Effects of surface roughness on sea ice freeboard retrieval with an Airborne Ku-Band SAR radar altimeter

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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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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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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Simulation of the Ku-Band Radar Altimeter Sea Ice Effective Scattering Surface

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2005.862276 ◽

2006 ◽

Vol 3 (2) ◽

pp. 237-240 ◽

Cited By ~ 8

Author(s):

R. Tonboe ◽

S. Andersen ◽

L.T. Pedersen

Keyword(s):

Sea Ice ◽

Radar Altimeter ◽

Effective Scattering Surface ◽

Ku Band

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Ku-band radar penetration into snow cover on Arctic sea ice using airborne data

Annals of Glaciology ◽

10.3189/172756411795931589 ◽

2011 ◽

Vol 52 (57) ◽

pp. 197-205 ◽

Cited By ~ 55

Author(s):

Rosemary Willatt ◽

Seymour Laxon ◽

Katharine Giles ◽

Robert Cullen ◽

Christian Haas ◽

...

Keyword(s):

Sea Ice ◽

Field Measurements ◽

Normal Incidence ◽

Arctic Sea Ice ◽

Radar Altimeter ◽

Sea Ice Thickness ◽

Validation Experiment ◽

Arctic Sea ◽

Arctic Sea Ice Thickness ◽

Ku Band

AbstractSatellite radar altimetry provides data to monitor winter Arctic sea-ice thickness variability on interannual, basin-wide scales. When using this technique an assumption is made that the peak of the radar return originates from the snow/ice interface. This has been shown to be true in the laboratory for cold, dry snow as is the case on Arctic sea ice during winter. However, this assumption has not been tested in the field. We use data from an airborne normal-incidence Ku-band radar altimeter and in situ field measurements, collected during the CryoSat Validation Experiment (CryoVEx) Bay of Bothnia, 2006 and 2008 field campaigns, to determine the dominant scattering surface for Arctic snow-covered sea ice. In 2006, when the snow temperatures were close to freezing, the dominant scattering surface in 25% of the radar returns appeared closer to the snow/ice interface than the air/snow interface. However, in 2008, when temperatures were lower, the dominant scattering surface appeared closer to the snow/ice interface than the air/snow interface in 80% of the returns.

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

The Cryosphere Discussions ◽

10.5194/tcd-7-1215-2013 ◽

2013 ◽

Vol 7 (2) ◽

pp. 1215-1242

Author(s):

M. Zygmuntowska ◽

K. Khvorostovsky ◽

V. Helm ◽

S. Sandven

Keyword(s):

Sea Ice ◽

Synthetic Aperture Radar ◽

Waveform Analysis ◽

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 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 has been analyzed. A set of parameters has been defined to characterize the difference in strength and width of the returned power waveforms. With a Bayesian based method it is possible to classify about 80% of the waveforms by three parameters: maximum of the returned power echo, the trailing edge width and pulse peakiness. Furthermore, the radar power echo maximum can be used to minimize the rate of false detection of leads compared to the widely used Pulse Peakiness parameter. The possibility to distinguish between different ice types and open water allows to improve the freeboard retrieval and the conversion into sea ice thickness where surface type dependent values for the sea ice density and snow load can be used.

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Impact of Snow Properties on Ka- and Ku-band Winter and Melt Season Microwave Signatures of Arctic Sea Ice

10.5194/egusphere-egu21-13067 ◽

2021 ◽

Author(s):

Vishnu Nandan ◽

Rosemary Willatt ◽

Julienne Stroeve ◽

Robbie Mallett ◽

Keyword(s):

