CryoSat-2 (CS2) is the first mission equipped with a pulse-limited radar altimeter capable of operating in Synthetic Aperture Radar (SAR) Interferometric (SARIn) mode. Over ice sheets and ice caps, CS2 SARIn data have been used to retrieve surface elevations over an across-track ground “swath.” This work demonstrates that retracking multiple coherent peaks of CS2 SARIn waveforms, in combination with the interferometric phase, enables to obtain more than one valid height estimate from single SARIn waveforms over Arctic sea ice. For some SARIn waveforms, the scattering from sea ice at the satellite nadir is successfully separated from returns originating from off-nadir leads. An average bias of -1.8 cm is found for absolute sea ice elevations when using a 50% threshold retracker. It is shown that including multiple SARIn peaks and the associated phase difference in the processing does not introduce any bias on the average sea ice freeboard heights compared with the estimates from regular SAR processing schemes, while significantly increasing the number of valid sea surface height retrievals (+55%) and the number of freeboard estimates in the coastal domain and in multi-year ice regions (~3 times). This results in an average ~34% reduction of the gridded random freeboard uncertainty, corresponding to a ~20% reduction of the gridded total sea ice thickness uncertainty. The results of this work show that SARIn acquisitions over Arctic sea ice provide improved spatial coverage and denser sampling of sea level and sea ice freeboard compared with the SAR mode, with accuracy being largely driven by the retracking algorithm.

An ultrawideband radiometer was used to measure microwave brightness temperature spectra over Arctic sea ice in the Lincoln Sea near the north coast of Greenland. Spectra over the range of 0.5-2 GHz were compared to thermal infrared images collected during the airborne campaign and also compared to nearly concurrent Sentinel-1 C-band synthetic aperture radar (SAR) data. Based on those comparisons, spectral signatures were associated with thick multiyear ice and thin ice. A radiative transfer (RT) model consisting of a homogeneous slab of sea ice bounded by sea water and air was then used to invert the spectra for sea ice thickness and salinity. Inferred thicknesses were consistent with ice thickness climatology for ice floes in the Lincoln Sea. Salinities are higher than expected which may be a consequence of neglecting surface and volume scattering contributions in the models.

The airborne Operation IceBridge and spaceborne CryoSat-2 missions observe polar sea ice at different spatial and temporal scales as well as with different sensor suites. Comparison of data products from IceBridge and CryoSat-2 is complicated by the fact that they use different geophysical corrections: reference ellipsoid, geoid model, tide model, and atmospheric corrections to derive surface elevation and sea-ice freeboard. In this paper, we compare sea-ice surface elevation and freeboard using eight coincident CryoSat-2, Airborne Topographic Mapper (ATM), and Land, Vegetation, and Ice Sensor (LVIS) observations with direct IceBridge underflights of CryoSat-2 ground tracks. We apply identical geophysical corrections to CryoSat-2 and IceBridge data to eliminate elevation biases due to these differences and focus on differences due to retracker performance. The IceBridge ATM and LVIS elevation and freeboard and Snow Radar snow depth data sets are averaged to each CryoSat-2 footprint for comparison. With snow depth measurements, we are able to compare elevations and freeboards at the snow/ice interface for five different CryoSat-2 retrackers (ESA, GSFCv1, AWI, JPL, and GSFCv2) and IceBridge. The overall mean of freeboard differences between GSFCv2, ESA, AWI, JPL retrackers, and ATM are in agreement within 0.05 m. However, the five different CryoSat-2 retrackers show distinct differences in mean elevation over leads and over floes. This suggests that the physical interpretation of the different retrackers needs to be considered depending on usage, for example, elevations from CryoSat-2 retrackers need to be carefully calibrated before comparing with elevation from other satellites for long-term surface elevation trends.

