14 research outputs found
Airborne investigation of quasi-specular Ku-band radar scattering for satellite altimetry over snow-covered Arctic sea ice
Surface-based Ku-band radar altimetry investigations indicate the radar signal is typically backscattered from well above the snow-sea ice interface. However, this would induce a bias in satellite altimeter sea ice thickness retrievals not reflected by buoy validation. Our study presents a mechanism to potentially explain this paradox: probabilistic quasi-specular radar scattering from the snow-ice interface. We introduce the theory for this mechanism before identifying it in airborne Ku-band radar observations collected over landfast first year Arctic sea ice near Eureka, Canada, in spring 2016. Based on SAR data, this study area likely represents level first year sea ice across the Arctic. Radar backscatter from the snow and ice interfaces were estimated by co-aligning laser scanner and radar observations with in situ measurements. On average, 4-5 times more radar power was scattered from the snow-ice than the air-snow interface over first-year ice. However, return power varied by up to 20 dB between consecutive radar echoes, particularly from the snow-ice interface, depending on local slope and roughness. Measured laser-radar snow depths were more accurate when radar returns were specular, but there was no systematic bias between airborne and in situ snow depths. The probability and strength of quasi-specular returns depend on the measuring height above and slope distribution of sea ice, so these findings have implications for satellite altimetry snow depth and freeboard estimates. This mechanism could explain the apparent differences in Ku-band radar penetration into snow on sea ice when observed from the range of a surface-, airborne- or satellite-based sensor
Synoptic variability in satellite altimeterâderived radar freeboard of Arctic sea ice
Satellite observations of sea ice freeboard are integral to the estimation of sea ice thickness. It is commonly assumed that radar pulses from satellite-mounted Ku-band altimeters penetrate through the snow and reflect from the snow-ice interface. We would therefore expect a negative correlation between snow accumulation and radar freeboard measurements, as increased snow loading weighs the ice floe down. In this study we produce daily-resolution radar freeboard products from the CryoSat-2 and Sentinel-3 altimeters via a recently developed optimal interpolation scheme. We find statistically significant (p < 0.05) positive correlations between radar freeboard anomalies and modelled snow accumulation. This suggests that, in the period after snowfall, radar pulses are not scattering from the snow-ice interface as commonly assumed. Our results offer satellite-based evidence of winter Ku-band radar scattering above the snow-ice interface, violating a key assumption in sea ice thickness retrievals
Synoptic Variability in Satellite Altimeter-Derived Radar Freeboard of Arctic Sea Ice
Satellite observations of sea ice freeboard are integral to the estimation of sea ice thickness. It is commonly assumed that radar pulses from satellite-mounted Ku-band altimeters penetrate through the snow and reflect from the snow-ice interface. We would therefore expect a negative correlation between snow accumulation and radar freeboard measurements, as increased snow loading weighs the ice floe down. In this study we produce daily resolution radar freeboard products from the CryoSat-2 and Sentinel-3 altimeters via a recently developed optimal interpolation scheme. We find statistically significant (p < 0.05) positive correlations between radar freeboard anomalies and modeled snow accumulation. This suggests that, in the period after snowfall, radar pulses are not scattering from the snow-ice interface as commonly assumed. Our results offer satellite-based evidence of winter Ku-band radar scattering above the snow-ice interface, violating a key assumption in sea ice thickness retrievals
Sub-kilometre scale distribution of snow depth on Arctic sea ice from Soviet drifting stations
The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of energy and mass, and is of importance for satellite estimates of sea-ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33 539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies
Snow Property Controls on Modeled Ku-Band Altimeter Estimates of First-Year Sea Ice Thickness: Case Studies From the Canadian and Norwegian Arctic
Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On first-year sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This article examines the expected changes in Ku-band main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity, and density derived from ten naturally occurring Arctic FYI Cases encompassing saline/nonsaline, warm/cold, simple/complexly layered snow (4â45 cm) overlying FYI (48â170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m 3 , especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies
Retrieval of Snow Depth on Arctic Sea Ice From SurfaceâBased, Polarimetric, DualâFrequency Radar Altimetry
Snow depth on sea ice is an Essential Climate Variable and a major source of uncertainty in satellite altimetryâderived sea ice thickness. During winter of the MOSAiC Expedition, the âKuKaâ dualâfrequency, fully polarized Kuâ and Kaâband radar was deployed in âstareâ nadirâlooking mode to investigate the possibility of combining these two frequencies to retrieve snow depth. Three approaches were investigated: dualâfrequency, dualâpolarization and waveform shape, and compared to independent snow depth measurements. Novel dualâpolarization approaches yielded r2 values up to 0.77. Mean snow depths agreed within 1Â cm, even for data subâbanded to CryoSatâ2 SIRAL and SARAL AltiKa bandwidths. Snow depths from coâpolarized dualâfrequency approaches were at least a factor of four too small and had a r2 0.15 or lower. r2 for waveform shape techniques reached 0.72 but depths were underestimated. Snow depth retrievals using polarimetric information or waveform shape may therefore be possible from airborne/satellite radar altimeters
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Wind-driven redistribution of snow on sea ice alters its
topography and microstructure, yet the impact of these processes on radar
signatures is poorly understood. Here, we examine the effects of snow
redistribution over Arctic sea ice on radar waveforms and backscatter
signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band
radar at incidence angles between 0â (nadir) and 50â.
