scholarly journals Vertical distribution of brine and volume structure thin one year ice Amur bay on base NMR and MRT dates

2019 ◽  
Vol 59 (5) ◽  
pp. 859-869
Author(s):  
N. A. Mel’nichenko ◽  
A. V. Tyuveev ◽  
A. Yu. Lazaryuk ◽  
V. E. Savchenko ◽  
E. V. Kustova
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Phase Distribution ◽  
Solid Phase ◽  
Empirical Relation ◽  
Amur Bay ◽  
Spatial Phase ◽  
Arctic Ice ◽  
One Year

It was studying distribution of liquid and solid phases in pores one year sea ice on Amur Bay with using NMR and MRT methods in period 20132016. According to findings predominant factor in ice structure formation is snow cover. The patterns of brine content and solid phase distribution are considered in interdependence with air temperature and corresponding ice layer temperatures in compliance with preceding weather conditions. Differences in vertical profiles for temperature and salinity for winter and spring periods was marked. The main features of spatial phase dictribution in thin ice in comparision Arctic ice are presented. Just snow cover effects on ice parameters was demonstrated using data 20132016. The relationship of interlayings number in ice with its thickness, air temperature, and snow cover thickness is discussed. The main features of spatial phase dictribution in thin ice in comparision Arctic ice are presented. The empirical relation for calculations thin sea ice thickness was suggested.

scholarly journals Theoretical approach describing the thermal regime of snow-covered sea ice

1993 ◽  
Vol 18 ◽  
pp. 79-84
Author(s):  
Nobuo Ono ◽  
Maxim S. Krass
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Thermal Regime ◽  
Thermal State ◽  
Equilibrium Phase ◽  
Temperature Oscillations ◽  
Oceanic Heat Flux ◽  
Boundary Model

As the greater part of sea-ice area is covered with snow, the thermal regime of sea ice is characterized by the thermal behavior of snow-covered sea ice. In this paper the thermal regime of snow-covered sea ice is quantitatively investigated with a one-dimensional non-linear boundary model which contains: compaction of snow cover; internal absorption of solar radiation; evaporation–condensation within snow cover; equilibrium phase change of brine within sea ice; and vertical oceanic heat flux from seawater to ice. Penetration of air temperature oscillations into the snow-covered sea ice increases remarkably with increasing snow density. As internal melting within the snow-covered sea ice appears with increasing solar radiation, the rise in air temperature and increase of solar radiation in the springtime produce a corresponding change in the thermal state of sea ice, causing a drastic retreat of sea-ice cover. A case study for warm sea ice is presented describing the thermal state during the melting season.

scholarly journals Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcel Nicolaus ◽  
Mario Hoppmann ◽  
Stefanie Arndt ◽  
Stefan Hendricks ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
The Arctic ◽  
Validation Data ◽  
Antarctic Sea Ice

Snow depth on sea ice is an essential state variable of the polar climate system and yet one of the least known and most difficult to characterize parameters of the Arctic and Antarctic sea ice systems. Here, we present a new type of autonomous platform to measure snow depth, air temperature, and barometric pressure on drifting Arctic and Antarctic sea ice. “Snow Buoys” are designed to withstand the harshest environmental conditions and to deliver high and consistent data quality with minimal impact on the surface. Our current dataset consists of 79 time series (47 Arctic, 32 Antarctic) since 2013, many of which cover entire seasonal cycles and with individual observation periods of up to 3 years. In addition to a detailed introduction of the platform itself, we describe the processing of the publicly available (near real time) data and discuss limitations. First scientific results reveal characteristic regional differences in the annual cycle of snow depth: in the Weddell Sea, annual net snow accumulation ranged from 0.2 to 0.9 m (mean 0.34 m) with some regions accumulating snow in all months. On Arctic sea ice, the seasonal cycle was more pronounced, showing accumulation from synoptic events mostly between August and April and maxima in autumn. Strongest ablation was observed in June and July, and consistently the entire snow cover melted during summer. Arctic air temperature measurements revealed several above-freezing temperature events in winter that likely impacted snow stratigraphy and thus preconditioned the subsequent spring snow cover. The ongoing Snow Buoy program will be the basis of many future studies and is expected to significantly advance our understanding of snow on sea ice, also providing invaluable in situ validation data for numerical simulations and remote sensing techniques.

