (LAI) and canopy coverage are important parameters when modelling snow process in coniferous forests, controlling interception and transmitting radiation. Estimates of LAI and sky view factor show large variability depending on the estimation method used, and it is not clear how this is reflected in the calculated snow processes beneath the canopy. In this study, the winter LAI and sky view fraction were estimated using different optical and biomass‐based approximations in several boreal coniferous forest stands in Fennoscandia with different stand density, age and site latitude. The biomass‐based estimate of LAI derived from forest inventory data was close to the values derived from the optical measurements at most sites, suggesting that forest inventory data can be used as input to snow hydrological modelling. Heterogeneity of tree species and site fertility, as well as edge effects between different forest compartments, caused differences in the LAI estimates at some sites. A snow energy and mass balance model (SNOWPACK) was applied to detect how the differences in the estimated values of the winter LAI and sky view fraction were reflected in simulated snow processes. In the simulations, an increase in LAI and a decrease in sky view fraction changed the snow surface energy balance by decreasing shortwave radiation input and increasing longwave radiation input. Changes in LAI and sky view fraction affected directly snow accumulation through altered throughfall fraction and indirectly snowmelt through the changed surface energy balance. Changes in LAI and sky view fraction had a greater impact on mean incoming radiation beneath the canopy than on other energy fluxes. Snowmelt was affected more than snow accumulation. The effect of canopy parameters on evaporation loss from intercepted snow was comparable with the effect of variation in governing meteorological variables such as precipitation intensity and air temperature. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

15.
The spatial distribution of snow water equivalent (SWE) is a key variable in many regional‐scale land surface models. Currently, the assimilation of point‐scale snow sensor data into these models is commonly performed without consideration of the spatial representativeness of the point data with respect to the model grid‐scale SWE. To improve the understanding of the relationship between point‐scale snow measurements and surrounding areas, we characterized the spatial distribution of snow depth and SWE within 1‐, 4‐ and 16‐km2 grids surrounding 15 snow stations (snowpack telemetry and California snow sensors) in California, Colorado, Wyoming, Idaho and Oregon during the 2008 and 2009 snow seasons. More than 30 000 field observations of snowpack properties were used with binary regression tree models to relate SWE at the sensor site to the surrounding area SWE to evaluate the sensor representativeness of larger‐scale conditions. Unlike previous research, we did not find consistent high biases in snow sensor depth values as biases over all sites ranged from 74% overestimates to 77% underestimates. Of the 53 assessments, 27 surveys indicated snow station biases of less than 10% of the surrounding mean observed snow depth. Depth biases were largely dictated by the physiographic relationship between the snow sensor locations and the mean characteristics of the surrounding grid, in particular, elevation, solar radiation index and vegetation density. These scaling relationships may improve snow sensor data assimilation; an example application is illustrated for the National Operational Hydrologic Remote Sensing Center National Snow Analysis SWE product. The snow sensor bias information indicated that the assimilation of point data into the National Operational Hydrologic Remote Sensing Center model was often unnecessary and reduced model accuracy. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

16.
Snowpacks and forests have complex interactions throughout the large range of altitudes where they co-occur. However, there are no reliable data on the spatial and temporal interactions of forests with snowpacks, such as those that occur in nearby areas that have different environmental conditions and those that occur during different snow seasons. This study monitored the interactions of forests with snowpacks in four forest stands in a single valley of the central Spanish Pyrenees during three consecutive snow seasons (2015/2016, 2016/2017 and 2017/2018). Daily snow depth data from time-lapse cameras were compared with snow data from field surveys that were performed every 10–15 days. These data thus provided information on the spatial and temporal changes of snow–water equivalent (SWE). The results indicated that forest had the same general effects on snowpack in each forest stand and during each snow season. On average, forest cover reduced the duration of snowpack by 17 days, reduced the cumulative SWE of the snowpack by about 60% and increased the spatial heterogeneity of snowpack by 190%. Overall, forest cover reduced SWE total accumulation by 40% and the rate of SWE accumulation by 25%. The forest-mediated reduction of the accumulation rate, in combination with the occasional forest-mediated enhancement of melting rate, explained the reduced duration of snowpacks beneath forest canopies. However, the magnitude and timing of certain forest effects on snowpack had significant spatial and temporal variations. This variability must be considered when selecting the location of an experimental site in a mountainous area, because the study site should be representative of surrounding areas. The same considerations apply when selecting a time period for study.  相似文献   

