Assessment of Categorical Triple Collocation for Sea Ice/Open Water Observations: Application to the Gulf of Saint Lawrence

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.

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Sea Ice and Open Water Classification of SAR Images Using a Deep Learning Model

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss39084.2020.9323990 ◽

2020 ◽

Author(s):

Yibin Ren ◽

Huan Xu ◽

Bin Liu ◽

Xiaofeng Li

Keyword(s):

Deep Learning ◽

Sea Ice ◽

Open Water ◽

Learning Model ◽

Sar Images ◽

Water Classification ◽

Deep Learning Model

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

Atmosphere ◽

10.3390/atmos12020174 ◽

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.

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

Annals of Glaciology ◽

10.3189/2013aog62a007 ◽

2013 ◽

Vol 54 (62) ◽

pp. 59-64 ◽

Cited By ~ 2

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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Eddy covariance flux measurements of momentum, heat and carbon dioxide in Hudson Bay at the onset of sea ice melt

10.5194/egusphere-egu21-15711 ◽

2021 ◽

Author(s):

Richard Sims ◽

Brian Butterworth ◽

Tim Papakyriakou ◽

Mohamed Ahmed ◽

Brent Else

Keyword(s):

Carbon Dioxide ◽

Gas Exchange ◽

Sea Ice ◽

Eddy Covariance ◽

Open Water ◽

The Arctic ◽

Gas Transfer ◽

Hudson Bay ◽

Flux Measurements ◽

Ice Fraction

Remoteness and tough conditions have made the Arctic Ocean historically difficult to access; until recently this has resulted in an undersampling of trace gas and gas exchange measurements. The seasonal cycle of sea ice completely transforms the air sea interface and the dynamics of gas exchange. To make estimates of gas exchange in the presence of sea ice, sea ice fraction is frequently used to scale open water gas transfer parametrisations. It remains unclear whether this scaling is appropriate for all sea ice regions. Ship based eddy covariance measurements were made in Hudson Bay during the summer of 2018 from the icebreaker CCGS Amundsen. We will present fluxes of carbon dioxide (CO2), heat and momentum and will show how they change around the Hudson Bay polynya under varying sea ice conditions. We will explore how these fluxes change with wind speed and sea ice fraction. As freshwater stratification was encountered during the cruise, we will compare our measurements with other recent eddy covariance flux measurements made from icebreakers and also will compare our turbulent CO2&#160;fluxes with bulk fluxes calculated using underway and surface bottle pCO2&#160;data.&#160;&#160;

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Characteristics of The Seasonal Sea Ice of East Antarctica and Comparisons with Satellite Observations

Annals of Glaciology ◽

10.3189/s0260305500000446 ◽

1987 ◽

Vol 9 ◽

pp. 85-91 ◽

Cited By ~ 6

Author(s):

T.H. Jacka ◽

I. Allison ◽

R. Thwaites ◽

J.C. Wilson

Keyword(s):

Sea Ice ◽

Remote Sensing Data ◽

Ice Cores ◽

Open Water ◽

Early Spring ◽

Visual Channel ◽

Antarctic Waters ◽

Study Characteristics ◽

Satellite Sensors ◽

The Antarctic

A cruise to Antarctic waters from late October to mid December 1985 provided the opportunity to study characteristics of the seasonal sea ice from a time close to that of maximum extent through early spring decay. The area covered by the observations extends from the northern ice limit to the Antarctic coast between long. 50 °E and 80 E. Shipboard observations included ice extent, type and thickness, and snow depth. Ice cores were drilled at several sites, providing data on salinity and structure.The observations verify the highly dynamic and divergent nature of the Antarctic seasonal sea-ice 2one. Floe size and thickness varied greatly at all locations, although generally increasing from north to south. A high percentage of the total ice mass exhibited a frazil crystal structure, indicative of the existence of open water in the vicinity.The ground based observations are compared with observations from satellite sensors. The remote sensing data include the visual channel imagery from NOAA 6, NOAA 9, and Meteor 11. Comparisons are made with the operational ice charts produced (mainly from satellite data) by the Joint Ice Center, and with the analyses available by facsimile from Molodezhnaya.

