Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation

Abstract. In the context of quantifying Arctic ice-volume decrease at global scale, the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku band synthetic aperture radar altimeter SIRAL (Synthetic Aperture Interferometric Radar Altimeter), which we use to derive sea-ice freeboard defined as the height of the ice surface above the sea level. Accurate CryoSat-2 range measurements over open water and the ice surface of the order of centimetres are necessary to achieve the required accuracy of the freeboard-to-thickness conversion. Besides uncertainties of the actual sea-surface height and limited knowledge of ice and snow properties, the composition of radar backscatter and therefore the interpretation of radar echoes is crucial. This has consequences in the selection of retracker algorithms which are used to track the main scattering horizon and assign a range estimate to each CryoSat-2 measurement. In this study we apply a retracker algorithm with thresholds of 40, 50 and 80% of the first maximum of radar echo power, spanning the range of values used in the current literature. By using the selected retrackers and additionally results from airborne validation measurements, we evaluate the uncertainties of sea-ice freeboard and higher-level products that arise from the choice of the retracker threshold only, independent of the uncertainties related to snow and ice properties. Our study shows that the choice of retracker thresholds does have a significant impact on magnitudes of estimates of sea-ice freeboard and thickness, but that the spatial distributions of these parameters are less affected. Specifically we find mean radar freeboard values of 0.121 m (0.265 m) for the 40% threshold, 0.086 m (0.203 m) for the 50% threshold and 0.024 m (0.092 m) for the 80% threshold, considering first-year ice (multiyear ice) in March 2013. We show that the main source of freeboard and thickness uncertainty results from the choice of the retracker and the unknown penetration of the radar pulse into the snow layer in conjunction with surface roughness effects. These uncertainties can cause a freeboard bias of roughly 0.06–0.12 m. Furthermore we obtain a significant rise of 0.02–0.15 m of freeboard from March 2013 to November 2013 in the area for multiyear sea ice north of Greenland and Canada. Since this is unlikely, it gives rise to the assumption that applying different retracker thresholds depending on seasonal properties of the snow load is necessary in the future.

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Sensitivity of CryoSat-2 Arctic sea-ice volume trends on radar-waveform interpretation

The Cryosphere Discussions ◽

10.5194/tcd-8-1831-2014 ◽

2014 ◽

Vol 8 (2) ◽

pp. 1831-1871 ◽

Cited By ~ 4

Author(s):

R. Ricker ◽

S. Hendricks ◽

V. Helm ◽

H. Skourup ◽

M. Davidson

Keyword(s):

Sea Ice ◽

Sea Level ◽

Global Scale ◽

Arctic Sea Ice ◽

Radar Altimeter ◽

Ice Volume ◽

Ice Surface ◽

Arctic Sea ◽

Volume Decrease ◽

Ku Band

Abstract. Several studies have shown that there is considerable evidence that the Arctic sea-ice is thinning during the last decades. When combined with the observed rapid reduction of ice-covered area this leads to a decline in sea-ice volume. The only remote sensing technique capable of quantifying this ice volume decrease at global scale is satellite altimetry. In this context the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku-band SAR radar altimeter SIRAL, which we use to derive sea-ice freeboard defined as the height of the ice surface above the local sea level. In the context of quantifying Arctic ice-volume decrease at global scale, the CryoSat-2 satellite was launched in 2010 and is equipped with the Ku-band SAR radar altimeter SIRAL, which we use to derive sea-ice freeboard defined as the height of the ice surface above the sea level. Accurate CryoSat-2 range measurements over open water and the ice surface in the order of centimeters are necessary to achieve the required accuracy of the freeboard to thickness conversion. Besides uncertainties of the actual sea-surface height and limited knowledge of ice and snow properties, the penetration of the radar signal into the snow cover and therefore the interpretation of radar echoes is crucial. This has consequences in the selection of retracker algorithms which are used to track the main scattering horizon and assign a range estimate to each CryoSat measurement. In this paper we apply a retracker algorithm with thresholds of 40%, 50% and 80% of the first maximum of radar echo power, spanning the range of values used in current literature. For the 40% threshold we assume that the main scattering horizon lies at a certain depth between the surface and snow-ice interface as verified through coincident CryoSat-2 and airborne laser altimetry measurements. This contrasts with the 50% and 80% thresholds where we assume the ice-snow interface as the main scattering horizon similar to other published studies. Using the selected retrackers we evaluate the uncertainties of trends in sea-ice freeboard and higher level products that arise from the choice of the retracker threshold only, independently from the uncertainties related to snow and ice properties. Our study shows that the choice of retracker thresholds does have a non-negligible impact on magnitude estimates of sea-ice freeboard, thickness and volume, but that the main trends in these parameters are less affected. Specifically we find declines of Arctic sea-ice volume of 9.7% (40% threshold), 10.9% (50% threshold) and 6.9% (80% threshold) between March 2011 and March 2013. In contrast to that we find increases in Arctic sea-ice volume of 27.88% (40% threshold), 25.71% (50% threshold) and 32.65% (80% threshold) between November 2011 and November 2013. Furthermore we obtain a significant increase of freeboard from March 2013 to November 2013 in the area for multi-seasonal sea-ice north of Greenland and the Canadian Archipelago. Since this is unlikely it gives rise to the assumption that applying different retracker thresholds depending on seasonal properties of the snow load is necessary in the future.

