Biological features of Lavandula angustifolia Mill. сultivated in the conditions of Russia non-chernozem zone

2020 ◽  
Author(s):  
I.N. Korotkikh I.N. ◽  
◽  
M.U. Grjaznov M.U. ◽  
S.A. Totskaya S.A.
Keyword(s):  
Snow Cover ◽  
Growth And Development ◽  
Seasonal Cycle ◽  
Winter Season ◽  
Moscow Region ◽  
Lavandula Angustifolia ◽  
Biological Features

The article discusses the biological features of Lavandula angustifolia Mill., cultivated in the non-Chernozem zone of Russia. In the Moscow region L. angustifolia goes through the entire seasonal cycle of growth and development lasting 150-155 days, lavandula plants are 93-97% resistant to the conditions of the winter season (if there is a snow cover of at least 10-12 cm high).

Influence of snow cover and air temperature on variations of ground freezing depth in Moscow and the Moscow region

2021 ◽  
Author(s):  
Denis Frolov
Keyword(s):  
Thermal Conductivity ◽  
Snow Cover ◽  
Air Temperature ◽  
Winter Season ◽  
Moscow Region ◽  
Frozen Ground ◽  
Ground Freezing ◽  
Meteorological Observatory ◽  
Freezing Depth ◽  
Cover Thickness

<p>According to consdidered influence of snow cover thickness and air temperature on variations of ground freezing depth at the site of meteorological observatory of Moscow State University and also according to the data of observatories in the Moscow region it is expected to make conclusions about the impact of the urban heat island to a ground freezing depth in Moscow region. For this purpose, the values of the maximum ground freezing depth were analyzed for MSU meteorological observatory and for the weather stations of the Moscow region: Kolomna, Mozhaisk and Sukhinichi. And since not always the data of actual observations are avaliable, for these weather stations the calculated values of the maximum ground freezing depth were obtained. The calculations were performed according to the previously developed calculation scheme, based on the problem of thermal conductivity of a three-layer medium (snow, frozen and thawed ground) with a phase transition at the boundary. The heat balance equation included the energy of the phase transition, the inflow of heat from the thawed ground and the outflow to the frozen ground and, in the presence of snow cover, through it to the atmosphere. The heat flow was calculated according to Fourier's law as the product of the thermal conductivity and the temperature gradient. It was assumed that the temperature in each medium varies linearly. For snow cover and frozen ground, the formula of thermal conductivity of a two-layer medium was used. The obtained calculated values were compared with the actual values of the ground freezing depth. The coefficients R<sup>2</sup> of the reliability of the linear trend line approximation when comparing the calculated and actual values for Moscow and the Moscow region were at the level of 0.6-0.7. The maximum ground freezing depth in Moscow and in the Moscow region in the same years may differ by an average of 10 cm. This confirms that the designed scheme well describes ground freezing depth based on data on air temperature and snow cover thickness and can be used to model the underground heat island of the Moscow region. In report it is also supposed to present the results of the recent years observations of snow cover and freezing depth variations in Moscow and the Moscow region. The past  2020 year is considered as the warmest in the entire history of observations according to the MSU Meteorological Observatory for Moscow, according to the Hydrometeorological Center of Russia for the whole of Russia and according to the Copernicus Climate Change Service (C3S) for the entire Globe. So the winter season of 2019/20 in Moscow region was also unusually warm, and therefore in the winter season of 2019/20 there was very little snow in the Moscow region. However, the warm summer of 2020 resulted in one of the lowest summer values of sea ice extent in the Arctic and, as a result, abnormally strong minimum temperatures and heavy snowfall in the winter of 2020/21 in Eurasia and Moscow. The work was done in a frame of state topic AAAA-A16-116032810093-2.</p>

scholarly journals Changes in Air Temperature and Snow Cover in Winter in Poland

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 68
Author(s):  
Arkadiusz M. Tomczyk ◽  
Ewa Bednorz ◽  
Katarzyna Szyga-Pluta
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Winter Season ◽  
Primary Objective ◽  
Climatic Conditions ◽  
Cover Depth ◽  
North Eastern ◽  
Northern Regions ◽  
Maximum Air Temperature ◽  
Snow Cover Depth

