scholarly journals Open-source algorithm for detecting sea ice surface features in high-resolution optical imagery

2018 ◽  
Vol 12 (4) ◽  
pp. 1307-1329 ◽  
Author(s):  
Nicholas C. Wright ◽  
Chris M. Polashenski
Keyword(s):  
Sea Ice ◽  
Open Source ◽  
Surface Coverage ◽  
Open Water ◽  
The Arctic ◽  
Source Distribution ◽  
Ice Melt ◽  
Observation Area ◽  
Melt Ponds ◽  
Optical Imagery

Abstract. Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available meter- to decimeter-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open-source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open-source distribution of this algorithm and associated training datasets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

scholarly journals Open Source Algorithm for Detecting Sea Ice Surface Features in High Resolution Optical Imagery

2017 ◽  
Author(s):  
Nicholas C. Wright ◽  
Christopher M. Polashenski
Keyword(s):  
Sea Ice ◽  
Open Source ◽  
Surface Coverage ◽  
Open Water ◽  
Training Data ◽  
The Arctic ◽  
Source Distribution ◽  
Observation Area ◽  
Melt Ponds ◽  
Optical Imagery

Abstract. Snow, ice, and melt ponds cover the surface of the Arctic Ocean in fractions that change throughout the seasons. These surfaces control albedo and exert tremendous influence over the energy balance in the Arctic. Increasingly available m- to dm-scale resolution optical imagery captures the evolution of the ice and ocean surface state visually, but methods for quantifying coverage of key surface types from raw imagery are not yet well established. Here we present an open source system designed to provide a standardized, automated, and reproducible technique for processing optical imagery of sea ice. The method classifies surface coverage into three main categories: Snow and bare ice, melt ponds and submerged ice, and open water. The method is demonstrated on imagery from four sensor platforms and on imagery spanning from spring thaw to fall freeze-up. Tests show the classification accuracy of this method typically exceeds 96 %. To facilitate scientific use, we evaluate the minimum observation area required for reporting a representative sample of surface coverage. We provide an open source distribution of this algorithm and associated training data sets and suggest the community consider this a step towards standardizing optical sea ice imagery processing. We hope to encourage future collaborative efforts to improve the code base and to analyze large datasets of optical sea ice imagery.

scholarly journals The impact of melt ponds on summertime microwave brightness temperatures and sea ice concentrations

2016 ◽  
Author(s):  
S. Kern ◽  
A. Rösel ◽  
L. T. Pedersen ◽  
N. Ivanova ◽  
R. Saldo ◽  
...  
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Water Fraction ◽  
Microwave Brightness Temperature ◽  
Ice Melt ◽  
Melt Ponds ◽  
Retrieval Algorithms ◽  
The Impact

Abstract. The sea ice concentration (SIC) derived from satellite microwave brightness temperature (TB) data are known to be less accurate during summer melt conditions – in the Arctic Ocean primarily because of the impact of melt ponds on sea ice. Using data from June to August 2009, we investigate how TBs and SICs vary as a function of the ice surface fraction (ISF) computed from open water fraction and melt pond fraction both derived from satellite optical reflectance data. SIC is computed from TBs using a set of eight different retrieval algorithms and applying a consistent set of tie points. We find that TB values change during sea ice melt non-linearly and not monotonically as a function of ISF for ISF of 50 to 100 %. For derived parameters such as the polarization ratio at 19 GHz the change is monotonic but substantially smaller than theoretically expected. Changes in ice/snow radiometric properties during melt also contribute to the TB changes observed; these contributions are functions of frequency and polarization and have the potential to partly counter-balance the impact of changing ISF on the observed TBs. All investigated SIC retrieval algorithms overestimate ISF when using winter tie points. The overestimation varies among the algorithms as a function of ISF such that the SIC retrieval algorithms could be categorized into two different classes. These reveal a different degree of ISF overestimation at high ISF and an opposite development of ISF over-estimation as ISF decreases. For one class, correlations between SIC and ISF are ≥ 0.85 and the associated linear regression lines suggest an exploitable relationship between SIC and ISF if reliable summer sea ice tie points can be established. This study shows that melt ponds are interpreted as open water by the SIC algorithms, while the concentration of ice between the melt ponds is in general being overestimated. These two effects may cancel each other out and thus produce seemingly correct SIC for the wrong reasons. This cancelling effect will in general only be "correct" at one specific value of MPF. Based on our findings we recommend to not correct SIC algorithms for the impact of melt ponds as this seems to violate physical principles. Users should be aware that the SIC algorithms available at the moment retrieve a combined parameter presented by SIC in winter and ISF in summer.