Winter arctic sea-ice cover variability and the prediction of spring vegetation growth over Eurasia

2020 ◽  
Author(s):  
Liuqing Ji ◽  
Ke Fan
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Prediction Models ◽  
Surface Air Temperature ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Hybrid Scheme ◽  
Coupled Modes ◽  
Previous Season

<p align="justify">The changes in Eurasian vegetation not only have important effects on regional climate, but also have effects on global temperatures and the carbon cycle<span>. </span>In this study, the interannual linkage between spring vegetation <span>growth</span> over Eurasia and winter sea-ice cover over the Barents Sea (SICBS), as well as the <span>prediction of spring Euraisan vegetation </span>are investigated. The Normalized Difference Vegetation Index (NDVI) derived from the advanced very high resolution radiometer is used as the proxy of vegetation <span>growth</span>. During 1982–2015, the winter SICBS is significantly correlated with the spring NDVI over Eurasia (NDVIEA). The positive (negative) winter SICBS anomalies tend to increase (decrease) the spring NDVIEA. The increased winter SICBS corresponds to higher winter surface air temperature and soil temperature over most parts of Eurasia, and in turn, corresponds to less winter snow cover and less snow water equivalent. The persistent less and thinner snow cover from winter to spring over Eurasia, especially over Western and Central Siberia, tends to induce increased surface air temperature through decreased surface albedo and less snowmelt latent heat. Subsequently, the increased surface air temperature corresponding to increased SICBS contributes to higher vegetation <span>growth</span> over Eurasia in spring and vice versa. <span>Based on this linkage, s</span>easonal predictions of spring NDVI over Eurasia are explored by applying the year-to-year increment approach. The prediction models were developed based on the coupled modes of singular value decomposition analyses between Eurasian NDVI and climate factors. One synchronous predictor, the spring surface air temperature from the NCEP<span>’</span>s Climate Forecast System (SAT-CFS), and three previous-season predictors (winter SICBS, winter sea surface temperature over the equatorial Pacific (SSTP), and winter North Atlantic Oscillation (NAO) were chosen to develop four single-predictor schemes: the SAT-CFS scheme, SICBS scheme, SSTP scheme, and NAO scheme. Meanwhile, a statistical scheme that involves the three previous-season predictors (i.e., SICBS, SSTP, and NAO) and a hybrid scheme that includes all four predictors are also proposed. To evaluate the prediction skills of the schemes, one-year-out cross-validation and independent hindcast results are analyzed, revealing the hybrid scheme as having the best prediction skill in terms of both the spatial pattern and the temporal variability of spring Eurasian NDVI.</p>

Seasonal Variability in the Mechanisms Behind the 2020 Siberian Heatwaves

2022 ◽  
pp. 1-44
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Land Surface ◽  
Arctic Oscillation ◽  
Surface Air Temperature ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Stratospheric Polar Vortex

Abstract Record breaking heatwaves and wildfires immersed Siberia during the boreal spring of 2020 following an anomalously warm winter. Springtime heatwaves are becoming more common in the region, with statistically significant trends in the frequency, magnitude, and duration of heatwave events over the past four decades. Mechanisms by which the heatwaves occur and contributing factors differ by season. Winter heatwave frequency is correlated with the atmospheric circulation, particularly the Arctic Oscillation, while the frequency of heatwaves during the spring months is highly correlated with aspects of the land surface including snow cover, albedo, and latent heat flux. Idealized AMIP-style experiments are used to quantify the contribution of suppressed Arctic sea ice and snow cover over Siberia on the atmospheric circulation, surface energy budget, and surface air temperature in Siberia during the winter and spring of 2020. Sea ice concentration contributed to the strength of the stratospheric polar vortex and Arctic Oscillation during the winter months, thereby influencing the tropospheric circulation and surface air temperature over Siberia. Warm temperatures across the region resulted in an earlier than usual recession of the winter snowpack. The exposed land surface contributed to up to 20% of the temperature anomaly during the spring through the albedo feedback and changes in the ratio of the latent and sensible heat fluxes. This, in combination with favorable atmospheric circulation patterns, resulted in record breaking heatwaves in Siberia in the spring of 2020.