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Relationship between specular returns in CryoSat-2 data, surface albedo, and Arctic summer minimum ice extent

Elem Sci Anth ◽

10.1525/elementa.311 ◽

2018 ◽

Vol 6 ◽

Cited By ~ 1

Author(s):

R. Kwok ◽

G. F. Cunningham ◽

T. W. K. Armitage

Keyword(s):

Sea Ice ◽

Large Scale ◽

Relative Rate ◽

Open Water ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Radar Altimeter ◽

Ice Surface ◽

Summer Minimum

Specular (mirror-like) reflections in radar altimeter returns are sensitive indicators of flat open water in leads and melt ponds within the Arctic sea ice cover. Here we find increased specular and near-specular returns in CryoSat-2 waveforms as the sea ice cover transitions from a high albedo snow-covered surface to a lower albedo surface dominated by ponds from snow melt. During early melt, mid-May to late June, increases in fractional coverage of specular returns (FSR) show spatial correspondence with concurrent decreases in albedo. To examine the utility of FSR, we compared its efficacy with that of satellite-derived albedo in forecasting summer minimum ice extent (SMIE). Regression analysis of the area-averaged FSR (F—SR\documentclass[10pt]{article}\usepackage{wasysym}\usepackage[substack]{amsmath}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage[mathscr]{eucal}\usepackage{mathrsfs}\usepackage{pmc}\usepackage[Euler]{upgreek}\pagestyle{empty}\oddsidemargin -1.0in\begin{document}\[{\bar F}_{SR}\]\end{document}) (2011–2017) shows that ~72% of SMIE variance can be explained by the dates when F—SR\documentclass[10pt]{article}\usepackage{wasysym}\usepackage[substack]{amsmath}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage[mathscr]{eucal}\usepackage{mathrsfs}\usepackage{pmc}\usepackage[Euler]{upgreek}\pagestyle{empty}\oddsidemargin -1.0in\begin{document}\[{\bar F}_{SR}\]\end{document} climbs to 0.5 within two latitudinal bands covering 70–80°N and 80–90°N. The lag between the two crossing dates provides a measure of the relative rate of the poleward progression of melt. Approximately 93% of SMIE variance can be explained by the date when albedo drops to 0.6 in these same latitudinal bands. Standard errors for these regressions are 0.37 and 0.19 × 106 km2, respectively. Calculating the regression coefficients using only 2011–2016, the 2017 SMIE was forecast with residuals of 0.06 (2% of the total extent) and –0.17 × 106 km2 (4%). Using only 2011–2015 yielded residuals that are less than 0.5 × 106 km2 (~10%) in forecasts of both 2016 and 2017 SMIE, demonstrating the robustness of the regression models. Even though large-scale changes in albedo during summer melt is a characteristic feature of the ice surface, available albedo fields have not been directly used in SMIE forecasts. While this CryoSat-2 record is short, these results suggest that both FSR and albedo could be potentially useful for enhancing forecasts of SMIE.