Two wind events in November 2019 during the Multidisciplinary drifting Observatory for
the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and
Ku-band radar waveforms and backscatter coefficients at nadir are observed,
coincident with surface topography changes measured by a terrestrial laser
scanner. At both frequencies, redistribution caused snow densification at
the surface and the uppermost layers, increasing the scattering at the
airâsnow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous
airâsnow interfaces, buried beneath newly deposited snow. The additional
scattering from previous airâsnow interfaces could therefore affect the
range retrieved from Ka- and Ku-band satellite altimeters. With increasing
incidence angles, the relative scattering contribution of the airâsnow
interface decreases, and the snowâsea ice interface scattering increases.
Relative to pre-wind event conditions, azimuthally averaged backscatter at
nadir during the wind events increases by up to 8âdB (Ka-band) and 5âdB (Ku-band). Results show substantial backscatter variability within the scan
area at all incidence angles and polarizations, in response to increasing
wind speed and changes in wind direction. Our results show that snow
redistribution and wind compaction need to be accounted for to interpret
airborne and satellite radar measurements of snow-covered sea ice
Wind redistribution of snow impacts the Ka- and Ku-band radar signatures of Arctic sea ice
Wind-driven redistribution of snow on sea ice alters its topography and microstructure, yet the impact of these processes on radar signatures is poorly understood. Here, we examine the effects of snow redistribution over Arctic sea ice on radar waveforms and backscatter signatures obtained from a surface-based, fully polarimetric Ka- and Ku-band radar at incidence angles between 0â (nadir) and 50â. Two wind events in November 2019 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition are evaluated. During both events, changes in Ka- and Ku-band radar waveforms and backscatter coefficients at nadir are observed, coincident with surface topography changes measured by a terrestrial laser scanner. At both frequencies, redistribution caused snow densification at the surface and the uppermost layers, increasing the scattering at the airâsnow interface at nadir and its prevalence as the dominant radar scattering surface. The waveform data also detected the presence of previous airâsnow interfaces, buried beneath newly deposited snow. The additional scattering from previous airâsnow interfaces could therefore affect the range retrieved from Ka- and Ku-band satellite altimeters. With increasing incidence angles, the relative scattering contribution of the airâsnow interface decreases, and the snowâsea ice interface scattering increases. Relative to pre-wind event conditions, azimuthally averaged backscatter at nadir during the wind events increases by up to 8âdB (Ka-band) and 5âdB (Ku-band). Results show substantial backscatter variability within the scan area at all incidence angles and polarizations, in response to increasing wind speed and changes in wind direction. Our results show that snow redistribution and wind compaction need to be accounted for to interpret airborne and satellite radar measurements of snow-covered sea ice
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Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover
Mean sea ice thickness is a sensitive indicator of Arctic climate change and is in long-term decline despite significant interannual variability. Current thickness estimations from satellite radar altimeters employ a snow climatology for converting range measurements to sea ice thickness, but this introduces unrealistically low interannual variability and trends. When the sea ice thickness in the period 2002â2018 is calculated using new snow data with more realistic variability and trends, we find mean sea ice thickness in four of the seven marginal seas to be declining between 60â%â100â% faster than when calculated with the conventional climatology. When analysed as an aggregate area, the mean sea ice thickness in the marginal seas is in statistically significant decline for 6 of 7 winter months. This is observed despite a 76â% increase in interannual variability between the methods in the same time period. On a seasonal timescale we find that snow data exert an increasingly strong control on thickness variability over the growth season, contributing 46â% in October but 70â% by April. Higher variability and faster decline in the sea ice thickness of the marginal seas has wide implications for our understanding of the polar climate system and our predictions for its change
Sub-kilometre scale distribution of snow depth on Arctic sea ice from Soviet drifting stations
The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of energy and mass, and is of importance for satellite estimates of sea-ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33 539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies