Simulation of the CryoSat-2 satellite radar altimeter sea ice thickness retrieval uncertainty

Abstract. Although it is well known that radar waves penetrate into snow and sea ice, the exact mechanisms for radar-altimeter scattering and its link to the depth of the effective scattering surface from sea ice are still unknown. Previously proposed mechanisms linked the snow ice interface, i.e. the dominating scattering horizon, directly with the depth of the effective scattering surface. However, simulations using a multilayer radar scattering model show that the effective scattering surface is affected by snow-cover and ice properties. With the coming Cryosat-2 (planned launch 2009) satellite radar altimeter it is proposed that sea ice thickness can be derived by measuring its freeboard. In this study we evaluate the radar altimeter sea ice thickness retrieval uncertainty in terms of floe buoyancy, radar penetration and ice type distribution using both a scattering model and ''Archimedes' principle''. The effect of the snow cover on the floe buoyancy and the radar penetration and on the ice cover spatial and temporal variability is assessed from field campaign measurements in the Arctic and Antarctic. In addition to these well known uncertainties we use high resolution RADARSAT SAR data to simulate errors due to the variability of the effective scattering surface as a result of the sub-footprint spatial backscatter and elevation distribution sometimes called preferential sampling. In particular in areas where ridges represent a significant part of the ice volume (e.g. the Lincoln Sea) the simulated altimeter thickness estimate is lower than the real average footprint thickness. This means that the errors are large, yet manageable if the relevant quantities are known a priori. A discussion of the radar altimeter ice thickness retrieval uncertainties concludes the paper.

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The impact of snow depth, snow density and ice density on sea ice thickness retrieval from satellite radar altimetry: results from the ESA-CCI Sea Ice ECV Project Round Robin Exercise

The Cryosphere ◽

10.5194/tc-9-37-2015 ◽

2015 ◽

Vol 9 (1) ◽

pp. 37-52 ◽

Cited By ~ 38

Author(s):

S. Kern ◽

K. Khvorostovsky ◽

H. Skourup ◽

E. Rinne ◽

Z. S. Parsakhoo ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Ice Thickness ◽

Data Sets ◽

Snow Density ◽

Radar Altimetry ◽

Sea Ice Thickness ◽

The Mean ◽

Satellite Radar ◽

Satellite Radar Altimetry

Abstract. We assess different methods and input parameters, namely snow depth, snow density and ice density, used in freeboard-to-thickness conversion of Arctic sea ice. This conversion is an important part of sea ice thickness retrieval from spaceborne altimetry. A data base is created comprising sea ice freeboard derived from satellite radar altimetry between 1993 and 2012 and co-locate observations of total (sea ice + snow) and sea ice freeboard from the Operation Ice Bridge (OIB) and CryoSat Validation Experiment (CryoVEx) airborne campaigns, of sea ice draft from moored and submarine upward looking sonar (ULS), and of snow depth from OIB campaigns, Advanced Microwave Scanning Radiometer (AMSR-E) and the Warren climatology (Warren et al., 1999). We compare the different data sets in spatiotemporal scales where satellite radar altimetry yields meaningful results. An inter-comparison of the snow depth data sets emphasizes the limited usefulness of Warren climatology snow depth for freeboard-to-thickness conversion under current Arctic Ocean conditions reported in other studies. We test different freeboard-to-thickness and freeboard-to-draft conversion approaches. The mean observed ULS sea ice draft agrees with the mean sea ice draft derived from radar altimetry within the uncertainty bounds of the data sets involved. However, none of the approaches are able to reproduce the seasonal cycle in sea ice draft observed by moored ULS. A sensitivity analysis of the freeboard-to-thickness conversion suggests that sea ice density is as important as snow depth.