The fine spatial resolution of laser altimeters makes them potentially valuable to oceanography studying features at mesoscale, close to land, and in the marginal ice zone. To fulfill this promise, we must understand laser sea state bias (SSB). SSB occurs in the measurement of sea surface height in the presence of waves when the altimeter observations are preferentially influenced by particular parts (e.g., wave troughs) of the wave-covered surface. Radar altimeters have received considerable attention relating radar SSB to wave properties and wind speed. Comparatively, little attention has been devoted to the SSB of laser altimeters, and the studies of laser SSB which have been done have led to indeterminate or ambiguous results even as to sign. Here, we find that to make changes in satellite dynamic ocean topography (DOT) from the Ice, Clouds, and Land Elevation Satellite (ICESat) period, 2004-2009, to the CryoSat-2 period, 2011-2015, consistent with hydrography plus ocean bottom pressure in the subarctic Greenland and Norwegian seas, we need to correct the ICESat DOT for SSB. On average, ICESat SSB is -18% of significant wave height in excess of 1.7 m.

In the above paper[1], there is an error inTable I. The value “30” in the bottom row, fifth column should be “350.” The corrected table is provided here.

Satellite radar altimeter (RA) measurements are important for continued monitoring of rapidly changing polar regions. In 2010, the European Space Agency launched CryoSat-2 carrying SIRAL, a Ku-band RA with objectives of determining the thickness and extent of sea ice and the topography of the ice sheets. One difficulty with Ku-band radar surveys over snow and ice is unknown penetration of RA signal into snow cover. Improving our understanding of the interactions of RA signals with snow and ice is needed to produce accurate elevation products. To this end, we developed a low-power, ultrawideband (12-18 GHz) RA for airborne surveys to provide fine resolution measurements capable of detecting both scattering from the surface and layers within sea ice and ice sheets. These measurements provide a means of identifying the dominant scattering location of lower resolution RA measurements comparable to satellite-based instruments. We generated two products: a full-bandwidth waveform (FBW) to identify scattering targets at fine resolution and a reduced-bandwidth waveform (RBW) to represent conventional RA measurements. Retrackers are used to generate height estimates over various surface conditions for comparisons. Over ice sheets, the leading-edge tracker provided consistent ice-surface elevation measurements between the FBW and RBW results; however, there were significant differences between the results from the centroid tracker. Over sea ice, the location of the dominant return between the results from snow-covered sea ice is highly variable. This paper provides an overview of RA surveys in polar regions, a description of the CReSIS system, and a discussion of the results.

Satellite and aircraft observations have revealed that remarkable changes in the Earth's polar ice cover have occurred in the last decade. The impacts of these changes, which include dramatic ice loss from ice sheets and rapid declines in Arctic sea ice, could be quite large in terms of sea level rise and global climate. NASA's Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), currently planned for launch in 2015, is specifically intended to quantify the amount of change in ice sheets and sea ice and provide key insights into their behavior. It will achieve these objectives through the use of precise laser measurements of surface elevation, building on the groundbreaking capabilities of its predecessor, the Ice Cloud and Land Elevation Satellite (ICESat). In particular, ICESat-2 will measure the temporal and spatial character of ice sheet elevation change to enable assessment of ice sheet mass balance and examination of the underlying mechanisms that control it. The precision of ICESat-2's elevation measurement will also allow for accurate measurements of sea ice freeboard height, from which sea ice thickness and its temporal changes can be estimated. ICESat-2 will provide important information on other components of the Earth System as well, most notably large-scale vegetation biomass estimates through the measurement of vegetation canopy height. When combined with the original ICESat observations, ICESat-2 will provide ice change measurements across more than a 15-year time span. Its significantly improved laser system will also provide observations with much greater spatial resolution, temporal resolution, and accuracy than has ever been possible before.

In December 2004 the JPL airborne synthetic aperture radar (AIRSAR) flown on the NASA DC-8 acquired fully polarimetric data in the Beaufort Sea at C, L and P-band. This work presents the backscatter coefficients (sigmaHH, sigmaVV, sigmaHV), copolarized ratios (sigmaHH/sigmaVV) and copolarized phase differences (phiHH-VV) at C-band from different young sea-ice types formed in recently frozen leads. Two weeks of RADARSAT-1 imagery from the same region as the AIRSAR data were used in order to identify when and where leads were formed and to estimate the age of the newly formed ice contained within the leads. A known empirical relationship based on freezing degree days was used to estimate the sea-ice thickness. The results indicate that some of the identified thin ice types have characteristic signatures.