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Consistent ice and open water classification combining historical synthetic aperture radar satellite images from ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1A/B

Annals of Glaciology ◽

10.1017/aog.2019.52 ◽

2020 ◽

Vol 61 (82) ◽

pp. 40-50 ◽

Cited By ~ 1

Author(s):

A. Malin Johansson ◽

Eirik Malnes ◽

Sebastian Gerland ◽

Anca Cristea ◽

Anthony P. Doulgeris ◽

...

Keyword(s):

Sea Ice ◽

Synthetic Aperture Radar ◽

Satellite Images ◽

Satellite Image ◽

Open Water ◽

Ice Cover ◽

Arctic Sea Ice ◽

Synthetic Aperture ◽

Envisat Asar ◽

Aperture Radar

AbstractSynthetic Aperture Radar (SAR) satellite images are used to monitor Arctic sea ice, with systematic data records dating back to 1991. We propose a semi-supervised classification method that separates open water from sea ice and can utilise ERS-1/2, Envisat ASAR, RADARSAT-2 and Sentinel-1 SAR images. The classification combines automatic segmentation with a manual segment selection stage. The segmentation algorithm requires only the backscatter intensities and incidence angle values as input, therefore can be used to establish a consistent decadal sea ice record. In this study we investigate the sea ice conditions in two Svalbard fjords, Kongsfjorden and Rijpfjorden. Both fjords have a seasonal ice cover, though Rijpfjorden has a longer sea ice season. The satellite image dataset has weekly to daily records from 2002 until now, and less frequent records between 1991 and 2002. Time overlap between different sensors is investigated to ensure consistency in the reported sea ice cover. The classification results have been compared to high-resolution SAR data as well as in-situ measurements and sea ice maps from Ny-Ålesund. For both fjords the length of the sea ice season has shortened since 2002 and for Kongsfjorden the maximum sea ice coverage is significantly lower after 2006.

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Seasonal changes in Arctic sea-ice morphology

Annals of Glaciology ◽

10.3189/172756401781818716 ◽

2001 ◽

Vol 33 ◽

pp. 171-176 ◽

Cited By ~ 16

Author(s):

Donald K. Perovich ◽

Jacqueline A. Richter-Menge ◽

Walter B. Tucker

Keyword(s):

Sea Ice ◽

Heat Budget ◽

Open Water ◽

Ice Cover ◽

Arctic Sea Ice ◽

The Arctic ◽

Ice Surface ◽

Arctic Sea ◽

Dynamic Forcing ◽

Break Up

AbstractThe morphology of the Arctic sea-ice cover undergoes large changes over an annual cycle. These changes have a significant impact on the heat budget of the ice cover, primarily by affecting the distribution of the solar radiation absorbed in the ice-ocean system. In spring, the ice is snow-covered and ridges are the prominent features. The pack consists of large angular floes, with a small amount of open water contained primarily in linear leads. By the end of summer the ice cover has undergone a major transformation. The snow cover is gone, many of the ridges have been reduced to hummocks and the ice surface is mottled with melt ponds. One surface characteristic that changes little during the summer is the appearance of the bare ice, which remains white despite significant melting. The large floes have broken into a mosaic of smaller, rounded floes surrounded by a lace of open water. Interestingly, this break-up occurs during summer when the dynamic forcing and the internal ice stress are small During the Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment we had an opportunity to observe the break-up process both on a small scale from the ice surface, and on a larger scale via aerial photographs. Floe break-up resulted in large part from thermal deterioration of the ice. The large floes of spring are riddled with cracks and leads that formed and froze during fall, winter and spring. These features melt open during summer, weakening the ice so that modest dynamic forcing can break apart the large floes into many fragments. Associated with this break-up is an increase in the number of floes, a decrease in the size of floes, an increase in floe perimeter and an increase in the area of open water.

