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During the past decades, radar sounder (RS) instruments have been effectively used to detect subglacial lakes (SLs). SLs appear as flat, smooth, and bright reflectors in RS radargrams. The visual interpretation has been the main approach to SL detection in radargrams. However, this approach is subjective and inappropriate for processing large amounts of radargrams. While the analysis of RS data for understanding the subglacial hydrology has recently received increased attention, the literature on the development of automatic methods specifically designed for SL detection is still limited. In order to fill this gap, in this paper, we propose a novel automatic technique for SL detection. The technique is made up of two steps: 1) feature extraction and 2) automatic detection. In the first step, we define and extract three families of features for discriminating between the lake and nonlake radar reflections. The features model locally the basal topography, the shape of the basal reflected waveforms, and the statistical properties of the basal signal. In the second step, we provide the features as input to a support vector machine classifier to perform the automatic SL detection. The proposed technique has been applied to radargrams acquired over two large regions in East Antarctica and Siple Coast. The obtained results, which are validated both quantitatively and qualitatively, confirm the robustness of the features and their capabilities to effectively characterize SLs. Moreover, they prove the potentiality of the method to process large amounts of radargrams and update the current SL inventory. [ABSTRACT FROM AUTHOR]

In this paper, a method to distinguish a wet or dry bedrock-ice interface is proposed. It is based on the analysis of radio echo sounding (RES) measurements, a widely employed method for determining bedrock topography in Antarctica. In particular, the RES system has played an important role in subglacial lake exploration and hydrogeological studies at the bedrock-ice interface. Recently, bedrock characterization has been improved through the analysis of the power of radar echoes. Signal power depends on bedrock reflectivity and its specific physical condition. In this paper, a linear model describing the loss term (internal ice absorption) is proposed. This model, together with other known quantities, contributes toward an assessment of power variation of bedrock reflectivity in order to determinate wet and dry bedrock interfaces in the Dome C region in Antarctica. [ABSTRACT FROM AUTHOR]

In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface- elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to atmospheric path delay. This paper complements previous studies in! the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradlometer (MODIS) onboard Terra Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus- cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an I , ample, the average path delays for FOV : 167 µad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica illustrated. [ABSTRACT FROM AUTHOR]

The C-band EUMETSAT Advanced Scatterometer (ASCAT) was launched in 2007, and provides backscatter measurements with excellent azimuth and incidence angle diversity in polar regions. C-band backscatter measurements can be used to retrieve near-surface snow/firn properties such as grain size and accumulation rate, however the Antarctic Ice Sheet (AIS) exhibits strong microwave backscatter anisotropy as a function of both incidence and azimuth angles, and this anisotropy must be well understood before such physical parameter retrieval can be accurately performed. This paper presents a detailed comparison of several different parameterizations of both the azimuth and the incidence anisotropy. Parameterizations used here result in residuals similar to the radiometric performance of ASCAT, indicating accurate characterization of the anisotropy. The analysis of these parameterizations provides an insight into the physical mechanisms taking place near the surface of the AIS. 30-day composite maps of several parameters are presented, and discussed in the context of near-surface glaciology. This anisotropy characterization will form the basis of a technique for extraction of physical parameters of the AIS. [ABSTRACT FROM PUBLISHER]

This paper presents details of techniques for generating thermal infrared and visible composite images from the cloud-free portions of temporally closely spaced MODerate resolution Imaging Spectroradiometer (MODIS) images, with a focus on studies of landfast sea ice along the East Antarctic coast. Composite image inclusion criteria are based on modified MODIS Earth Observing System cloud mask product results. The compositing process presented places emphasis on retaining maximum spatial resolution while minimizing storage space requirements. Composite images can be produced either as a regular product (e.g., on a ten-day grid), or dynamically (whenever enough information is acquired to produce a new output image). The techniques presented are applicable at any latitude, are available for all MODIS channels at their native resolution, can combine Aqua and Terra images, and can produce maps in any output projection. However, due to the polar orbit of NASA's Terra a Aqua satellites which host the MODIS instrument, more frequent coverage is produced at higher latitudes. Thus, the techniques presented are particularly applicable to polar research. Examples of composite image generation of the landfast sea ice around the Mertz Glacier region, East Antarctica, are included for both winter and summer. [ABSTRACT FROM AUTHOR]