The RADARSAT Geophysical Processing System has been processing geophysical data products at ASF and JPL since 1999. The RGPS data products provide an opportunity to improve our understanding of a myriad of processes that affect climate by generating a range of products over the Arctic at 3- and 6 day intervals. These processes include mass balance, heat transfer and momentum transfer between the Arctic Ocean and atmosphere. The RGPS Team is presently processing data acquired by RADARSAT during the winter of 1998-1999 for the seasonal ice zone and the Barents Sea. Data products from other seasons for the Arctic Basin are currently available on the web. We will summarize the some results from the products generated by the ASF RGPS and describe availability of this data set to the general community.

Inverse scattering algorithms for reconstructing the physical properties of sea ice from scattered electromagnetic field data are presented. The development of these algorithms has advanced the theory of remote sensing, particularly in the microwave region, and has the potential to form the basis for a new generation of techniques for recovering sea ice properties, such as ice thickness, a parameter of geophysical and climatological importance. Moreover, the analysis underlying the algorithms has led to significant advances in the mathematical theory of inverse problems. In particular, the principal results include the following. (1) Inverse algorithms for reconstructing the complex permittivity in the Helmholtz equation in one and higher dimensions, based on layer stripping and nonlinear optimization, have been obtained and successfully applied to a (lossless) laboratory system. In one dimension, causality has been imposed to obtain stability of the solution and layer thicknesses can be obtained from the recovered dielectric profile, or directly from the reflection data through a nonlinear generalization of the Paley-Wiener theorem in Fourier analysis. (2) When the wavelength is much larger than the microstructural scale, the above algorithms reconstruct a profile of the effective complex permittivity of the sea ice, a composite of pure ice with random brine and air inclusions. A theory of inverse homogenization has been developed, which in this quasistatic regime, further inverts the reconstructed permittivities for microstructural information beyond the resolution of the wave. Rigorous bounds on brine volume and inclusion separation for a given value of the effective complex permittivity have been obtained as well as an accurate algorithm for reconstructing the brine volume from a set of values. (3) Inverse algorithms designed to recover sea ice thickness have been developed. A coupled radiative transfer-thermodynamic sea ice inverse model has accurately reconstructed the growth of a thin, artificial sea ice sheet from time-series electromagnetic scattering data.

Satellite radar interferometry (SRI) provides an important new tool for determining ice-flow velocity. Interferometric measurements made from a single-track direction are sensitive only to a single component of the three-component velocity vector. Observations from along three different track directions would allow the full velocity vector to be determined. A north/south-looking synthetic aperture radar (SAR) could provide these observations over large portions of the globe, but not over large areas of the polar ice sheets. The authors develop and demonstrate a technique that allows the three-component velocity vector to be estimated from data acquired along two track directions (ascending and descending) under a surface-parallel flow assumption. This technique requires that there are accurate estimates of the surface slope, which are also determined interferometrically. To demonstrate the technique, the authors estimate the three-component velocity field for the Ryder Glacier, Greenland. Their results are promising, although they do not have yet ground-truth data with which to determine the accuracy of their estimates.

The connections between laboratory measurements and remote-sensing observations of sea ice are explored. The focus of this paper is on thin ice, which is more easily simulated in a laboratory environment. The authors summarize results of C-band scatterometer measurements and discuss how they may help in the interpretation of remote-sensing data. They compare the measurements with observations of thin ice from ERS and airborne radar data sets. They suggest that laboratory backscatter signatures should serve as bounds on the interpretation of remote-sensing data. They examine these bounds from the perspective of thin ice signatures, the effect of temperature, and surface processes, such as frost flowers and slush on these signatures. Controlled experiments also suggest new directions in remote-sensing measurements. The potential of polarimetric radar measurements in the retrieval of thickness of thin ice is discussed. In addition to the radar results, the authors discuss the importance of low-frequency passive measurements with respect to the thickness of thin ice.

