scholarly journals Optical properties of ice and snow

2019 ◽  
Vol 377 (2146) ◽  
pp. 20180161 ◽  
Author(s):  
Stephen G. Warren
Keyword(s):  
Sea Ice ◽  
Sheet Thickness ◽  
Open Water ◽  
Microwave Emission ◽  
Radiative Properties ◽  
Radio Waves ◽  
Lake Ice ◽  
Near Ultraviolet ◽  
Glacier Ice ◽  
Natural Snow

The interactions of electromagnetic radiation with ice, and with ice-containing media such as snow and clouds, are determined by the refractive index and absorption coefficient (the ‘optical constants’) of pure ice as functions of wavelength. Bulk reflectance, absorptance and transmittance are further influenced by grain size (for snow), bubbles (for glacier ice and lake ice) and brine inclusions (for sea ice). Radiative transfer models for clouds can also be applied to snow; the important differences in their radiative properties are that clouds are optically thinner and contain smaller ice crystals than snow. Absorption of visible and near-ultraviolet radiation by ice is so weak that absorption of sunlight at these wavelengths in natural snow is dominated by trace amounts of light-absorbing impurities such as dust and soot. In the thermal infrared, ice is moderately absorptive, so snow is nearly a blackbody, with emissivity 98–99%. The absorption spectrum of liquid water resembles that of ice from the ultraviolet to the mid-infrared. At longer wavelengths they diverge, so microwave emission can be used to detect snowmelt on ice sheets, and to discriminate between sea ice and open water, by remote sensing. Snow and ice are transparent to radio waves, so radar can be used to infer ice-sheet thickness.This article is part of the theme issue ‘The physics and chemistry of ice: scaffolding across scales, from the viability of life to the formation of planets’.

Comparison of Arctic cloud properties over sea ice and open ocean based on airborne spectral solar remote sensing

2021 ◽  
Author(s):  
Marcus Klingebiel ◽  
André Ehrlich ◽  
Elena Ruiz-Donoso ◽  
Manfred Wendisch
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Open Water ◽  
Open Ocean ◽  
Arctic Sea Ice ◽  
Radiative Properties ◽  
Radiation Budget ◽  
The Arctic ◽  
Liquid Water Path ◽  
Cloud Properties

<p>Over the last decades, the Arctic has experienced an enhanced warming, which is known as Arctic amplification. This process leads to a decrease in the amount of Arctic sea ice, which is linked by different feedback mechanisms to clouds and the related radiative properties. To analyze how the properties of these Arctic clouds could change in a future sea ice free Arctic, we completed three airborne campaigns in the marginal sea ice zone between 2017 and 2020 covering summer and winter conditions. During these campaigns we performed in-situ and remote sensing measurements to study cloud micro- and macrophysical properties and analyzed how these clouds affect the radiation budget. In this study we use the passive remote sensing measurements from these airborne observations to retrieve cloud top effective radius, liquid water path and cloud optical thickness. We found that these cloud properties differ between a sea ice surface and over open water. The airborne observations are supported by an analysis of the cloud product from the MODIS satellite. The systematic differences of clouds over sea ice and the open ocean suggests that clouds may change in a future warming Arctic environment.</p>

scholarly journals Recent changes in pan-Arctic sea ice, lake ice, and snow-on/off timing

2021 ◽  
Vol 15 (10) ◽  
pp. 4781-4805
Author(s):  
Alicia A. Dauginis ◽  
Laura C. Brown
Keyword(s):  
Sea Ice ◽  
Climatic Change ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Regional Variability ◽  
Lake Ice ◽  
The North ◽  
Snow And Ice

