Specific features of the structure of oligotrophic peatlands in the Arctic ecoregions

2020 ◽  
Author(s):  
Svetlana Selyanina ◽  
Tamara Ponomareva
Keyword(s):  
Snow Cover ◽  
The Arctic ◽  
Cellular Structures ◽  
Plant Residues ◽  
Peat Bogs ◽  
Botanical Composition ◽  
Sphagnum Mosses ◽  
Peat Deposits ◽  
Subarctic Climate ◽  
Continental Climate

<p>The ecological functions of bog ecosystems and their resistance to external influences are largely determined by the structure and chemical composition of peat.</p><p>The structure of thick peat deposits of oligotrophic bogs typical for the west of the Arctic ecoregion of Russia is studied.  The investigated peatlands are affected by the seas of the Arctic Ocean (the White and Barents).  Bog massifs in the continental climate zone without marine influence outside the Arctic territories were studied for comparison purposes. The studied bog natural complexes all belong to the oligotrophic type, are similar in structure to the deposit profile, have a peat layer of the comparable thickness and a similar homogeneous botanical composition. The peat of all studied bogs is characterized by a low degree of decomposition over the entire depth of the profile (not more than 15-20%).</p><p>The degree of decomposition, the botanical composition and the structure of the samples was studied by transmitted-light-microscopy. Fractionation was carried out by elutriation on sieves with a mesh size of 100 μm and 250 μm.</p><p>The macrostructure of the studied peat bogs is formed by the undecomposed and weakly decomposed residues of peat-forming plants - mainly sphagnum mosses mixed with cotton-grass in certain layers. Analysis of peat samples from the Arctic ecoregion showed a high degree of grinding of sphagnum moss residues without visible signs of biochemical disturbance of cellular structures. This feature is most noticeable when considering the fraction of 100-250 μm, where particles of such plant residues are concentrated. Leaves of sphagnum mosses in peat samples from the Arctic maritime territories are broken, but the cellular structures retain their integrity. In peat samples from bogs of the continental climatic zone, this phenomenon is not observed. Plant residues retain their integrity quite well, both in the upper and lower layers, and the fraction of 100-250 μm is composed of undisturbed leaves of sphagnum mosses.</p><p>The revealed specific nature of defragmentation of plant residues in the conditions of oligotrophic bog massifs of the Arctic ecoregion can be explained by the freezing-thawing cycles during the formation of a stable snow cover. In the conditions of a maritime subarctic climate, a stable snow cover is formed for a long period in the multiple transitions of air and soil temperatures through the zero-temperature mark. The thickness of the snow cover under the influence of winds in the open spaces of the bogs can decrease to the minimum values. The noted structural features are traced throughout the depth of the deposit. However, increased content of physically destroyed particles of sphagnum mosses in the upper horizons of the peat deposit in the maritime subarctic climate is observed, which may well be associated with global warming and an increase in freezing-thawing cycles.</p><p>The obtained results require confirmation in the framework of model experiments both in the conditions of a mesocosm and laboratory. Besides, the extensive comparative studies on similar peat deposits in a maritime and continental climate must be made.</p>

scholarly journals Element composition of peat deposits in flat frost mound bogs of the Pyakupur River (northern taiga of West Siberia)

2018 ◽  
Vol 8 (1) ◽  
pp. 79-87 ◽  
Author(s):  
A. G. Lim ◽  
S. V. Loiko ◽  
T. V. Raudina ◽  
I. I. Volkova ◽  
V. P. Seredina
Keyword(s):  
Active Layer ◽  
Accumulation Rate ◽  
Element Composition ◽  
Peat Deposit ◽  
Composition Analysis ◽  
Birch Bark ◽  
Botanical Composition ◽  
Sphagnum Mosses ◽  
Peat Deposits ◽  
Significant Difference

