160 research outputs found
On the estimation of ice volume of alpine glaciers
No full textVolume (V) − area (S) scaling approach (V = kSp, where V and S are obtained from direct measurements) is widely used for ice storage assessments in glacier-mountain systems. Accuracy of this approach was tested using surface area and volume dataset for 121 glaciers of different morphological type and sizes in Altay Mountains. It is shown that to increase total volume estimation accuracy, the coefficients k and p should be calculated for dominant morphological glacier types in the given region. Volume assessments for individual glaciers can be done using limited ice thickness data along the longitudinal profile. For two glaciers in Caucasus volume was calculated using parabolic and Topo to Raster approximation for cross section profiles of their surface and bedrock with acceptable accuracy (from 1 to 33%). It is also shown that ice-thickness data for 10–15 glaciers of dominant morphological type is enough for adequate estimation of the total ice storage in given mountain system with error less than 20%
Comment on “Absence of Age‐Related Trends in Stable Oxygen Isotope Ratios From Oak Tree Rings” by Duffy et al. (2019)
No full text202
Reserve of ice in glaciers on the Nordenskiöld Land, Spitsbergen, and their changes over the last decades
Get PDFData on thickness and area of 16 glaciers on the Nordenskiöld Land (Svalbard) were obtained in 1999 and 2010–2013. These data were used to determine volume of the glaciers and to establish statistical local relationship between the volume V and the area A (V–A scaling) in the form of the power function V = cAγ, and then to calculate the total ice volume of all 202 glaciers in this area and its changes during the period since 1936 to 2002–2008. The total area of 16 glaciers was 129.9±0.35 km2, 14 of which had areas from 0.2 to 8.1 km2. The two largest ones, the Fridtjof and the West Grenfjord, had the areas 17.5 and 47.3 km2, respectively, and thus occupied about 50% (64.8 km2) of the total area of 16 glaciers. These two glaciers account for 67% of the total measured volume (10,034 km3) of the 16 glaciers. A nonlinear least-squares method was used to estimate ice reserves in all 202 glaciers from data on the volume and area of 16 glaciers. The relation between volume V and area A of the glaciers (V–A scaling) was obtained as the ratio V = 0.03637A1,283 with 95%‑th confidence intervals of the coefficients с and γ, (0.02303–0,4971) and (1.184–1.381), respectively. This made possible to calculate total volume of 202 glaciers as of 2002-2008 state using data from RGI v.6.0, and that prove to be equal to 32.89 (16.75–56.63) km3. To verify this estimation, we applied the bootstrapping method for chosen 43 glaciers and calculated the volume by means of sequential use of data for large and smaller glaciers. According to this estimate, the total volume of 202 glaciers amounted to 30.34 km3 with a 95% confidence interval of 15.42–44.27 km3, that turned out to be slightly smaller than the volume calculated by nonlinear least squares method basing on measurements on 16 glaciers. Despite the large error (on the average, from −49% to +84%) in estimating the total volume of 202 glaciers in the Nordenskiöld Land, the data obtained were used for assessment of relative changes in the total volume of glaciers in this area over different time intervals. During the period from 1936 to1990 (54 years), the total area of all glaciers reduced from 738.1 to 546.7 km2, and the total volume decreased from 49,205 to 34,857 km3. Similar results for the period 1990–2002–2008 (~15 years) are the total area changes from 546.7 to 507.9 km2 and their total volume - from 34.857 to 32.890 km3. The rate of decrease of the volume for the period 1936–1990 was equal to −0.266 km3/year, for the period 1990–2002–2008 – minus 0.131 km3/year, and as a whole for the studied period (since 1936 to 2002–2008) – minus 0.236 km3/year. The average mass balance in the first period was equal to −0.372 m w.e./year, in the second one −0.224 m w.e./year, and for the whole time −0.342 m w.e./year
Testing long-term summer temperature reconstruction based on maximum density chronologies obtained by reanalysis of tree-ring data sets from northernmost Sweden and Finland
No full textHere we analyse the maximum latewood density (MXD) chronologies of two
published tree-ring data sets: one from Torneträsk region in northernmost
Sweden (TORN; Melvin et al., 2013) and one from northern Fennoscandia (FENN;
Esper et al., 2012). We paid particular attention to the MXD low-frequency
variations to reconstruct summer (June–August, JJA) long-term temperature
history. We used published methods of tree-ring standardization: regional
curve standardization (RCS) combined with signal-free implementation.