scholarly journals Determination of areal surface-feature coverage in the Beaufort Sea using aircraft video data

1997 ◽  
Vol 25 ◽  
pp. 434-438 ◽  
Author(s):  
Mark A. Tschudi ◽  
Judith A. Curry ◽  
James A. Maslanik
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Video Camera ◽  
Surface Feature ◽  
Video Data ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Areal Coverage ◽  
Melt Ponds

The surface-energy budget of the Arctic Ocean depends on the distribution of various sea-ice features that form by both mechanical and thermodynamic processes. Melt ponds, new ice and open water greatly affect the determination of surface albedo. However, even basic measurements of some surface-feature characteristics, such as areal extent of melt ponds, remain rare.A method has been developed to assess the areal coverage of melt ponds, new ice and open water using video data from the Beaufort and Arctic Storms Experiment (BASE). A downward-looking video camera mounted on the underside of a Hercules C-130 aircraft provided clear images of the surface. Images acquired over multi-year ice on 21 September 1994 were analyzed using a spectral technique to determine the areal coverage of melt ponds, new ice and open water. Statistics from this analysis were then compared to previous field studies and to the Schramm and others (in press) sea-ice model.

scholarly journals Arctic sea-ice conditions and the distribution of solar radiation during summer

1997 ◽  
Vol 25 ◽  
pp. 445-450 ◽  
Author(s):  
Donald K. Perovich ◽  
Walter B. Tucker
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Feedback Mechanism ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Melt Ponds ◽  
Arctic Ice ◽  
Median Area

Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.

scholarly journals Regional melt-pond fraction and albedo of thin Arctic first-year drift ice in late summer

2015 ◽  
Vol 9 (1) ◽  
pp. 255-268 ◽  
Author(s):  
D. V. Divine ◽  
M. A. Granskog ◽  
S. R. Hudson ◽  
C. A. Pedersen ◽  
T. I. Karlsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Surface Type ◽  
Melt Pond ◽  
Melt Ponds

Abstract. The paper presents a case study of the regional (≈150 km) morphological and optical properties of a relatively thin, 70–90 cm modal thickness, first-year Arctic sea ice pack in an advanced stage of melt. The study combines in situ broadband albedo measurements representative of the four main surface types (bare ice, dark melt ponds, bright melt ponds and open water) and images acquired by a helicopter-borne camera system during ice-survey flights. The data were collected during the 8-day ICE12 drift experiment carried out by the Norwegian Polar Institute in the Arctic, north of Svalbard at 82.3° N, from 26 July to 3 August 2012. A set of > 10 000 classified images covering about 28 km2 revealed a homogeneous melt across the study area with melt-pond coverage of ≈ 0.29 and open-water fraction of ≈ 0.11. A decrease in pond fractions observed in the 30 km marginal ice zone (MIZ) occurred in parallel with an increase in open-water coverage. The moving block bootstrap technique applied to sequences of classified sea-ice images and albedo of the four surface types yielded a regional albedo estimate of 0.37 (0.35; 0.40) and regional sea-ice albedo of 0.44 (0.42; 0.46). Random sampling from the set of classified images allowed assessment of the aggregate scale of at least 0.7 km2 for the study area. For the current setup configuration it implies a minimum set of 300 images to process in order to gain adequate statistics on the state of the ice cover. Variance analysis also emphasized the importance of longer series of in situ albedo measurements conducted for each surface type when performing regional upscaling. The uncertainty in the mean estimates of surface type albedo from in situ measurements contributed up to 95% of the variance of the estimated regional albedo, with the remaining variance resulting from the spatial inhomogeneity of sea-ice cover.

scholarly journals Dimethylsulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago

2017 ◽  
Author(s):  
Margaux Gourdal ◽  
Martine Lizotte ◽  
Guillaume Massé ◽  
Michel Gosselin ◽  
Michael Scarratt ◽  
...  
Keyword(s):  
Sea Ice ◽  
Canadian Arctic ◽  
The Arctic ◽  
First Year ◽  
Canadian Arctic Archipelago ◽  
Ice Melt ◽  
Melt Pond ◽  
Potential Source ◽  
Melt Ponds ◽  
Cover Up