To investigate effects of diurnal thermal cycles on C-band polarimetric backscatter and millimeter-wave emission from sea ice, the authors carried out a winter experiment at the outdoor geophysical research facility (GRF) in the cold regions research and engineering laboratory (CRREL), the ice sheet grew from open sea water to a thickness of 10 cm in 2.5 days, during which they took polarimetric backscatter data with a C-band scatterometer, interlaced with brightness temperature measurements at 90 GHz in conjunction with meteorological and sea ice characterizations. The initial ice growth in the late morning was slow due to high insolation. As the air temperature dropped during the night, the growth rate increased significantly. Air temperature changed drastically from about -12 to -36/spl deg/C between day and night, the diurnal thermal cycle repeated itself the next day and the growth rate varied in the same manner. Ice temperature profiles clearly show the diurnal response in the ice sheet with a lag of 2.5 h behind the time of the maximum short-wave incident solar radiation. The diurnal cycles are also evident in the millimeter-wave brightness temperature data, measured sea ice backscatter revealed substantial diurnal variations up to 6 dB with repeatable cycles in synchronization with the temperature cycles and the brightness temperature modulations, the diurnal cycles in backscatter indicate that the dominant scattering mechanism related to thermodynamic processes in sea ice is reversible, a diurnal backscatter model based on sea ice electrodynamics and thermodynamics explains the observed diurnal signature. This work shows that diurnal effects are important for inversion algorithms to retrieve sea ice geophysical parameters from remote sensing data acquired with a satellite synthetic aperture radar (SAR) or scatterometer on Sun-synchronous orbits.

This paper describes a classification algorithm using dual-polarized scatterometer measurements to identify the edge of the sea ice cover. The distinct polarization scattering signatures of sea ice and open water are discussed and illustrated with the dual-polarized radar measurements from the Seasat-A scatterometer (SASS). The analysis of SASS data suggests that the ratio of vertical and horizontal polarization backscatter, denoted as the copol ratio, is a useful discriminator of sea ice and open ocean. A simple classification algorithm using the thresholds of the copol ratio and backscatter levels is proposed. The feasibility of this algorithm is demonstrated using the SASS data from the single-sided, dual-polarization mode. The results indicate that the dual-polarized measurements from the NASA scatterometer (NSCAT) can be used to produce routine maps of sea ice edges.

Both topography and motion information are present in repeat pass ERS-1 interferograms over ice sheets. The authors demonstrate that the topography is separable from the surface displacement field when a sequence of radar images are available. If the velocity field is constant over the time span of observation, the topography can be derived from differential interferograms formed from sequential observations. With this measurement, a pure displacement field can then be obtained by removal of the topographic contribution to the interferometric phase at each pixel. Further, they discuss how the vertical and horizontal components of displacement affect the interferometrically-derived motion field. They illustrate their approach with four successive (3-day repeat) ERS-1 images of a flow feature in northeastern Greenland.

Several automatic methods have been developed to classify sea ice types from fully polarimetric synthetic aperture radar (SAR) images, and these techniques are generally grouped into supervised and unsupervised approaches. In previous work, supervised methods have been shown to yield higher accuracy than unsupervised techniques, but suffer from the need for human interaction to determine classes and training regions. In contrast, unsupervised methods determine classes automatically, but generally show limited ability to accurately divide terrain into natural classes. In this paper, a new classification technique is applied to determine sea ice types in polarimetric and multifrequency SAR images, utilizing an unsupervised neural network to provide automatic classification, and employing an iterative algorithm to improve the performance. The learning vector quantization (LVQ) is first applied to the unsupervised classification of SAR images, and the results are compared with those of a conventional technique, the migrating means method. Results show that LVQ outperforms the migrating means method, but performance is still poor. An iterative algorithm is then applied where the SAR image is reclassified using the maximum likelihood (ML) classifier. It is shown that this algorithm converges, and significantly improves classification accuracy. The new algorithm successfully identifies first-year and multiyear sea ice regions in the images at three frequencies. The results show that L- and P-band images have similar characteristics, while the C-band image is substantially different. Classification based on single features is also carried out using LVQ and the iterative ML method. It is found that the fully polarimetric classification provides a higher accuracy than those based on a single feature. The significance of multilook classification is demonstrated by comparing the results obtained using four-look and single-look classifications.>