17.
Snowmelt drives a large portion of streamflow in many mountain areas of the world. However, the water paths from snowmelt to the arrival of the water in the streams are still largely unknown. This work analyzes for first time the influence of snowmelt on spring streamflow with different snow accumulation and duration, in an alpine catchment of the central Spanish Pyrenees. This study presents the water balance of the main melting months (May and June). Piezometric values, water temperature, electrical conductivity and isotope data (δ18O) allow a better understanding of the hydrological functioning of the basin during these months. Results of the water balance calculations showed that snow represented on average 73% of the water available for streamflow in May and June while precipitation during these months accounted for only 27%. However, rainfall during the melting period was important to determine the shape of the spring hydrographs. On average, 78% of the sum of both the snow water equivalent (SWE) accumulated at the beginning of May and the precipitation in May and June converted into runoff during the May–June melting period. The average evaporation-sublimation during the 2 months corresponded to 8.4% of the accumulated SWE and rainfall, so that only a small part of the water input was ultimately available for soil and groundwater storage. When snow cover disappeared from the catchment, soil water storage and streamflow showed a sharp decline. Consequently, streamflow electrical conductivity, temperature and δ18O showed a marked tipping point towards higher values. The fast hydrological response of the catchment to snow and meteorological fluctuations, as well as the marked diel fluctuations of streamflow δ18O during the melting period, strongly suggests short meltwater transit times. As a consequence of this hydrological behaviour, independently of the amount of snow accumulated and of melting date, summer streamflow remained always low, with only small runoff peaks driven by rainfall events.  相似文献   

18.
Diagnosing the source of errors in snow models requires intensive observations, a flexible model framework to test competing hypotheses, and a methodology to systematically test the dominant snow processes. We present a novel process‐based approach to diagnose model errors through an example that focuses on snow accumulation processes (precipitation partitioning, new snow density, and snow compaction). Twelve years of meteorological and snow board measurements were used to identify the main source of model error on each snow accumulation day. Results show that modeled values of new snow density were outside observational uncertainties in 52% of days available for evaluation, while precipitation partitioning and compaction were in error 45% and 16% of the time, respectively. Precipitation partitioning errors mattered more for total winter accumulation during the anomalously warm winter of 2014–2015, when a higher fraction of precipitation fell within the temperature range where partition methods had the largest error. These results demonstrate how isolating individual model processes can identify the primary source(s) of model error, which helps prioritize future research.  相似文献   

19.
We report a methodology for reconstructing the daily snow depth distribution at high spatial resolution in a small Pyrenean catchment using time‐lapse photographs and snow depletion rates derived from an on‐site measuring meteorological station. The results were compared with the observed snow depth distribution, determined on a number of separate occasions using a terrestrial laser scanner (TLS). The time‐lapse photographs were projected onto a digital elevation model of the study site, and converted into snow presence/absence information. The melt‐out date (MOD; first occurrence of melt out after peak snow accumulation) was obtained from the projected photograph series. Commencing the backward reconstruction for each grid cell at the MOD, the method uses simulated snow depth depletion rates using a temperature index approach, which are extrapolated to the grid cells of the domain to arrive at the snow distribution of the previous day. Two variants of the reconstruction techniques were applied (1) using a spatially constant degree day factor (DDF) for calculating the daily expected snow depth depletion rate, and (2) allowing a spatially distributed DDF calculated from two consecutive TLS acquisitions compared to the snow depth depletion rate observed at the meteorological station. Validation revealed that both methods performed well (average R2 = 0.68; standard RMSE = 0.58), with better results obtained from the spatially distributed approach. Nevertheless, the spatially corrected DDF reconstruction, which requires TLS data, suggests that the constant DDF approach is an efficient, and for most applications sufficiently accurate and easily reproducible method. The results highlight the usefulness of time‐lapse photography for not only determining the snow covered area, but also for estimating the spatial distribution of snow depth. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

20.
A 109.91 m ice core was recovered from Dome A (or Dome Argus), the highest ice feature in Antarctica, during the 2004/05 austral summer by the 21st Chinese National Antarctic Research Expedition (CHINARE-21). Both methane profile along the core and firn densification model calculation suggest that the close-off depth is at about 102.0 m with an ice age about 4200 a. Stable isotopes (δ18O and δD) of the chips samples produced during each run of ice core drilling at Dome A, together with those of the other co...  相似文献   

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