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About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice

The Cryosphere Discussions ◽

10.5194/tcd-9-4893-2015 ◽

2015 ◽

Vol 9 (5) ◽

pp. 4893-4923 ◽

Cited By ~ 1

Author(s):

S. Schwegmann ◽

E. Rinne ◽

R. Ricker ◽

S. Hendricks ◽

V. Helm

Keyword(s):

Southern Ocean ◽

Sea Ice ◽

Altimeter Data ◽

Ice Thickness ◽

Radar Altimeter ◽

Growth Season ◽

Sea Ice Thickness ◽

Antarctic Sea Ice ◽

Abstract Knowledge ◽

Modal Values

Abstract. Knowledge about Antarctic sea-ice volume and its changes over the past decades has been sparse due to the lack of systematic sea-ice thickness measurements in this remote area. Recently, first attempts have been made to develop a sea-ice thickness product over the Southern Ocean from space-borne radar altimetry and results look promising. Today, more than 20 years of radar altimeter data are potentially available for such products. However, data come from different sources, and the characteristics of individual sensors differ. Hence, it is important to study the consistency between single sensors in order to develop long and consistent time series over the potentially available measurement period. Here, the consistency between freeboard measurements of the Radar Altimeter 2 on-board Envisat and freeboard measurements from the Synthetic-Aperture Interferometric Radar Altimeter on-board CryoSat-2 is tested for their overlap period in 2011. Results indicate that mean and modal values are comparable over the sea-ice growth season (May–October) and partly also beyond. In general, Envisat data shows higher freeboards in the seasonal ice zone while CryoSat-2 freeboards are higher in the perennial ice zone and near the coasts. This has consequences for the agreement in individual sectors of the Southern Ocean, where one or the other ice class may dominate. Nevertheless, over the growth season, mean freeboard for the entire (regional separated) Southern Ocean differs generally by not more than 2 cm (5 cm, except for the Amundsen/Bellingshausen Sea) between Envisat and CryoSat-2, and the differences between modal freeboard lie generally within ±10 cm and often even below.

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A comparison between Envisat and ICESat sea ice thickness in the Antarctic

10.5194/tc-2020-48 ◽

2020 ◽

Author(s):

Jinfei Wang ◽

Chao Min ◽

Robert Ricker ◽

Qinghua Yang ◽

Qian Shi ◽

...

Keyword(s):

Sea Ice ◽

European Space Agency ◽

Weddell Sea ◽

Ice Thickness ◽

Radar Altimeter ◽

Average Deviation ◽

Absolute Deviation ◽

Sea Ice Thickness ◽

Antarctic Sea Ice ◽

The Antarctic

Abstract. The crucial role that Antarctic sea ice plays in the global climate system is strongly linked to its thickness. While in situ observations are too sparse in the Antarctic to determine long-term trends of the Antarctic sea ice thickness on a global scale, satellite radar altimetry data can be applied with a promising prospect. A newly released Envisat-derived product from the European Space Agency Sea Ice Climate Change Initiative (ESA SICCI), including sea ice freeboard and sea ice thickness, covers the entire Antarctic year-round from 2002 to 2012. In this study, the SICCI Envisat sea ice thickness in the Antarctic is firstly compared with a conceptually new proposed ICESat ice thickness that has been derived from an algorithm employing modified ice density. Both data sets have been validated with the Weddell Sea upward looking sonar measurements (ULS), indicating that ICESat agrees better with field observations. The inter-comparisons are conducted for three seasons except winter based on the ICESat operating periods. According to the results, the deviations between Envisat and ICESat sea ice thickness are different considering different seasons, years and regions. More specifically, the smallest average deviation between Envisat and ICESat sea ice thickness exists in spring by −0.03 m while larger deviations exist in summer and autumn by 0.86 m and 0.62 m, respectively. Although the smallest absolute deviation occurs in spring 2005 by 0.02 m, the largest correlation coefficient appears in autumn 2004 by 0.77. The largest positive deviation occurs in the western Weddell Sea by 1.03 m in summer while the largest negative deviation occurs in the Eastern Antarctic by −0.25 m in spring. Potential reasons for those deviations mainly deduce from the limitations of Envisat radar altimeter affected by the weather conditions and the surface roughness as well as the different retrieval algorithms. The better performance in spring of Envisat has a potential relation with relative humidity.