A procedure for monitoring the local age distribution of the Arctic sea ice cover is presented. The age distribution specifies the area covered by ice in different age classes. In our approach, a regular array of grid points is defined initially on the first image of a long time series, and an ice tracker finds the positions of those points in all subsequent images of the series. These Lagrangian points mark the corners of a set of cells that move and deform with the ice cover. The area of each cell changes with each new image or time step. A positive change indicates that ice in a new age class was formed in the cell. A negative change is assumed to have ridged the youngest ice in the cell, reducing its area. The ice in each cell ages as it progresses through the time series. The area of multiyear ice in each cell is computed using an ice classification algorithm. Any area that is not accounted for by the young ice or multiyear ice is assigned to a category of older first-year ice. We thus have a fine age resolution in the young end of the age distribution, and coarse resolution for older ice. The age distribution of the young ice can be converted to a thickness distribution using a simple empirical relation between accumulated freezing-degree days and ice thickness, or using a more complicated thermodynamic model. We describe a general scheme for implementing this procedure for the Arctic Ocean from fall freeze-up until the onset of melt in the spring. The concept is illustrated with a time series of five ERS-1 SAR images spanning a period of 12 days. Such a scheme could be implemented with RADARSAT SAR imagery to provide basin-wide ice age and thickness information.

During the two different overflights of the Bonanza Creek Experimental Forest (near Fairbanks, Alaska) by the NASA/JPL radar polarimeter in March 1988, the environmental conditions over the region changed significantly with temperatures ranging from unseasonably warm (1 to 9/spl deg/C) during one day to well below freezing (-8 to -15/spl deg/C) during the other. The moisture content of the snow and trees changed from a liquid to frozen state causing significant changes in the radiometric and polarimetric responses of the forest to the radar wave. The L-band polarimetric observations are summarized in this paper. Up to a 6 dB change in the backscatter was observed in certain forest stands at L-band. Features extracted from the Stokes matrices of the same stands from the thawed and frozen days suggest the changes in the relative contribution of the different scattering mechanisms to the radar return. Comparison of the polarimetric signatures indicate relatively higher contribution from diffuse scatterers on the thawed day than on the frozen day. The sensitivity of the polarimetric signatures to changing environmental conditions is clearly demonstrated.>

Changes in the seasonal CO/sub 2/ flux of the boreal forests may result from increased atmospheric CO/sub 2/ concentrations and associated global warming patterns. To monitor this potential change, a combination of information derived from remote sensing data, including forest type and growing season length, and ecophysiological models which predict the CO/sub 2/ flux and its seasonal amplitude based on meteorological data, are required. The authors address the use of synthetic aperture radar (SAR) to map forest type and monitor canopy and soil freeze/thaw, which define the growing season for conifers, and leaf on/off, which defines the growing season for deciduous species. Aircraft SAR (AIRSAR) data collected in March 1988 during a freeze/thaw event are used to generate species maps and to determine the sensitivity of SAR to canopy freeze/thaw transitions. These data are also used to validate a microwave scattering model which is then used to determine the sensitivity of SAR to leaf on/off transitions and soil freeze/thaw. Finally, a CO/sub 2/ flux algorithm is presented which utilizes SAR data and an ecophysiological model to estimate CO/sub 2/ flux. CO/sub 2/ flux maps are generated, from which areal estimates of CO/sub 2/ flux are derived. >

A new method for symmetrizing polarimetric scattering matrices is applied to the polarimetric synthetic aperture radar (SAR) images acquired over Mount Shasta. This method symmetrizes the cross-polarized responses in the polarimetric images using a 2*2 matrix derived from the image itself and based on the reciprocal property of natural distributed targets. The covariance parameters of the in-scene trihedral reflectors are presented to demonstrate the effectiveness of this method. The results are also compared with those obtained by the symmetrization technique employed by POLCAL, before and after crosstalk removal. Before crosstalk is removed from the images, there were no significant differences between the results obtained by the POLCAL method and the new method for the covariance parameters of trihedral reflectors. After crosstalk removal, using distributed targets with reflection symmetry, the new symmetrization method outperformed the POLCAL method.>

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the psi -s curve. The first algorithm uses normalized correlation to match the psi -s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.>