Abstract. Melt pond formation is a natural seasonal pan-Arctic process. During the thawing season, melt ponds may cover up to 90 % of the Arctic first year sea ice (FYI) and 15 to 25 % of the multi-year sea ice (MYI). These pools of water lying at the surface of the sea-ice cover are habitats for microorganisms and represent a potential source of the biogenic gas dimethylsulfide (DMS) for the atmosphere. Here we report on the concentrations and dynamics of DMS in nine melt ponds sampled in July 2014 in the Eastern Canadian Arctic. DMS concentrations were under the detection limit (

scholarly journals Inorganic carbon dynamics of melt pond-covered first year sea ice in the Canadian Arctic

2014 ◽  
Vol 11 (5) ◽  
pp. 7485-7519 ◽  
Author(s):  
N.-X. Geilfus ◽  
R. J. Galley ◽  
O. Crabeck ◽  
T. Papakyriakou ◽  
J. Landy ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Melt Ponds ◽  
Arctic Sea ◽  
Melt Water

Abstract. Melt pond formation is a common feature of the spring and summer Arctic sea ice. However, the role of the melt ponds formation and the impact of the sea ice melt on both the direction and size of CO2 flux between air and sea is still unknown. Here we describe the CO2-carbonate chemistry of melting sea ice, melt ponds and the underlying seawater associated with measurement of CO2 fluxes across first year landfast sea ice in the Resolute Passage, Nunavut, in June 2012. Early in the melt season, the increase of the ice temperature and the subsequent decrease of the bulk ice salinity promote a strong decrease of the total alkalinity (TA), total dissolved inorganic carbon (TCO2) and partial pressure of CO2 (pCO2) within the bulk sea ice and the brine. Later on, melt pond formation affects both the bulk sea ice and the brine system. As melt ponds are formed from melted snow the in situ melt pond pCO2 is low (36 μatm). The percolation of this low pCO2 melt water into the sea ice matrix dilutes the brine resulting in a strong decrease of the in situ brine pCO2 (to 20 μatm). As melt ponds reach equilibrium with the atmosphere, their in situ pCO2 increase (up to 380 μatm) and the percolation of this high concentration pCO2 melt water increase the in situ brine pCO2 within the sea ice matrix. The low in situ pCO2 observed in brine and melt ponds results in CO2 fluxes of −0.04 to −5.4 mmol m–2 d–1. As melt ponds reach equilibrium with the atmosphere, the uptake becomes less significant. However, since melt ponds are continuously supplied by melt water their in situ pCO2 still remains low, promoting a continuous but moderate uptake of CO2 (~ −1mmol m–2 d–1). The potential uptake of atmospheric CO2 by melting sea ice during the Arctic summer has been estimated from 7 to 16 Tg of C ignoring the role of melt ponds. This additional uptake of CO2 associated to Arctic sea ice needs to be further explored and considered in the estimation of the Arctic Ocean's overall CO2 budget.

scholarly journals The Potential of Space-Based Sea Surface Salinity on Monitoring the Hudson Bay Freshwater Cycle

2020 ◽  
Vol 12 (5) ◽  
pp. 873 ◽  
Author(s):  
Wenqing Tang ◽  
Simon H. Yueh ◽  
Daqing Yang ◽  
Ellie Mcleod ◽  
Alexander Fore ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Sea Ice ◽  
River Discharge ◽  
Open Water ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
The Arctic ◽  
Hudson Bay ◽  
Surface Salinity ◽  
Ice Melt

Hudson Bay (HB) is the largest semi-inland sea in the Northern Hemisphere, connecting with the Arctic Ocean through the Foxe Basin and the northern Atlantic Ocean through the Hudson Strait. HB is covered by ice and snow in winter, which completely melts in summer. For about six months each year, satellite remote sensing of sea surface salinity (SSS) is possible over open water. SSS links freshwater contributions from river discharge, sea ice melt/freeze, and surface precipitation/evaporation. Given the strategic importance of HB, SSS has great potential in monitoring the HB freshwater cycle and studying its relationship with climate change. However, SSS retrieved in polar regions (poleward of 50°) from currently operational space-based L-band microwave instruments has large uncertainty (~ 1 psu) mainly due to sensitivity degradation in cold water (<5°C) and sea ice contamination. This study analyzes SSS from NASA Soil Moisture Active and Passive (SMAP) and European Space Agency (ESA) Soil Moisture and Ocean Salinity(SMOS) missions in the context of HB freshwater contents. We found that the main source of the year-to-year SSS variability is sea ice melting, in particular, the onset time and places of ice melt in the first couple of months of open water season. The freshwater contribution from surface forcing P-E is smaller in magnitude comparing with sea ice contribution but lasts on longer time scale through the whole open water season. River discharge is comparable with P-E in magnitude but peaks before ice melt. The spatial and temporal variations of freshwater contents largely exceed the remote sensed SSS uncertainty. This fact justifies the use of remote sensed SSS for monitoring the HB freshwater cycle.