The primary objective of the paper was to characterize the climatic conditions in the winter season in Poland in the years 1966/67–2019/20. The study was based on daily values of minimum (Tmin) and maximum air temperature (Tmax), and daily values of snow cover depth. The study showed an increase in both Tmin and Tmax in winter. The most intensive changes were recorded in north-eastern and northern regions. The coldest winters were recorded in the first half of the analyzed multiannual period, exceptionally cold being winters 1969/70 and 1984/85. The warmest winters occurred in the second half of the analyzed period and among seasons with the highest mean Tmax, particularly winters 2019/20 and 1989/90 stood out. In the study period, a decrease in snow cover depth statistically significant in the majority of stations in Poland was determined, as well as its variability both within the winter season and multiannual.

scholarly journals Comparing Sudden Stratospheric Warming Definitions in Reanalysis Data*

2015 ◽  
Vol 28 (17) ◽  
pp. 6823-6840 ◽  
Author(s):  
Froila M. Palmeiro ◽  
David Barriopedro ◽  
Ricardo García-Herrera ◽  
Natalia Calvo
Keyword(s):  
Seasonal Cycle ◽  
Winter Season ◽  
Reanalysis Data ◽  
Sudden Stratospheric Warming ◽  
Pronounced Increase ◽  
Future Studies ◽  
Common Peak ◽  
Before And After ◽  
The Mean ◽  
Large Case

Abstract Sudden stratospheric warmings (SSWs) are characterized by a pronounced increase of the stratospheric polar temperature during the winter season. Different definitions have been used in the literature to diagnose the occurrence of SSWs, yielding discrepancies in the detected events. The aim of this paper is to compare the SSW climatologies obtained by different methods using reanalysis data. The occurrences of Northern Hemisphere SSWs during the extended-winter season and the 1958–2014 period have been identified for a suite of eight representative definitions and three different reanalyses. Overall, and despite the differences in the number and exact dates of occurrence of SSWs, the main climatological signatures of SSWs are not sensitive to the considered reanalysis. The mean frequency of SSWs is 6.7 events decade−1, but it ranges from 4 to 10 events, depending on the method. The seasonal cycle of events is statistically indistinguishable across definitions, with a common peak in January. However, the multidecadal variability is method dependent, with only two definitions displaying minimum frequencies in the 1990s. An analysis of the mean signatures of SSWs in the stratosphere revealed negligible differences among methods compared to the large case-to-case variability within a given definition. The stronger and more coherent tropospheric signals before and after SSWs are associated with major events, which are detected by most methods. The tropospheric signals of minor SSWs are less robust, representing the largest source of discrepancy across definitions. Therefore, to obtain robust results, future studies on stratosphere–troposphere coupling should aim to minimize the detection of minor warmings.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

scholarly journals Nimbus-7 SMMR Derived Global Snow Cover Parameters

1987 ◽  
Vol 9 ◽  
pp. 39-44 ◽  
Author(s):  
A.T.C. Chang ◽  
J.L. Foster ◽  
D.K. Hall
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Snow Water Equivalent ◽  
Theoretical Calculations ◽  
Winter Season ◽  
Western China ◽  
High Plains ◽  
Snow Covered Area ◽  
Covered Area ◽  
Snow Water

Snow covers about 40 million km2 of the land area of the Northern Hemisphere during the winter season. The accumulation and depletion of snow is dynamically coupled with global hydrological and climatological processes. Snow covered area and snow water equivalent are two essential measurements. Snow cover maps are produced routinely by the National Environmental Satellite Data and Information Service of the National Oceanic and Atmospheric Administration (NOAA/NESDIS) and by the US Air Force Global Weather Center (USAFGWC). The snow covered area reported by these two groups sometimes differs by several million km2, Preliminary analysis is performed to evaluate the accuracy of these products.Microwave radiation penetrating through clouds and snowpacks could provide depth and water equivalent information about snow fields. Based on theoretical calculations, snow covered area and snow water equivalent retrieval algorithms have been developed. Snow cover maps for the Northern Hemisphere have been derived from Nimbus-7 SMMR data for a period of six years (1978–1984). Intercomparisons of SMMR, NOAA/NESDIS and USAFGWC snow maps have been conducted to evaluate and assess the accuracy of SMMR derived snow maps. The total snow covered area derived from SMMR is usually about 10% less than the other two products. This is because passive microwave sensors cannot detect shallow, dry snow which is less than 5 cm in depth. The major geographic regions in which the differences among these three products are the greatest are in central Asia and western China. Future study is required to determine the absolute accuracy of each product.Preliminary snow water equivalent maps have also been produced. Comparisons are made between retrieved snow water equivalent over large area and available snow depth measurements. The results of the comparisons are good for uniform snow covered areas, such as the Canadian high plains and the Russian steppes. Heavily forested and mountainous areas tend to mask out the microwave snow signatures and thus comparisons with measured water equivalent are poorer in those areas.