scholarly journals Theoretical approach describing the thermal regime of snow-covered sea ice

1993 ◽  
Vol 18 ◽  
pp. 79-84
Author(s):  
Nobuo Ono ◽  
Maxim S. Krass
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Thermal Regime ◽  
Thermal State ◽  
Equilibrium Phase ◽  
Temperature Oscillations ◽  
Oceanic Heat Flux ◽  
Boundary Model

As the greater part of sea-ice area is covered with snow, the thermal regime of sea ice is characterized by the thermal behavior of snow-covered sea ice. In this paper the thermal regime of snow-covered sea ice is quantitatively investigated with a one-dimensional non-linear boundary model which contains: compaction of snow cover; internal absorption of solar radiation; evaporation–condensation within snow cover; equilibrium phase change of brine within sea ice; and vertical oceanic heat flux from seawater to ice. Penetration of air temperature oscillations into the snow-covered sea ice increases remarkably with increasing snow density. As internal melting within the snow-covered sea ice appears with increasing solar radiation, the rise in air temperature and increase of solar radiation in the springtime produce a corresponding change in the thermal state of sea ice, causing a drastic retreat of sea-ice cover. A case study for warm sea ice is presented describing the thermal state during the melting season.

Seasonal variations in the properties and structural composition of sea ice and snow cover in the Bellingshausen and Amundsen Seas, Antarctica

1997 ◽  
Vol 43 (143) ◽  
pp. 138-151 ◽  
Author(s):  
M. O. Jeffries ◽  
K. Morris ◽  
W.F. Weeks ◽  
A. P. Worby
Keyword(s):  
Sea Ice ◽  
Isotopic Composition ◽  
Snow Cover ◽  
Sea Water ◽  
Ice Cores ◽  
Ice Cover ◽  
Snow Accumulation ◽  
Ice Formation ◽  
Frazil Ice ◽  
Core Sets

AbstractSixty-three ice cores were collected in the Bellingshausen and Amundsen Seas in August and September 1993 during a cruise of the R.V. Nathaniel B. Palmer. The structure and stable-isotopic composition (18O/16O) of the cores were investigated in order to understand the growth conditions and to identify the key growth processes, particularly the contribution of snow to sea-ice formation. The structure and isotopic composition of a set of 12 cores that was collected for the same purpose in the Bellingshausen Sea in March 1992 are reassessed. Frazil ice and congelation ice contribute 44% and 26%, respectively, to the composition of both the winter and summer ice-core sets, evidence that the relatively calm conditions that favour congelation-ice formation are neither as common nor as prolonged as the more turbulent conditions that favour frazil-ice growth and pancake-ice formation. Both frazil- and congelation-ice layers have an av erage thickness of 0.12 m in winter, evidence that congelation ice and pancake ice thicken primarily by dynamic processes. The thermodynamic development of the ice cover relies heavily on the formation of snow ice at the surface of floes after sea water has flooded the snow cover. Snow-ice layers have a mean thickness of 0.20 and 0.28 m in the winter and summer cores, respectively, and the contribution of snow ice to the winter (24%) and summer (16%) core sets exceeds most quantities that have been reported previously in other Antarctic pack-ice zones. The thickness and quantity of snow ice may be due to a combination of high snow-accumulation rates and snow loads, environmental conditions that favour a warm ice cover in which brine convection between the bottom and top of the ice introduces sea water to the snow/ice interface, and bottom melting losses being compensated by snow-ice formation. Layers of superimposed ice at the top of each of the summer cores make up 4.6% of the ice that was examined and they increase by a factor of 3 the quantity of snow entrained in the ice. The accumulation of superimposed ice is evidence that melting in the snow cover on Antarctic sea-ice floes ran reach an advanced stage and contribute a significant amount of snow to the total ice mass.

scholarly journals Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

2021 ◽  
Author(s):  
Zhaomin Ding ◽  
Renguang Wu
Keyword(s):  
Sea Ice ◽  
Air Temperature ◽  
Western Siberia ◽  
Russian Far East ◽  
Far East ◽  
Surface Air Temperature ◽  
The Caspian Sea ◽  
Sea Ice Concentration ◽  
Northern Siberia ◽  
The Impact

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

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.

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