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Sea ice local surface topography from single-pass satellite InSAR measurements: a feasibility study

10.5194/tc-2017-40 ◽

2017 ◽

Author(s):

Wolfgang Dierking ◽

Oliver Lang ◽

Thomas Busche

Keyword(s):

Sea Ice ◽

Surface Topography ◽

Signal To Noise Ratio ◽

Open Water ◽

Satellite Orbit ◽

Snow Layer ◽

Single Pass ◽

Ice Surface ◽

Ice Drift ◽

Relative Errors

Abstract. Quantitative parameters characterizing the sea ice surface topography are needed in geophysical investigations such as studies on atmosphere-ice interactions or sea ice mechanics. Recently, the use of space-borne single-pass interferometric synthetic aperture radar (InSAR) for retrieving the ice surface topography has attracted notice among geophysicists. In this paper the potential of InSAR measurements is examined for several satellite configurations and radar frequencies, considering statistics of heights and widths of ice ridges as well as possible magnitudes of ice drift. It is shown that theoretically surface height variations can be retrieved with relative errors ≤ 0.5 m. In practice, however, the sea ice drift and open water leads may contribute significantly to the measured interferometric phase. Another essential factor is the dependence of the achievable interferometric baseline on the satellite orbit configurations. Possibilities to assess the influence of different factors on the measurement accuracy are demonstrated: signal-to-noise ratio, presence of a snow layer, and the penetration depth into the ice. Practical examples of sea surface height retrievals from bistatic SAR images collected during the TanDEM-X Science Phase are presented.

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Investigating how platform height affects sea ice radar returns with KuKaSim

10.5194/egusphere-egu21-11311 ◽

2021 ◽

Author(s):

Thomas Newman ◽

Rosemary Willatt ◽

Julienne Stroeve ◽

Robbie Mallet ◽

Michel Tsamados ◽

...

Keyword(s):

Surface Morphology ◽

Sea Ice ◽

Arctic Sea Ice ◽

Airborne Lidar ◽

Ice Thickness ◽

Radar Altimeter ◽

Sea Ice Thickness ◽

Ice Surface ◽

Arctic Sea ◽

Airborne Lidar Data

<p>Current, and ongoing observations, of Arctic sea ice, indicate a trend towards a younger, thinner and more mobile pack that exhibits significant inter-annual variability. Satellite and airborne radar altimeters have been used extensively to quantify these changes by deriving sea ice freeboard to infer sea ice thickness. Radar returns from altimeters are impacted by both the morphology of snow and ice features on the sea ice surface, in addition to the radar properties of the snowpack, with both contributing to uncertainties in radar-derived sea ice freeboard. Here we make use of airborne lidar data, collected as part of the MOSAiC expedition in the winter of 2019/2020, to investigate the effect of sea ice surface morphology on radar altimeter measurements. We quantify these effects using 'KuKaSim' a forward-modelling approach based on the KuKa instrument deployed at MOSAiC, which allows us to investigate how simulated radar returns vary with radar height. Our results allow us to better constrain the altimetric uncertainty resulting from ice surface morphology, with respect to both radar height and sea ice type, leading to an enhanced understanding of sources of uncertainty in altimeter-derived sea ice thickness products.</p>

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Waveform classification of airborne synthetic aperture radar altimeter over Arctic sea ice

The Cryosphere ◽

10.5194/tc-7-1315-2013 ◽

2013 ◽

Vol 7 (4) ◽

pp. 1315-1324 ◽

Cited By ~ 25

Author(s):

M. Zygmuntowska ◽

K. Khvorostovsky ◽

V. Helm ◽

S. Sandven

Keyword(s):