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Airborne observations and simulations of three-dimensional radiative interactions between Arctic boundary layer clouds and ice floes

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-8147-2015 ◽

2015 ◽

Vol 15 (14) ◽

pp. 8147-8163 ◽

Cited By ~ 12

Author(s):

M. Schäfer ◽

E. Bierwirth ◽

A. Ehrlich ◽

E. Jäkel ◽

M. Wendisch

Keyword(s):

Boundary Layer ◽

Radiative Transfer ◽

Sea Ice ◽

Three Dimensional ◽

Open Water ◽

Radiative Effects ◽

Arctic Boundary Layer ◽

Boundary Layer Clouds ◽

Ice Edge ◽

Ice Floes

Abstract. Based on airborne spectral imaging observations, three-dimensional (3-D) radiative effects between Arctic boundary layer clouds and highly variable Arctic surfaces were identified and quantified. A method is presented to discriminate between sea ice and open water under cloudy conditions based on airborne nadir reflectivity γλ measurements in the visible spectral range. In cloudy cases the transition of γλ from open water to sea ice is not instantaneous but horizontally smoothed. In general, clouds reduce γλ above bright surfaces in the vicinity of open water, while γλ above open sea is enhanced. With the help of observations and 3-D radiative transfer simulations, this effect was quantified to range between 0 and 2200 m distance to the sea ice edge (for a dark-ocean albedo of αwater = 0.042 and a sea-ice albedo of αice = 0.91 at 645 nm wavelength). The affected distance Δ L was found to depend on both cloud and sea ice properties. For a low-level cloud at 0–200 m altitude, as observed during the Arctic field campaign VERtical Distribution of Ice in Arctic clouds (VERDI) in 2012, an increase in the cloud optical thickness τ from 1 to 10 leads to a decrease in Δ L from 600 to 250 m. An increase in the cloud base altitude or cloud geometrical thickness results in an increase in Δ L; for τ = 1/10 Δ L = 2200 m/1250 m in case of a cloud at 500–1000 m altitude. To quantify the effect for different shapes and sizes of ice floes, radiative transfer simulations were performed with various albedo fields (infinitely long straight ice edge, circular ice floes, squares, realistic ice floe field). The simulations show that Δ L increases with increasing radius of the ice floe and reaches maximum values for ice floes with radii larger than 6 km (500–1000 m cloud altitude), which matches the results found for an infinitely long, straight ice edge. Furthermore, the influence of these 3-D radiative effects on the retrieved cloud optical properties was investigated. The enhanced brightness of a dark pixel next to an ice edge results in uncertainties of up to 90 and 30 % in retrievals of τ and effective radius reff, respectively. With the help of Δ L, an estimate of the distance to the ice edge is given, where the retrieval uncertainties due to 3-D radiative effects are negligible.

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Albedo of Young and First-Year Antarctic Sea Ice

Annals of Glaciology ◽

10.1017/s0260305500008909 ◽

1990 ◽

Vol 14 ◽

pp. 331 ◽

Cited By ~ 2

Author(s):

Richard Brandt ◽

Ian Allison ◽

Stephen Warren

Keyword(s):

Sea Ice ◽

Radiation Flux ◽

Open Water ◽

First Year ◽

Spectral Measurements ◽

Antarctic Sea Ice ◽

Antarctic Expedition ◽

Downward Radiation ◽

Radiation Measurements ◽

Snow Thickness

Reflection of solar radiation was studied in the seasonal sea-ice zone off East Antarctica on a cruise of the Australian Antarctic Expedition, October-December 1988. Spectral and total albedos were measured for grease ice, nilas, young grey ice, grey-white ice, snow-covered ice, and open water. Spectral measurements covered the region 400–1000 nm wavelength. For ice too thin to support our weight, the radiometers were mounted at the end of a 1.5 m rod extended out the door of a helicopter or from a basket hung from the ship's crane, using a positioning and leveling rack. Corrections had to be applied to the downward radiation flux because the helicopter or the crane was in the field of view of the cosine-collector. The fractional coverage of each of the ice types (and open water) was estimated hourly for the region near the ship, as well as the thickness of each ice type, and the snow thickness. Observations were carried out continuously during the four weeks the ship was in the ice, supplemented by occasional helicopter surveys covering larger areas. These observations, together with the radiation measurements, make possible the computation of area-average albedo for the East Antarctic sea-ice zone in spring.

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Optical properties of ice and snow

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2018.0161 ◽

2019 ◽

Vol 377 (2146) ◽

pp. 20180161 ◽

Cited By ~ 19

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’.

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