Sea Ice ◽

Snow Accumulation ◽

Arctic Sea Ice ◽

Surface Scattering ◽

Snow Surface ◽

State Variables ◽

Radar Altimeter ◽

Ka Band ◽

Microwave Signatures ◽

Ku Band

We present the baseline and detailed assessment of Ka- and Ku-band microwave signatures of winter (Legs 1 and 2) and melt season (Leg 4) snow-covered sea ice, acquired during the 2019-2020 MOSAiC International Arctic Drift Expedition. The microwave signatures were acquired using a surface-based, fully-polarimetric, Ku- and Ka-band radar (KuKa radar), acquired coincident with in situ meteorological and snow/sea ice geophysical property measurements. The KuKa radar mimicked the center frequencies of presently operational Ku- and Ka-band satellite radar altimeter and scatterometer missions.Preliminary observations, supported by microwave backscatter modeling indicates dominant Ka-band snow surface scattering and its strong sensitivity due to snow surface roughness and its changes, induced by snow accumulation, wind-driven redistribution/erosion. For Ku-band, winter backscatter signatures originate from the snow/sea ice interface. We also showcase the winter backscatter sensitivity through its impact during the November 2019 warm storm.&#160; During advanced melt, the Ka- and Ku-band signatures demonstrates sensitivity to snow surface melt/refreeze diurnal cycling, caused by fluctuations in liquid water content. During the melt cycle, scattering loss and absorption dominated both frequencies, while refrozen snow surface scattering dominated the refreeze cycle (observed during morning and evening scans).&#160;Observations from the KuKa radar will in turn provide critical understanding of snow/sea ice geophysical processes over the annual cycle, that will improve the accuracy of satellite-based retrievals of snow/sea ice critical state variables such as snow depth, sea ice thickness,&#160; freeze-up and melt-onset timings etc, from operational and forthcoming missions such as AltiKa, CryoSat-2, Sentinel-3, ScatSat-1, CRISTAL etc.&#160;

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Large-scale inverse Ku-band backscatter modeling of sea ice

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2003.813495 ◽

2003 ◽

Vol 41 (8) ◽

pp. 1821-1833 ◽

Cited By ~ 13

Author(s):

Q.P. Remund ◽

D.G. Long

Keyword(s):

Sea Ice ◽

Large Scale ◽

Ku Band

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First results from the e Copernicus Sentinel-6 satellite mission

10.5194/egusphere-egu21-3165 ◽

2021 ◽

Author(s):

Craig Donlon ◽

Robert Cullen ◽

Luisella Giulicchi ◽

Marco Fonari

Keyword(s):

Sea Level ◽

Microwave Radiometer ◽

Precise Orbit Determination ◽

Well Being ◽

The European Union ◽

Radar Altimeter ◽

Satellite Mission ◽

International Partnership ◽

Satellite Missions ◽

Ku Band

The threat of sea level rise to coastal communities is an area of significant concern to the well-being and security of future generations. Environmental policy actions and decisions affecting coastal states are being made now.&#160; Given the considerable range of applications, sustained altimetry satellite missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to address the needs of the European Copernicus programme for precision sea level, near-real-time measurements of sea surface height, significant wave height, and other products tailored to operational services in the climate, ocean, meteorology and hydrology domains. It is designed to provide enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon (T/P) mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). &#160;It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter providing synthetic aperture radar (SAR) processing in Ku-band to improve the signal through better along-track sampling and reduced measurement noise. The altimeter has an innovative interleaved mode enabling radar data processing on two parallel chains, one with the SAR enhancements and the other furnishing a "Low Resolution Mode" that is fully backward-compatible with the historical T/P and Jason measurements, so that complete inter-calibration between the state-of-the-art data and the historical record can be assured. A three-channel Advanced Microwave Radiometer for Climate (AMR-C) developed by NASA JPL provides measurements of atmospheric water vapour that would otherwise degrade the radar altimeter measurements. An experimental High Resolution Microwave Radiometer (HRMR) is also included in the AMR-C design to support improved performance in coastal areas. Additional sensors are included in the payload to provide Precise Orbit Determination, atmospheric sounding via GNSS-Radio Occultation and radiation monitoring around the spacecraft.Early in-orbit performance data are presented.

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