<p>The content and the profile distribution of the element composition of the 1 meter high peat deposits in flat frost mound bogs are investigated. The botanical composition of peat is described. The results of the botanical composition analysis of peat showed that deposits consist mainly of sphagnum mosses, lichens, shrubs, green mosses, pine wood, as well as pine and birch bark. A good correlation between the degree of peat decomposition and the brightness of dry peat measured by the CIE L*a*b* color model is revealed. As a result of the study of peat samples’ color, it has been found that this parameter can be used as an express method for the rapid assessment of peat degree decomposition. The highest concentration of the organic carbon occurs at the base of the peat deposit (64.4±0.2%). The nitrogen concentration in permafrost peat is higher than in thawed (1.0 ± 0.2% and 0.7 ± 0.1%, respectively, the difference is significant at p = 0.001). The C / N ratio decreases from 72 ± 16 in 0-40 cm in the thawed layer to 50 ± 10 in the frozen part (40-100 cm). Within the bottom low boundary of the seasonally thawed layer, a local increase in the N concentration was detected, as well as an almost 2-fold decrease in the C/N ratio. It is most likely related to the high increase in the rate of microbial activity on the border between the thawed layer and the permafrost peat. It was revealed that most of the elements are concentrated in the upper (thawed) part of the peat deposit. Among them, only Na, Mg, Ca, Zn, Ba, As and Sb have a significant difference. Despite the fact that significant differences according to non-parametric U-criterion Mann-Whitney test were identified only for 7 elements, the distribution of the rest along elements the frozen and thawed peat layer is similar in nature. So for Na, Mg, Al, P, K, Ca, Ti, Fe, Zn, Ba, Li, B, V, Cr, Mn, Co, Ni, Cu, Ga, As, Rb, Sr, Y, Zr, Nb, Mo, Cd, Sb, Cs, the upper quartiles of concentrations in the seasonally thawed layer are 1.2 - 6.9 times higher than in the permafrost peat, and for C, N, Al, Ba, B, V, Co, Cu , Zr, Nb, Mo it is 1,0 - 0,6 times lower, respectively. Generally, according to the element composition, it is safe to say that the differences stem from the botanical composition. In general, according to the elemental composition it can be said that the differences are primarily due to the botanical composition. The active layer comprises mainly sphagnum mosses and lichens, the woody peat already appears in the lower permafrost part of the deposit. A correlation between the brightness of peat and the total content of ash elements (R2 = 0.65, excluding 1 sample) was revealed within the active layer. Taking into account the fact that the brightness correlates with the degree of decomposition, it may be concluded that higher upper quartile of the concentrations of elements in the active layer relates to the slower peat accumulation rate for the last 3 thousand years and, correspondingly, a large accumulation of dust components from the atmosphere by the peat layers.</p>

scholarly journals Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 130
Author(s):  
Sebastian Rößler ◽  
Marius S. Witt ◽  
Jaakko Ikonen ◽  
Ian A. Brown ◽  
Andreas J. Dietz
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Air Temperature ◽  
Kendall Test ◽  
The Arctic ◽  
Boreal Winter ◽  
Snowmelt Runoff ◽  
River Catchment ◽  
Catchment Areas ◽  
Runoff Model

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR’s Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM).

scholarly journals Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

2017 ◽  
Vol 8 (4) ◽  
pp. 963-976 ◽  
Author(s):  
Jaak Jaagus ◽  
Mait Sepp ◽  
Toomas Tamm ◽  
Arvo Järvet ◽  
Kiira Mõisja
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Large Scale ◽  
Regime Shifts ◽  
The Arctic ◽  
Dry Period ◽  
Snow Cover Duration ◽  
Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

Concluding remarks

1977 ◽  
Vol 280 (972) ◽  
pp. 373-374
Keyword(s):  
Lake Sediments ◽  
Ice Sheets ◽  
The Arctic ◽  
Peat Bogs ◽  
British Isles ◽  
Field Of Study ◽  
Great Range ◽  
Scientific Disciplines ◽  
History Of ◽  
Antarctic Ice Sheets

The conclusion of this two day meeting finds us with a very great deal on which we may congratulate ourselves. In the first place there is the extremely large attendance, embracing scientists of all ages, and graced and illuminated by the attendance of many overseas colleagues of experience and distinction. In the second place we have the great range of scientific disciplines that are now applied to our field of study, many now extremely sophisticated, and the corresponding extension of Quaternary Studies into fields of evidence not hitherto exploited. In the early days of palynology of laminated lake sediments one could write of deciphering the ‘annals of the lakes’, but beginning by reading the record of lakes, peat bogs, coastal, fluviatile, glacial and periglacial geology, we have progressed to translating the long and detailed records of the deep oceans, and now the encapsulated history of the Arctic and Antarctic ice sheets. We have been introduced to the marvellous potential of the great CLIMAP Project, and all [biologists in the British Isles at least will now have to consider whether their hypotheses of past biotic history satisfy the new principle that we can all see emerging as ‘McIntyre’s Gate’.