Abstract. Arctic snow and ice cover are vital indicators of climate variability and change, yet while the Arctic shows overall warming and dramatic changes in snow and ice cover, the response of these high-latitude regions to recent climatic change varies regionally. Although previous studies have examined changing snow and ice separately, examining phenology changes across multiple components of the cryosphere together is important for understanding how these components and their response to climate forcing are interconnected. In this work, we examine recent changes in sea ice, lake ice, and snow together at the pan-Arctic scale using the Interactive Multisensor Snow and Ice Mapping System 24 km product from 1997–2019, with a more detailed regional examination from 2004–2019 using the 4 km product. We show overall that for sea ice, trends toward earlier open water (−7.7 d per decade, p<0.05) and later final freeze (10.6 d per decade, p<0.05) are evident. Trends toward earlier first snow-off (−4.9 d per decade, p<0.05), combined with trends toward earlier first snow-on (−2.8 d per decade, p<0.05), lead to almost no change in the length of the snow-free season, despite shifting earlier in the year. Sea ice-off, lake ice-off, and snow-off parameters were significantly correlated, with stronger correlations during the snow-off and ice-off season compared to the snow-on and ice-on season. Regionally, the Bering and Chukchi seas show the most pronounced response to warming, with the strongest trends identified toward earlier ice-off and later ice-on. This is consistent with earlier snow-off and lake ice-off and later snow-on and lake ice-on in west and southwest Alaska. In contrast to this, significant clustering between sea ice, lake ice, and snow-on trends in the eastern portion of the North American Arctic shows an earlier return of snow and ice. The marked regional variability in snow and ice phenology across the pan-Arctic highlights the complex relationships between snow and ice, as well as their response to climatic change, and warrants detailed monitoring to understand how different regions of the Arctic are responding to ongoing changes.

scholarly journals Recent changes in Pan-Arctic sea ice, lake ice, and snow on/off timing

2021 ◽  
Author(s):  
Alicia A. Dauginis ◽  
Laura C. Brown
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Climate Forcing ◽  
The Arctic ◽  
Lake Ice ◽  
Multiple Components ◽  
Mapping System ◽  
Snow And Ice

Abstract. Arctic snow and ice cover are vital indicators of climate variability and change, yet while the Arctic shows overall warming and dramatic changes in snow and ice cover, the response of these high-latitude regions to recent climatic change varies regionally. Although previous studies have examined changing snow and ice separately, examining phenology changes across multiple components of the cryosphere together is important for understanding how these components, and their response to climate forcing, are interconnected. In this work, we examine recent changes in sea ice, lake ice and snow together at the pan-Arctic scale using the Interactive Multisensor Snow and Ice Mapping System 24 km product from 1997–2019, with a more detailed regional examination from 2004–2019 using the 4 km product. We show overall that for sea ice, trends towards earlier open water (−7.7 d decade−1, p 

scholarly journals Retrieval of Summer Sea Ice Concentration in the Pacific Arctic Ocean from AMSR2 Observations and Numerical Weather Data Using Random Forest Regression

2021 ◽  
Vol 13 (12) ◽  
pp. 2283
Author(s):  
Hyangsun Han ◽  
Sungjae Lee ◽  
Hyun-Cheol Kim ◽  
Miae Kim
Keyword(s):  
Random Forest ◽  
Sea Ice ◽  
Arctic Ocean ◽  
Open Water ◽  
The Arctic ◽  
Atmospheric Effects ◽  
Sea Ice Concentration ◽  
Air Temperatures ◽  
The Pacific ◽  
Ice Concentration