scholarly journals Introduction of sorts of Clematis L. genus in the South-Ural Botanical Garden-Institute of UFRC RAS

2021 ◽  
Vol 21 (1) ◽  
pp. 56-61
Author(s):  
Roza A. Bilalova ◽  
Keyword(s):  
High Resistance ◽  
Growth And Development ◽  
Vegetative Reproduction ◽  
Botanical Garden ◽  
Climatic Conditions ◽  
Rooted Cuttings ◽  
Seasonal Rhythm ◽  
Growing Period ◽  
Biological Features

The article presents the results of a long-term of study of biological features of 54 sorts of Clematis L. genus of collection of the SouthUral Botanical Garden-Institute of UFRC RAS. The aim of the work was to summarize the introduction studies for the possibility of successful use of clematis sorts in vertical gardening in the Bashkir Cis-Urals and adjacent territories. During the period 2007 and 2015, the seasonal rhythm of growth and development and vegetative reproduction were studied, and the prospects of introduction and introduction resistance under the culture were assessed. The length of the clematis growing period varies from 156 to 168 days. The duration of flowering of sorts is 24–111 days. Rooting of clematis sorts using root-forming stimulators is 33 to 100%. The largest number of rooted cuttings was obtained using the preparation “Circon”. According to the results of the introduction success assessment, all the studied sorts have high resistance to local climatic conditions.

A tracking algorithm to identify slab and weak layer combinations for assessing snow instability and avalanche problem type

2021 ◽  
Author(s):  
Benjamin Reuter ◽  
Léo Viallon-Galinier ◽  
Stephanie Mayer ◽  
Pascal Hagenmuller ◽  
Samuel Morin
Keyword(s):  
Snow Cover ◽  
Winter Season ◽  
Essential Element ◽  
Problem Type ◽  
Model Output ◽  
Avalanche Forecasting ◽  
Weak Layer ◽  
Problem Types ◽  
Snow Stratigraphy ◽  
Wet Snow

<p>Snow cover models have mostly been developed to support avalanche forecasting. Recently developed snow instability metrics can help interpreting modeled snow cover data. However, presently snow cover models cannot forecast the relevant avalanche problem types – an essential element to describe avalanche danger. We present an approach to detect, track and assess weak layers in snow cover model output data to eventually assess the related avalanche problem type. We demonstrate the applicability of this approach with both, SNOWPACK and CROCUS snow cover model output for one winter season at Weissfluhjoch. We introduced a classification scheme for four commonly used avalanche problem types including new snow, wind slabs, persistent weak layers and wet snow, so different avalanche situations during a winter season can be classified based on weak layer type and meteorological conditions. According to the modeled avalanche problem types and snow instability metrics both models produced weaknesses in the modeled stratigraphy during similar periods. For instance, in late December 2014 the models picked up a non-persistent as well as a persistent weak layer that were both observed in the field and caused widespread instability in the area. Times when avalanches released naturally were recorded with two seismic avalanche detection systems, and coincided reasonably well with periods of low modeled stability. Moreover, the presented approach provides the avalanche problem types that relate to the observed natural instability which makes the interpretation of modeled snow instability metrics easier. As the presented approach is process-based, it is applicable to any model in any snow avalanche climate. It could be used to anticipate changes in avalanche problem type due to changing climate. Moreover, the presented approach is suited to support the interpretation of snow stratigraphy data for operational forecasting.</p>

scholarly journals Simultaneous Measurements of Stability Indices and Characteristic Parameters Describing the Snow Cover and the Weather in Fracture Zones of Avalanches

1980 ◽  
Vol 26 (94) ◽  
pp. 65-74 ◽  
Author(s):  
H. Gubler
Keyword(s):  
Snow Cover ◽  
Winter Season ◽  
Processing System ◽  
Weather Conditions ◽  
Fracture Zones ◽  
Characteristic Parameters ◽  
On Line ◽  
Solar Powered ◽  
Snow Temperature ◽  
Stability Indices