In this paper, a new digital elevation model (DEM) is derived for the ice sheet in western Dronning Maud Land, Antarctica. It is based on differential interferometric synthetic aperture radar (SAR) from the European Remote Sensing 1/2 (ERS-1/2) satellites, in combination with ICESat's Geoscience Laser Altimeter System (GLAS). A DEM mosaic is compiled out of 116 scenes from the ERS-1 ice phase in 1994 and the ERS-1/2 tandem mission between 1996 and 1997 with the GLAS data acquired in 2003 that served as ground control. Using three different SAR processors, uncertainties in phase stability and baseline model, resulting in height errors of up to 20 m, are exemplified. Atmospheric influences at the same order of magnitude are demonstrated, and corresponding scenes are excluded. For validation of the DEM mosaic, covering an area of about 130 000 km² on a 50-m grid, independent ICESat heights ,(2004-2007), ground-based kinematic GPS (2005), and airborne laser scanner data (ALS, 2007) are used. Excluding small areas with low phase coherence, the DEM differs in mean and standard deviation by 0.5 + / - 10.1, 1.1 + / - 6.4, and 3.1 + / - 4.0 m from ICESat, GPS, and ALS, respectively. The excluded data points may deviate by more than 50 m. In order to suppress the spatially variable noise below a 5-m threshold, 18% of the DEM area is selectively averaged to a final product at varying horizontal spatial resolution. Apart from mountainous areas, the new DEM outperforms other currently available DEMs and may serve as a benchmark for future elevation models such as from the TanDEM-X mission to spatially monitor ice sheet elevation. [ABSTRACT FROM AUTHOR]

In this paper, several techniques to improve the processing and analysis of decadal elevation-change time series (ECTS) constructed using satellite radar altimeter data over the Antarctic ice sheet are described. First, a method that improves both the quality and quantity of ice-sheet ECTS is introduced. By dynamically selecting the reference month used in constructing ECTS for a given local region, the maximum number of elevation-change estimates are used in a matrix processing technique. This can improve ECTS quality while also generating ECTS in new areas, leading to a significant increase in spatial coverage. Next, an improved autoregressive (IAR) approach is presented for modeling nonlinear medium-period variations in decadal Antarctic ECTS. This builds upon previous work where an AR model was used to characterize seasonal and interannual variations in ice-sheet ECTS. The improved approach avoids overdecomposition by adopting an iterative local average filter to estimate nonlinear medium-period trends. Monte Carlo simulations show that the IAR method significantly outperforms the AR method when realistic nonlinear trends are present. Because of these characteristics, the IAR model is able to adequately characterize seasonal, interannual, and medium-period nonlinear signals present in decadal ECTS and extract their long-term trends with very small error. This is important for accurate measurement of decadal elevation change over the Antarctic ice sheet and for assessing the impact of these changes on the global sea level. [ABSTRACT FROM AUTHOR]

Satellite data are the most suitable tools for monitoring time and spatial variations of snow covered areas and for studying snow characteristics on a global scale. Current knowledge of the microwave emission from the deep ice sheet in Antarctica is limited by the lack of low-frequency satellite sensors and by their inadequate knowledge of the physical effects governing microwave emission at wavelengths exceeding 5 cm. On the other hand, in addition to the interest related to climatic changes and to glaciological and hydrological applications, there is growing interest, on the part of the remote sensing community, in using the Antarctic and, in particular, the Dome-C plateau where the Concordia station is located, for calibrating and validating data of satellite-borne microwave and optical radiometers. This is because of the size, structure, spatial homogeneity, and thermal stability of this area. With a view to the future launches of two new low-frequency spaceborne sensors Soil Moisture and Ocean Salinity mission and Aquarius, an experiment was carried out at Dome-C, thanks to financial support from European Space Agency, aimed at evaluating the stability and the absolute value of the L- and C-band brightness temperature Tb. This paper presents a report on the experimental campaign, the characteristics of the radiometric measurements, and on the main results. The C-band Tb data indicated a diurnal cycle amplitude of a few kelvin. It was confirmed that this takes place as a consequence of observed variability in the physical temperature of the top 4 m of the snowpack around the mean surface value of -24 °C. In contrast, the L-band data indicated extremely stable Tb values of 192.32 K (1σ = 0.18 K) and 190.77 K (1σ = 0.57 K) at θ = 45° and θ = 56°, respectively. [ABSTRACT FROM AUTHOR]