The Arctic sea ice concentration (SIC) in summer is a key indicator of global climate change and important information for the development of a more economically valuable Northern Sea Route. Passive microwave (PM) sensors have provided information on the SIC since the 1970s by observing the brightness temperature (TB) of sea ice and open water. However, the SIC in the Arctic estimated by operational algorithms for PM observations is very inaccurate in summer because the TB values of sea ice and open water become similar due to atmospheric effects. In this study, we developed a summer SIC retrieval model for the Pacific Arctic Ocean using Advanced Microwave Scanning Radiometer 2 (AMSR2) observations and European Reanalysis Agency-5 (ERA-5) reanalysis fields based on Random Forest (RF) regression. SIC values computed from the ice/water maps generated from the Korean Multi-purpose Satellite-5 synthetic aperture radar images from July to September in 2015–2017 were used as a reference dataset. A total of 24 features including the TB values of AMSR2 channels, the ratios of TB values (the polarization ratio and the spectral gradient ratio (GR)), total columnar water vapor (TCWV), wind speed, air temperature at 2 m and 925 hPa, and the 30-day average of the air temperatures from the ERA-5 were used as the input variables for the RF model. The RF model showed greatly superior performance in retrieving summer SIC values in the Pacific Arctic Ocean to the Bootstrap (BT) and Arctic Radiation and Turbulence Interaction STudy (ARTIST) Sea Ice (ASI) algorithms under various atmospheric conditions. The root mean square error (RMSE) of the RF SIC values was 7.89% compared to the reference SIC values. The BT and ASI SIC values had three times greater values of RMSE (20.19% and 21.39%, respectively) than the RF SIC values. The air temperatures at 2 m and 925 hPa and their 30-day averages, which indicate the ice surface melting conditions, as well as the GR using the vertically polarized channels at 23 GHz and 18 GHz (GR(23V18V)), TCWV, and GR(36V18V), which accounts for atmospheric water content, were identified as the variables that contributed greatly to the RF model. These important variables allowed the RF model to retrieve unbiased and accurate SIC values by taking into account the changes in TB values of sea ice and open water caused by atmospheric effects.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

scholarly journals Ground ice in the Northern Foothills, northern Victoria Land, Antarctica

2004 ◽  
Vol 39 ◽  
pp. 495-500 ◽  
Author(s):  
Mauro Guglielmin ◽  
Hugh M. French
Keyword(s):  
Oxygen Isotope ◽  
Ross Sea ◽  
Progress Report ◽  
Ground Ice ◽  
Lake Ice ◽  
Near Surface ◽  
Victoria Land ◽  
Different Types ◽  
Glacier Ice ◽  
Surface Ice

AbstractThis progress report classifies the different types of ground-ice bodies that occur in the Northern Foothills, northern Victoria Land, Antarctica. Oxygen isotope variations are presented, but interpretation is kept to a minimum pending further investigations. Surface ice, as distinct from moving glacier ice, occurs in the form of widespread buried (‘dead’) glacier ice lying beneath ablation (sublimation) till, together with perennial lake ice, snow banks and icing-blister ice.’Dry’ permafrost is uncommon, and interstitial ice is usually present at the base of the active layer and in the near-surface permafrost. This probably reflects the supply of moisture from the Ross Sea and limited sublimation under today’s climate. Intrusive ice occurs as layers within perennial lake-ice covers and gives rise to small icing blisters. Small ice wedges found beneath the furrows of high-centered polygons appear to agree with the model of sublimation-till development proposed by Marchant and others (2002).

scholarly journals Ice-edge detection from Japanese C-band radar and high-frequency radar coastal stations

2013 ◽  
Vol 54 (62) ◽  
pp. 59-64 ◽  
Author(s):  
K. Shirasawa ◽  
N. Ebuchi ◽  
M. Leppäranta ◽  
T. Takatsuka
Keyword(s):  
Sea Ice ◽  
Edge Detection ◽  
High Frequency ◽  
Open Water ◽  
Radar Data ◽  
Hf Radar ◽  
Sea Surface ◽  
Geometrical Structures ◽  
Overlapping Data ◽  
Ice Edge

AbstractA C-band sea-ice radar (SIR) network system was operated to monitor the sea-ice conditions off the Okhotsk Sea coast of northern Hokkaido, Japan, from 1969 to 2004. The system was based on three radar stations, which were capable of continuously monitoring the sea surface as far as 60 km offshore along a 250 km long coastal section. In 2004 the SIR system was closed down and a sea surface monitoring programme was commenced using high-frequency (HF) radar; this system provides information on surface currents in open-water conditions, while areas with ‘no signal’ can be identified as sea ice. The present study compares HF radar data with SIR data to evaluate their feasibility for sea-ice remote sensing. The period of overlapping data was 1.5 months. The results show that HF radar information can be utilized for ice-edge mapping although it cannot fully compensate for the loss of the SIR system. In particular, HF radar does not provide ice concentration, ice roughness and geometrical structures or ice kinematics. The probability of ice-edge detection by HF radar was 0.9 and the correlation of the ice-edge distance between the radars was 0.7.

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