AbstractStability indices at different slope aspects and characteristic parameters describing the snow cover and the weather conditions are recorded simultaneously and automatically in potential fracture zones of avalanches during the whole winter season. A remote, solar-powered system including measurements of snow depth, mass flux of wind-blown snow and of the snow temperature profile as well as on-line and off-line data processing has been developed and tested. The results show that this type of data-recording and processing system makes quantitative case studies of natural stability variations possible.

scholarly journals Snow Thickness Estimation on First-Year Sea Ice from Late Winter Spaceborne Scatterometer Backscatter Variance

2019 ◽  
Vol 11 (4) ◽  
pp. 417 ◽  
Author(s):  
John Yackel ◽  
Torsten Geldsetzer ◽  
Mallik Mahmud ◽  
Vishnu Nandan ◽  
Stephen Howell ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Winter Season ◽  
Late Winter ◽  
First Year ◽  
Snow Layer ◽  
Independent Case ◽  
Brine Volume ◽  
Snow Thickness

Ku- and C-band spaceborne scatterometer sigma nought (σ°) backscatter data of snow covered landfast first-year sea ice from the Canadian Arctic Archipelago are acquired during the winter season with coincident in situ snow-thickness observations. Our objective is to describe a methodological framework for estimating relative snow thickness on first-year sea ice based on the variance in σ° from daily time series ASCAT and QuikSCAT scatterometer measurements during the late winter season prior to melt onset. We first describe our theoretical basis for this approach, including assumptions and conditions under which the method is ideally suited and then present observational evidence from four independent case studies to support our hypothesis. Results suggest that the approach can provide a relative measure of snow thickness prior to σ° detected melt onset at both Ku- and C-band frequencies. We observe that, during the late winter season, a thinner snow cover displays a larger variance in daily σ° compared to a thicker snow cover on first-year sea ice. This is because for a given increase in air temperature, a thinner snow cover manifests a larger increase in basal snow layer brine volume owing to its higher thermal conductivity, a larger increase in the dielectric constant and a larger increase in σ° at both Ku- and C bands. The approach does not apply when snow thickness distributions on first-year sea ice being compared are statistically similar, indicating that similar late winter σ° variances likely indicate regions of similar snow thickness.

scholarly journals Growth and Development of Ipomoea Weeds

2019 ◽  
Vol 37 ◽  
Author(s):  
A.A.M. BARROSO ◽  
P.S.H. FERREIRA ◽  
D. MARTINS
Keyword(s):  
Growth And Development ◽  
Winter Season ◽  
Total Biomass ◽  
Growth Data ◽  
Leaf Production ◽  
Cycle Times ◽  
Randomized Design ◽  
Periodic Growth ◽  
Productive Potential ◽  
Number Of Leaves

ABSTRACT: Weeds reduce the productive potential of crops. Plants of the Ipomoea genus, besides competing for water, light, space and nutrients, create problems in crop harvests due to their volatile stems. The objective of this work was to evaluate the growth and development of five Ipomoea species. For such, Ipomoea grandifolia, Ipomoea hederifolia, Ipomoea nil, Ipomoea purpurea and Ipomoea quamoclit plants were analyzed during the summer and winter season. Five destructive and periodic growth evaluations were carried out for each study, where leaf number, leaves, stems, roots and the total biomass were analyzed. Phenological stages of the plant development were also evaluated for emergence, flowering and maturation sub-periods by degree-days, totalizing five treatments, conducted in a completely randomized design with four replicates. The phenology averages were analyzed according to the Hess scale, and the growth data through nonlinear regressions. I. quamoclit and I. grandifolia obtained the highest number of leaves in the summer and the winter, respectively. I. nil obtained greater accumulation of leaf and stem dry biomass in both seasons. I. grandifolia obtained greater root development in both periods. I. quamoclit presented reduced cycle times when compared to the other species, especially I. hederifolia and I. grandifolia, which presented larger cycles. Based on the results, I. grandifolia probably shows greater interference with agricultural crops due to high root growth, high leaf production and longer cycle. Shorter-cycle species, such as I. quamoclit, when present, should require shorter residual control periods.

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