scholarly journals Arctic sea-ice conditions and the distribution of solar radiation during summer

1997 ◽  
Vol 25 ◽  
pp. 445-450 ◽  
Author(s):  
Donald K. Perovich ◽  
Walter B. Tucker
Keyword(s):  
Solar Radiation ◽  
Sea Ice ◽  
Open Water ◽  
Ice Cover ◽  
Feedback Mechanism ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Melt Ponds ◽  
Arctic Ice ◽  
Median Area

Understanding the interaction of solar radiation with the ice cover is critical in determining the heat and mass balance of the Arctic ice pack, and in assessing potential impacts due to climate change. Because of the importance of the ice-albedo feedback mechanism, information on the surface state of the ice cover is needed. Observations of the surface slate of sea ice were obtained from helicopter photography missions made during the 1994 Arctic Ocean Section cruise. Photographs from one flight, taken during the height of the melt season (31 July 1994) at 76° N, 172° W, were analyzed in detail. Bare ice covered 82% of the total area, melt ponds 12%, and open water 6%, There was considerable variability in these area fractions on scales < 1 km2. Sample areas >2 3 km2 gave representative values of ice concentration and pond fraction. Melt ponds were numerous, with a number density of 1800 ponds km-2. The melt ponds had a mean area of 62 m2 a median area of 14 m2, and a size distribution that was well lit by a cumulative lognormal distribution. While leads make up only a small portion of the total area, they are the source of virtually all of the solar energy input to the ocean.

scholarly journals Dimethyl sulfide dynamics in first-year sea ice melt ponds in the Canadian Arctic Archipelago

2018 ◽  
Vol 15 (10) ◽  
pp. 3169-3188 ◽  
Author(s):  
Margaux Gourdal ◽  
Martine Lizotte ◽  
Guillaume Massé ◽  
Michel Gosselin ◽  
Michel Poulin ◽  
...  
Keyword(s):  
Sea Ice ◽  
Dimethyl Sulfide ◽  
De Novo ◽  
Canadian Arctic ◽  
The Arctic ◽  
First Year ◽  
Canadian Arctic Archipelago ◽  
Ice Melt ◽  
Melt Ponds ◽  
Arctic Atmosphere

Abstract. Melt pond formation is a seasonal pan-Arctic process. During the thawing season, melt ponds may cover up to 90 % of the Arctic first-year sea ice (FYI) and 15 to 25 % of the multi-year sea ice (MYI). These pools of water lying at the surface of the sea ice cover are habitats for microorganisms and represent a potential source of the biogenic gas dimethyl sulfide (DMS) for the atmosphere. Here we report on the concentrations and dynamics of DMS in nine melt ponds sampled in July 2014 in the Canadian Arctic Archipelago. DMS concentrations were under the detection limit (< 0.01 nmol L−1) in freshwater melt ponds and increased linearly with salinity (rs = 0.84, p ≤ 0.05) from ∼ 3 up to ∼ 6 nmol L−1 (avg. 3.7 ± 1.6 nmol L−1) in brackish melt ponds. This relationship suggests that the intrusion of seawater in melt ponds is a key physical mechanism responsible for the presence of DMS. Experiments were conducted with water from three melt ponds incubated for 24 h with and without the addition of two stable isotope-labelled precursors of DMS (dimethylsulfoniopropionate), (D6-DMSP) and dimethylsulfoxide (13C-DMSO). Results show that de novo biological production of DMS can take place within brackish melt ponds through bacterial DMSP uptake and cleavage. Our data suggest that FYI melt ponds could represent a reservoir of DMS available for potential flux to the atmosphere. The importance of this ice-related source of DMS for the Arctic atmosphere is expected to increase as a response to the thinning of sea ice and the areal and temporal expansion of melt ponds on Arctic FYI.

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