Sea Ice ◽

Synthetic Aperture Radar ◽

Arctic Sea Ice ◽

Synthetic Aperture ◽

The Arctic ◽

Ice Thickness ◽

Radar Altimeter ◽

Sea Ice Thickness ◽

Ku Band ◽

Aperture Radar

Abstract. Sea ice thickness is one of the most sensitive variables in the Arctic climate system. In order to quantify changes in sea ice thickness, CryoSat-2 was launched in 2010 carrying a Ku-band radar altimeter (SIRAL) designed to measure sea ice freeboard with a few centimeters accuracy. The instrument uses the synthetic aperture radar technique providing signals with a resolution of about 300 m along track. In this study, airborne Ku-band radar altimeter data over different sea ice types have been analyzed. A set of parameters has been defined to characterize the differences in strength and width of the returned power waveforms. With a Bayesian-based method, it is possible to classify about 80% of the waveforms from three parameters: maximum of the returned power waveform, the trailing edge width and pulse peakiness. Furthermore, the maximum of the power waveform can be used to reduce the number of false detections of leads, compared to the widely used pulse peakiness parameter. For the pulse peakiness the false classification rate is 12.6% while for the power maximum it is reduced to 6.5%. The ability to distinguish between different ice types and leads allows us to improve the freeboard retrieval and the conversion from freeboard into sea ice thickness, where surface type dependent values for the sea ice density and snow load can be used.

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Bacterial Production in the Bottom Surface of Sea Ice in the Canadian Subarctic

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f90-223 ◽

1990 ◽

Vol 47 (10) ◽

pp. 1986-1995 ◽

Cited By ~ 24

Author(s):

J. N. Bunch ◽

R. C. Harland

Keyword(s):

Organic Carbon ◽

Sea Ice ◽

Open Water ◽

Arctic Sea Ice ◽

Trophic Levels ◽

Bottom Surface ◽

First Year ◽

Bacterial Assemblage ◽

Ice Surface ◽

Arctic Sea

Standing stocks of bacteria in the bottom of first-year sea ice at Frobisher Bay, N.W.T., increased fivefold between March and May (1985 and 1986) and constituted up to 5% of particulate organic carbon (POC). Autoradiography demonstrated that approximately one-third of the bacterial assemblage incorporated radioactive thymidine. The mean volume of cells was six times larger than that in the underlying water, and the assemblage was dominated by rod-shaped cells rather than the coccus-shaped cells prevalent in the water column. Bacterial carbon production by 3H-thymidine incorporation amounted to 0.04 mg carbon m−2∙h−1, or a doubling time of about 22 h, in the bottom ice surface and 0.01 mg carbon m−3∙h−1 in the underlying water. The concentration of dissolved organic carbon (DOC) was generally much higher in the bottom ice surface than in the underlying water, and was closely related to rate of cell production. A model of bacterial dependancy on DOC derived from primary production suggests that bacteria are important in the localized production of POC in the bottom of arctic sea ice, and contribute to an early source of nutrition for higher trophic levels before summer production in open water.

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Sea ice local surface topography from single-pass satellite InSAR measurements: a feasibility study

The Cryosphere ◽

10.5194/tc-11-1967-2017 ◽

2017 ◽

Vol 11 (4) ◽

pp. 1967-1985 ◽

Cited By ~ 12

Author(s):

Wolfgang Dierking ◽

Oliver Lang ◽

Thomas Busche

Keyword(s):

Sea Ice ◽

Surface Topography ◽

Signal To Noise Ratio ◽

Open Water ◽

Satellite Orbit ◽

Snow Layer ◽

Single Pass ◽

Ice Surface ◽

Ice Drift ◽

Relative Errors

Abstract. Quantitative parameters characterizing the sea ice surface topography are needed in geophysical investigations such as studies on atmosphere–ice interactions or sea ice mechanics. Recently, the use of space-borne single-pass interferometric synthetic aperture radar (InSAR) for retrieving the ice surface topography has attracted notice among geophysicists. In this paper the potential of InSAR measurements is examined for several satellite configurations and radar frequencies, considering statistics of heights and widths of ice ridges as well as possible magnitudes of ice drift. It is shown that, theoretically, surface height variations can be retrieved with relative errors ≤  0.5 m. In practice, however, the sea ice drift and open water leads may contribute significantly to the measured interferometric phase. Another essential factor is the dependence of the achievable interferometric baseline on the satellite orbit configurations. Possibilities to assess the influence of different factors on the measurement accuracy are demonstrated: signal-to-noise ratio, presence of a snow layer, and the penetration depth into the ice. Practical examples of sea surface height retrievals from bistatic SAR images collected during the TanDEM-X Science Phase are presented.

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