scholarly journals On the role of Eurasian autumn snow cover in dynamical seasonal predictions 

2021 ◽  
Author(s):  
Paolo Ruggieri ◽  
Marianna Benassi ◽  
Stefano Materia ◽  
Daniele Peano ◽  
Constantin Ardilouze ◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Land Surface ◽  
General Circulation ◽  
Dominant Role ◽  
General Circulation Models ◽  
The Arctic ◽  
Seasonal Forecasts ◽  
Eurasian Snow

&lt;p&gt;Seasonal climate predictions leverage on many predictable or persistent components of the Earth system that can modify the state of the atmosphere and of relant weather related variable such as temprature and precipitation. With a dominant role of the ocean, the land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between land surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere both locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been investigated and documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of Autumn Eurasian snow in recent dynamical seasonal forecasts is therefore unclear. In this study we assess the role of Eurasian snow cover in a set of 5 operational seasonal forecast system characterized by a large ensemble size and a high atmospheric and oceanic resolution. Results are compemented with a set of targeted idealised simulations with atmospheric general circulation models forced by different snow cover conditions. Forecast systems reproduce realistically regional changes of the surface energy balance associated with snow cover variability. Retrospective forecasts and idealised sensitivity experiments converge in identifying a coherent change of the circulation in the Northern Hemisphere. This is compatible with a lagged but fast feedback from the snow to the Arctic Oscillation trough a tropospheric pathway.&lt;/p&gt;

scholarly journals Frequency and distribution of winter melt events from passive microwave satellite data in the pan-Arctic, 1988–2013

2016 ◽  
Author(s):  
Libo Wang ◽  
Peter Toose ◽  
Ross Brown ◽  
Chris Derksen
Keyword(s):  
Snow Cover ◽  
Microwave Radiometer ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Temporal Variations ◽  
Passive Microwave ◽  
The Arctic ◽  
Winter Period ◽  
Strongly Correlated ◽  
Air Temperatures

Abstract. This study presents an algorithm for detecting winter melt events in seasonal snow cover based on temporal variations in the brightness temperature difference between 19 and 37 GHz from satellite passive microwave measurements. An advantage of the passive microwave approach is that it is based on the physical presence of liquid water in the snowpack, which may not be the case with melt events inferred from surface air temperature data. The algorithm is validated using in situ observations from weather stations, snowpit surveys, and a surface-based passive microwave radiometer. The results of running the algorithm over the pan-Arctic region (north of 50º N) for the 1988–2013 period show that winter melt days are relatively rare averaging less than 7 melt days per winter over most areas, with higher numbers of melt days (around two weeks per winter) occurring in more temperate regions of the Arctic (e.g. central Quebec and Labrador, southern Alaska, and Scandinavia). The observed spatial pattern was similar to winter melt events inferred with surface air temperatures from ERA-interim and MERRA reanalysis datasets. There was little evidence of trends in winter melt frequency except decreases over northern Europe attributed to a shortening of the duration of the winter period. The frequency of winter melt events is shown to be strongly correlated to the duration of winter period. This must be taken into account when analyzing trends to avoid generating false increasing trends from shifts in the timing of the snow cover season.

scholarly journals The Changing Cryosphere: Pan-Arctic Snow Trends (1979–2009)

2011 ◽  
Vol 24 (21) ◽  
pp. 5691-5712 ◽  
Author(s):  
Glen E. Liston ◽  
Christopher A. Hiemstra
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Snow Water Equivalent ◽  
Reanalysis Data ◽  
The Arctic ◽  
Regional Variability ◽  
Time Step ◽  
Snow Season ◽  
Regional Trends ◽  
Dominant Feature

