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

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

<p>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 <em>in situ</em> 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.</p><p>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.  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). </p><p>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,  freeze-up and melt-onset timings etc, from operational and forthcoming missions such as AltiKa, CryoSat-2, Sentinel-3, ScatSat-1, CRISTAL etc. </p>

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

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.

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

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.

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

2013 ◽  
Vol 7 (4) ◽  
pp. 1315-1324 ◽  
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.

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

2011 ◽  
Vol 52 (57) ◽  
pp. 197-205 ◽  
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.

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

2014 ◽  
Vol 8 (2) ◽  
pp. 1831-1871 ◽  
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.

scholarly journals Evaluating Airborne Ku-Band Radar Altimetry over Landfast First-Year Sea Ice

2020 ◽  
Author(s):  
Paul Donchenko ◽  
Joshua King ◽  
Richard Kelly
Keyword(s):  
Grain Size ◽  
Sea Ice ◽  
Snow Cover ◽  
Surface Properties ◽  
Surface Characteristics ◽  
Arctic Sea Ice ◽  
Surface Elevation ◽  
Snow Surface ◽  
Ice Surface ◽  
Ku Band

Abstract. Recent studies have challenged the assumption that Ku-band radar used by the CryoSat-2 altimeter fully penetrates the dry snow cover of Arctic sea ice. There is also uncertainty around the proper technique for handling retracker threshold selection in the Threshold First-Maxima Retracker (TFMRA) method which estimates the ice surface elevation from the radar echo waveform. The purpose of this study was to evaluate the accuracy and penetration of the TFMRA retracking method applied to the Airborne Synthetic Aperture Radar and Interferometric Radar Altimeter System (ASIRAS), an airborne simulator of the CryoSat-2, to investigate the effect of surface characteristics and improve accuracy. The ice surface elevation estimate from ASIRAS was evaluated by comparing to the snow surface measured by aggregating laser altimetry observations from the Airborne Laser Scanner (ALS), and the ice surface measured by subtracting ground observations of snow depth from the snow surface. The perceived penetration of the ice surface estimate was found to increase with the retracker threshold and was correlated with the value of surface properties. The slope of the relationship between penetration and threshold was greater for a deformed ice surface, a rough snow surface, a deeper snow cover, an absence of salinity and a larger snow grain size. As a result, the ideal retracked threshold, one that would achieve 100 % penetration, varies depending on properties of the surface being observed. Under conditions such deep snow or a large grain size, the retracked elevation sr was found in some cases to not penetrate fully the snowpack. This would cause an overestimation of the sea ice freeboard and as a consequence, the sea ice thickness. Results suggest that using a single threshold with the TFMRA retracking method will not yield a reliable estimate of the snow-ice interface when observed over an area with diverse surface properties. However, there may be potential to improve the retracking method by incorporating knowledge of the sensed surface physical characteristics. This study shows that remotely sensed surface properties, such as the ice deformity or snow surface roughness, can be combined with the waveform shape to select an ideal retracker for individual returns with an additional offset to account for the incomplete penetration of Ku-band over appropriate surface characteristics.

Intercomparison of Arctic Sea Ice Backscatter and Ice Type Classification Using Ku-Band and C-Band Scatterometers

2021 ◽  
pp. 1-18
Author(s):  
Zhilun Zhang ◽  
Yining Yu ◽  
Mohammed Shokr ◽  
Xinqing Li ◽  
Yufang Ye ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Arctic Sea ◽  
Type Classification ◽  
Ku Band

scholarly journals The European Space Agency’s Earth Explorer Mission CryoSat: measuring variability in the cryosphere

2004 ◽  
Vol 39 ◽  
pp. 313-320 ◽  
Author(s):  
Mark R. Drinkwater ◽  
Richard Francis ◽  
Guy Ratier ◽  
Duncan J. Wingham
Keyword(s):  
European Space Agency ◽  
Ice Sheets ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Radar Altimeter ◽  
Operating Characteristics ◽  
Space Agency ◽  
Explorer Mission ◽  
Arctic Sea ◽  
Ku Band

AbstractCryoSat is currently being prepared for a 2005 launch as the first European Space Agency Earth Explorer Opportunity mission. It is a dedicated cryospheric mission equipped with a Ku-band SIRAL (SAR/Interferometric Radar ALtimeter), whose primary objectives are to measure the variability and trends in the mass of the Arctic sea-ice cover and large terrestrial ice sheets. In this paper, an overview is provided of the mission and of the measurement characteristics of the new SIRAL instrument. Examples of data acquired on recent preparatory campaigns are presented, illustrating the operating characteristics of the key SIRAL modes. Preparatory plans for calibration and validation of CryoSat data are described.

scholarly journals The role of cyclone activity in snow accumulation on Arctic sea ice

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
M. A. Webster ◽  
C. Parker ◽  
L. Boisvert ◽  
R. Kwok
Keyword(s):  
Sea Ice ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Cyclone Activity ◽  
In Situ Data ◽  
Arctic Sea ◽  
Spatio Temporal

AbstractIdentifying the mechanisms controlling the timing and magnitude of snow accumulation on sea ice is crucial for understanding snow’s net effect on the surface energy budget and sea-ice mass balance. Here, we analyze the role of cyclone activity on the seasonal buildup of snow on Arctic sea ice using model, satellite, and in situ data over 1979–2016. On average, 44% of the variability in monthly snow accumulation was controlled by cyclone snowfall and 29% by sea-ice freeze-up. However, there were strong spatio-temporal differences. Cyclone snowfall comprised ~50% of total snowfall in the Pacific compared to 83% in the Atlantic. While cyclones are stronger in the Atlantic, Pacific snow accumulation is more sensitive to cyclone strength. These findings highlight the heterogeneity in atmosphere-snow-ice interactions across the Arctic, and emphasize the need to scrutinize mechanisms governing cyclone activity to better understand their effects on the Arctic snow-ice system with anthropogenic warming.

scholarly journals Arctic sea-ice albedo derived from RGPS-based ice-thickness estimates

2001 ◽  
Vol 33 ◽  
pp. 225-229 ◽  
Author(s):  
R.W. Lindsay
Keyword(s):  
Sea Ice ◽  
Empirical Relationship ◽  
Early Spring ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
First Year ◽  
Large Set ◽  
Radar Images ◽  
Arctic Sea

AbstractThe RADARSAT geophysical processor system (RGPS) uses sequential synthetic aperture radar images of Arctic sea ice taken every 3 days to track a large set of Lagrangian points over the winter and spring seasons. The points are the vertices of cells, which are initially square and 10 km on a side, and the changes in the area of these cells due to opening and closing of the ice are used to estimate the fractional area of a set of first-year ice categories. The thickness of each category is estimated by the RGPS from an empirical relationship between ice thickness and the freezing degree-days since the formation of the ice. With a parameterization of the albedo based on the ice thickness, the albedo may be estimated from the first-year ice distribution. We compute the albedo for the first spring processed by the RGPS, the early spring of 1997. The data include most of the Beaufort and Chukchi Seas. We find that the mean albedo is 0.79 with a standard deviation of 0.04, with lower albedo values near the edge of the perennial ice zone. The biggest source of error is likely the assumed rate of snow accumulation on new ice.

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