Comparisons with RCS chronologies produced using single and multiple
(non-climatic) ageing curves (to be removed from the initial MXD series)
were also carried out. We develop a novel method of standardization, the
correction implementation of signal-free standardization, tailored for
detection of pure low-frequency signal in tree-ring chronologies. In this
method, the error in RCS chronology with signal-free implementation is
analytically assessed and extracted to produce an advanced chronology. The
importance of correction becomes obvious at lower frequencies as smoothed
chronologies become progressively more correlative with correction
implementation. Subsampling the FENN data to mimic the lower chronology
sample size of TORN data shows that the chronologies bifurcate during the
7th, 9th, 17th and 20th centuries. We used the two MXD data sets to
reconstruct summer temperature variations over the period 8 BC through AD
2010. Our new reconstruction shows multi-decadal to multi-centennial
variability with changes in the amplitude of the summer temperature of 2.2 °C on average during the Common Era. Although the MXD data provide palaeoclimate research with a highly reliable summer temperature proxy, the
bifurcating dendroclimatic signals identified in the two data sets imply that future research should aim at a more advanced understanding of MXD
data on distinct issues: (1) influence of past population density
variations on MXD production, (2) potential biases when calibrating
differently produced MXD data to produce one proxy record, (3) influence of
the biological age of MXD data when introducing young trees into the chronology
over the most recent past and (4) possible role of waterlogging in MXD
production when analysing tree-ring data of riparian trees
Estimation of Biases in RCS Chronologies of Tree Rings
No full textПроводится сравнение RCS- и signal-free RCS- хронологий на нескольких примерах с реальными
и модельными измерениями ширины годичных колец деревьев. Модельные измерения,
содержащие известный климатический сигнал, строятся на основе реальных с сохранением
структуры набора данных. Во всех экспериментах на модельных данных signal-free RCS
превосходит обычный RCS. Но в то же время он менее устойчив к сокращению числа серий
измерений. Предлагается метод оценки и корректировки возможных смещений в RCS-
хронологиях древесных колец, связанных со структурой набора данных (длина и особенности
индивидуальных серий, распределение данных во времени). Такая корректировка может
проводиться перед построением реконструкций с применением стандартизации региональной
кривой (RCS) и ее «очищенной от сигнала» модификации (signal-free RCS) для повышения
точности этих реконструкций.We use several examples of modeled and real tree ring width measurements to compare RCS and
signal-free RCS chronologies. Modeled data containing known climatic signal are designed to preserve
the structure of dataset. All the experiments with modeled data showed the better ability of signal-free
RCS to restore climatic signal. At the same time it is less (as compared to conventional RCS) robust
to the reduction of sample depth. A method for evaluation and correction of biases connected with the
structure of dataset (length and specifics of individual series, their distribution in time) is proposed.
Such correction can be carried out before making climate reconstructions with conventional RCS and
signal-free RCS chronologies
Estimation of Biases in RCS Chronologies of Tree Rings
No full textПроводится сравнение RCS- и signal-free RCS- хронологий на нескольких примерах с реальными
и модельными измерениями ширины годичных колец деревьев. Модельные измерения,
содержащие известный климатический сигнал, строятся на основе реальных с сохранением
структуры набора данных. Во всех экспериментах на модельных данных signal-free RCS
превосходит обычный RCS. Но в то же время он менее устойчив к сокращению числа серий
измерений. Предлагается метод оценки и корректировки возможных смещений в RCS-
хронологиях древесных колец, связанных со структурой набора данных (длина и особенности
индивидуальных серий, распределение данных во времени). Такая корректировка может
проводиться перед построением реконструкций с применением стандартизации региональной
кривой (RCS) и ее «очищенной от сигнала» модификации (signal-free RCS) для повышения
точности этих реконструкций.We use several examples of modeled and real tree ring width measurements to compare RCS and
signal-free RCS chronologies. Modeled data containing known climatic signal are designed to preserve
the structure of dataset. All the experiments with modeled data showed the better ability of signal-free
RCS to restore climatic signal. At the same time it is less (as compared to conventional RCS) robust
to the reduction of sample depth. A method for evaluation and correction of biases connected with the
structure of dataset (length and specifics of individual series, their distribution in time) is proposed.
Such correction can be carried out before making climate reconstructions with conventional RCS and
signal-free RCS chronologies
The intensity of the climatic signal in the dynamics of the inсrement of Scots pine (Pinus silvestris L.) of the Khrenovskii forest (Voronezh region, Russia)
Get PDFOur research was carried out in the center of the Voronezh Region, Russia, in the pine forest "Khrenovskoy forest", located in the forest steppe zone of the Russian Plain. The samples for dendrochronological analysis were collected from 30 trees (1 core per tree). The climatic characteristics are taken from the data of the weather stations "Khrenovskoy forest", for the period 1936-1996 and Voronezh for the period 1862-2015. In accordance with the goal of the research, we identified high correlation coefficients (up to 0.42) and dispersion (up to 0.66) between the radial increment of Scots pine and the climatic limiting growth factors (sum of atmospheric precipitation, hydrothermal coefficient Selyaninova
Combined dendrochronological and radiocarbon dating of six Russian icons from the 15th–17th centuries
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Holocene history of the Ullukam Glacier
No full textUsing instrumental archives, aerial photographs, satellite images, old maps, descriptions of early explorers and old photographs we identified and mapped nine front positions of the Ullukam Glacier (SW slope of Elbrus) for the period from the end of XIX to the early XXI centuries. In 1884–2009 glacier retreated by 775 m. It advanced from 1971 to 1987 (36 m). The glacier fluctuations in the previous period were reconstructed using geomorphologic data, lichenometry, modern and buried soil description and radiorarbon analyses. We identified three Little Ice Age moraines of almost equal magnitude when the Ullukam Glacier was 889 m longer than in 2009. Two later advances occurred in the first third to middle of XIX century and in 1870s The recent fluctuations of the Ullukam Glacier closely correspond to the retreat two other glaciers in Elbus area. The location of the buried soil in the valley of Ullukam glacier brings evidence that the glacier have not advanced lower than 2813 m a.s.l. at least during the last four thousand years
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