Abstract Arctic snow presence, absence, properties, and water amount are key components of Earth’s changing climate system that incur far-reaching physical and biological ramifications. Recent dataset and modeling developments permit relatively high-resolution (10-km horizontal grid; 3-h time step) pan-Arctic snow estimates for 1979–2009. Using MicroMet and SnowModel in conjunction with land cover, topography, and 30 years of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) atmospheric reanalysis data, a distributed snow-related dataset was created including air temperature, snow precipitation, snow-season timing and length, maximum snow water equivalent (SWE) depth, average snow density, snow sublimation, and rain-on-snow events. Regional variability is a dominant feature of the modeled snow-property trends. Both positive and negative regional trends are distributed throughout the pan-Arctic domain, featuring, for example, spatially distinct areas of increasing and decreasing SWE or snow season length. In spite of strong regional variability, the data clearly show a general snow decrease throughout the Arctic: maximum winter SWE has decreased, snow-cover onset is later, the snow-free date in spring is earlier, and snow-cover duration has decreased. The domain-averaged air temperature trend when snow was on the ground was 0.17°C decade−1 with minimum and maximum regional trends of −0.55° and 0.78°C decade−1, respectively. The trends for total number of snow days in a year averaged −2.49 days decade−1 with minimum and maximum regional trends of −17.21 and 7.19 days decade−1, respectively. The average trend for peak SWE in a snow season was −0.17 cm decade−1 with minimum and maximum regional trends of −2.50 and 5.70 cm decade−1, respectively.

FEATURES OF SNOW COVER OF SEMI-DESERTS AND DRY STEPPES OF THE CASPIAN SEA ACCORDING TO SATELLITE DATA FOR THE PERIOD 2001...2020

2021 ◽  
Vol 101 (2) ◽  
pp. 80-87
Author(s):  
A.G Terekhov ◽  
◽  
N.I. Ivkina ◽  
N.N. Abayev ◽  
A.V. Galayeva ◽  
...  
Keyword(s):  
Snow Cover ◽  
Caspian Sea ◽  
Snow Depth ◽  
Eastern Coast ◽  
The Caspian Sea ◽  
Dry Steppe ◽  
Natural Tendency ◽  
Second Mode ◽  
Continental Climate

The Snow Depth FEWS NET daily product was used to analyze snowy regime of the upper part of the River Emba basin from January 1 to April 30 for the period of 2001...2020. The Emba River basin is situated in Kazakhstan at the Eastern coast of the Caspian Sea. The area is characterized by the arid and extreme continental climate with dry-steppe and semi-desert landscapes. The population is small and the anthropogenic impact on the snow cover is minimal there. These conditions give an opportunity to identify the natural tendency in long-term changes of snow covering in semidesert zone of Kazakhstan. This paper describes the characteristics of the formation and destruction of the snow cover in the last 20 years. It was indicated that snowy regime has a trigger structure including two states; low-snowy regime and others years. It was shown that the snowy conditions are triggered. There are two modes, the first, as a low-snowy regime (up to 50 % of the entire sample) and the second mode includes other years. Significant variations of snow depth in various years masked many years’ tendencies of snow cover characteristics. But low-snowy regime was observed four times during five last years that can relate with modern decreasing snow covering in semi-desert zone of Kazakhstan.

scholarly journals High resolution snow distribution data from complex Arctic terrain: a tool for model validation

2002 ◽  
Vol 2 (3/4) ◽  
pp. 147-155 ◽  
Author(s):  
Ch. Jaedicke ◽  
A. D. Sandvik
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Numerical Models ◽  
The Arctic ◽  
Distribution Data ◽  
Blowing Snow ◽  
Data Set ◽  
Meteorological Model ◽  
Drift Model ◽  
Snow Distribution

Abstract. Blowing snow and snow drifts are common features in the Arctic. Due to sparse vegetation, low temperatures and high wind speeds, the snow is constantly moving. This causes severe problems for transportation and infrastructure in the affected areas. To minimise the effect of drifting snow already in the designing phase of new structures, adequate models have to be developed and tested. In this study, snow distribution in Arctic topography is surveyed in two study areas during the spring of 1999 and 2000. Snow depth is measured by ground penetrating radar and manual methods. The study areas encompass four by four kilometres and are partly glaciated. The results of the surveys show a clear pattern of erosion, accumulation areas and the evolution of the snow cover over time. This high resolution data set is valuable for the validation of numerical models. A simple numerical snow drift model was used to simulate the measured snow distribution in one of the areas for the winter of 1998/1999. The model is a two-level drift model coupled to the wind field, generated by a mesoscale meteorological model. The simulations are based on five wind fields from the dominating wind directions. The model produces a satisfying snow distribution but fails to reproduce the details of the observed snow cover. The results clearly demonstrate the importance of quality field data to detect and analyse errors in numerical simulations.

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