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Simulated Ka- and Ku-band radar altimeter height and freeboard estimation on snow-covered Arctic sea ice

The Cryosphere ◽

10.5194/tc-15-1811-2021 ◽

2021 ◽

Vol 15 (4) ◽

pp. 1811-1822

Author(s):

Rasmus T. Tonboe ◽

Vishnu Nandan ◽

John Yackel ◽

Stefan Kern ◽

Leif Toudal Pedersen ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Arctic Sea Ice ◽

Ice Thickness ◽

Radar Altimeter ◽

Sea Ice Thickness ◽

Scattering Model ◽

Radar Scattering ◽

The Impact ◽

Ku Band

Abstract. Owing to differing and complex snow geophysical properties, radar waves of different wavelengths undergo variable penetration through snow-covered sea ice. However, the mechanisms influencing radar altimeter backscatter from snow-covered sea ice, especially at Ka- and Ku-band frequencies, and the impact on the Ka- and Ku-band radar scattering horizon or the “track point” (i.e. the scattering layer depth detected by the radar re-tracker) are not well understood. In this study, we evaluate the Ka- and Ku-band radar scattering horizon with respect to radar penetration and ice floe buoyancy using a first-order scattering model and the Archimedes principle. The scattering model is forced with snow depth data from the European Space Agency (ESA) climate change initiative (CCI) round-robin data package, in which NASA's Operation IceBridge (OIB) data and climatology are included, and detailed snow geophysical property profiles from the Canadian Arctic. Our simulations demonstrate that the Ka- and Ku-band track point difference is a function of snow depth; however, the simulated track point difference is much smaller than what is reported in the literature from the Ku-band CryoSat-2 and Ka-band SARAL/AltiKa satellite radar altimeter observations. We argue that this discrepancy in the Ka- and Ku-band track point differences is sensitive to ice type and snow depth and its associated geophysical properties. Snow salinity is first increasing the Ka- and Ku-band track point difference when the snow is thin and then decreasing the difference when the snow is thick (>0.1 m). A relationship between the Ku-band radar scattering horizon and snow depth is found. This relationship has implications for (1) the use of snow climatology in the conversion of radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both (1) and (2), the impact of using a snow climatology versus the actual snow depth is relatively small on the radar freeboard, only raising the radar freeboard by 0.03 times the climatological snow depth plus 0.03 times the real snow depth. The radar freeboard is a function of both radar scattering and floe buoyancy. This study serves to enhance our understanding of microwave interactions towards improved accuracy of snow depth and sea ice thickness retrievals via the combination of the currently operational and ESA's forthcoming Ka- and Ku-band dual-frequency CRISTAL radar altimeter missions.

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About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice

The Cryosphere ◽

10.5194/tc-10-1415-2016 ◽

2016 ◽

Vol 10 (4) ◽

pp. 1415-1425 ◽

Cited By ~ 17

Author(s):

Sandra Schwegmann ◽

Eero Rinne ◽

Robert Ricker ◽

Stefan Hendricks ◽

Veit Helm

Keyword(s):

Southern Ocean ◽

Sea Ice ◽

Altimeter Data ◽

Ice Thickness ◽

Radar Altimeter ◽

Growth Season ◽

Sea Ice Thickness ◽

Antarctic Sea Ice ◽

Abstract Knowledge ◽

Modal Values

Abstract. Knowledge about Antarctic sea-ice volume and its changes over the past decades has been sparse due to the lack of systematic sea-ice thickness measurements in this remote area. Recently, first attempts have been made to develop a sea-ice thickness product over the Southern Ocean from space-borne radar altimetry and results look promising. Today, more than 20 years of radar altimeter data are potentially available for such products. However, the characteristics of individual radar types differ for the available altimeter missions. Hence, it is important and our goal to study the consistency between single sensors in order to develop long and consistent time series. Here, the consistency between freeboard measurements of the Radar Altimeter 2 on board Envisat and freeboard measurements from the Synthetic-Aperture Interferometric Radar Altimeter on board CryoSat-2 is tested for their overlap period in 2011. Results indicate that mean and modal values are in reasonable agreement over the sea-ice growth season (May–October) and partly also beyond. In general, Envisat data show higher freeboards in the first-year ice zone while CryoSat-2 freeboards are higher in the multiyear ice zone and near the coasts. This has consequences for the agreement in individual sectors of the Southern Ocean, where one or the other ice class may dominate. Nevertheless, over the growth season, mean freeboard for the entire (regionally separated) Southern Ocean differs generally by not more than 3 cm (8 cm, with few exceptions) between Envisat and CryoSat-2, and the differences between modal freeboards lie generally within ±10 cm and often even below.

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Simulated Ka- and Ku-band radar altimeter scattering horizon on snow-covered Arctic sea ice

10.5194/tc-2020-196 ◽

2020 ◽

Author(s):

Rasmus T. Tonboe ◽

Vishnu Nandan ◽

John Yackel ◽

Stefan Kern ◽

Leif Toudal Pedersen ◽

...

Keyword(s):

Sea Ice ◽

Snow Depth ◽

Arctic Sea Ice ◽

Ice Thickness ◽

Radar Altimeter ◽

Sea Ice Thickness ◽

Scattering Model ◽

Radar Scattering ◽

The Impact ◽

Ku Band

Abstract. Owing to differing and complex snow geophysical properties, radar waves of different wavelengths undergo variable penetration through snow-covered sea ice. However, the mechanisms influencing radar altimeter backscatter from snow-covered sea ice, especially at Ka- and Ku-band frequencies, and its impact on the Ka- and Ku-band radar scattering horizon or the "track point" (i.e. the scattering layer depth detected by the radar re-tracker), are not well understood. In this study, we evaluate the Ka- and Ku-band radar scattering horizon with respect to radar penetration and ice floe buoyancy using a first-order scattering model and Archimedes’ principle. The scattering model is forced with snow depth data from the European Space Agency (ESA) climate change initiative (CCI) round robin data package, NASA’s Operation Ice Bridge (OIB) data and climatology, and detailed snow geophysical property profiles from the Canadian Arctic. Our simulations demonstrate that the Ka- and Ku-band track point difference is a function of snow depth, however, the simulated track point difference is much smaller than what is reported in the literature from the CryoSat-2 Ku-band and SARAL/AltiKa Ka-band satellite radar altimeter observations. We argue that this discrepancy in the Ka- and Ku-band track point differences are sensitive to ice type and snow depth and its associated geophysical properties. Snow salinity is first increasing the Ka- and Ku-band track-point difference when the snow is thin and then decreasing the difference when the snow is thick (> 10 cm). A relationship between the Ku-band radar scattering horizon and snow depth is found. This relationship has implications for 1) the use of snow climatology in the conversion of radar freeboard into sea ice thickness and 2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small on the measured freeboard, by only raising the measured freeboard by 0.03 times the climatological snow depth plus 0.03 times the real snow depth. This study serves to enhance our understanding of microwave interactions towards improved accuracy of snow depth and sea ice thickness retrievals from combining currently operational and upcoming Ka- and Ku-band dual-frequency radar altimeter missions, such as ESA’s Copernicus High Priority Candidate Mission CRISTAL.

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Brief Communication: Conventional assumptions involving the speed of radar waves in snow introduce systematic underestimates to sea ice thickness and seasonal growth rate estimates

10.5194/tc-2019-198 ◽

2019 ◽

Author(s):

Robbie D. C. Mallett ◽

Isobel R. Lawrence ◽

Julienne C. Stroeve ◽

Jack C. Landy ◽

Michel Tsamados

Keyword(s):

Growth Rate ◽

Sea Ice ◽

Arctic Sea Ice ◽

Ice Thickness ◽

Snow Layer ◽

Sea Ice Thickness ◽

Arctic Sea ◽

Satellite Radar ◽

Arctic Sea Ice Thickness ◽

Radar Wave

Abstract. Pan-Arctic sea ice thickness has been monitored over recent decades by satellite radar altimeters such as CryoSat-2, which emit Ku-band radar waves that are conventionally assumed to penetrate overlying snow and scatter from the ice-snow interface. Here we examine two expressions for the time delay caused by slower radar wave propagation through the snow layer and related assumptions concerning the time-evolution of overlying snow density. Two conventional treatments lead to systematic underestimates of winter ice thickness and thermodynamic growth rate of up to 15 cm over multiyear ice. Correcting these biases would improve the accuracy of sea ice thickness products, which feed a wide variety of model projections, calibrations, validations and reanalyses.

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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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