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

Zygmuntowska, Marta; Khvorostovsky, K.; Helm, Veit; Sandven, Stein

doi:10.5194/tc-7-1315-2013

Cited by 40 publications

(64 citation statements)

References 47 publications

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“…To further analyse the link between the variability of the ice surface properties and the radar freeboard discrepancy between Envisat and CryoSat-2, the waveform pulse peakiness (PP) can be analysed. For nadir-looking radar altimeters such as Envisat and CryoSat-2, high values of PP indicate the presence of flat and specular FYI while low values of PP indicate the presence of rough and snow-covered MYI (Zygmuntowska et al, 2013). This phenomenon is also visible on the waveform echoes shown in Fig.…”

Section: Comparison Of Gridded Radar Freeboard Estimatesmentioning

confidence: 84%

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Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

et al. 2017

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Abstract. Over the past decade, sea-ice freeboard has been monitored with various satellite altimetric missions with the aim of producing long-term time series of ice thickness. While recent studies have demonstrated the capacity of the CryoSat-2 mission (2010-present) to provide accurate freeboard measurements, the current estimates obtained with the Envisat mission (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) still require some large improvements.In this study, we first estimate Envisat and CryoSat-2 radar freeboard by using the exact same processing algorithms. We then analyse the freeboard difference between the two estimates over the common winter periods (November 2010-April 2011 and November 2011-March 2012. The analysis of along-track data and gridded radar freeboard in conjunction with Envisat pulse-peakiness (PP) maps suggests that the discrepancy between the two sensors is related to the surface properties of sea-ice floes and to the use of a threshold retracker.Based on the relation between the Envisat pulse peakiness and the radar freeboard difference between Envisat and CryoSat-2, we produce a monthly CryoSat-2-like version of Envisat freeboard. The improved Envisat data set freeboard displays a similar spatial distribution to CryoSat-2 (RMSD = 1.5 cm) during the two ice growth seasons and for all months of the period of study.The comparison of the altimetric data sets with in situ ice draught measurements during the common flight period shows that the improved Envisat data set (RMSE = 12-28 cm) is as accurate as CryoSat-2 (RMSE = 15-21 cm) and much more accurate than the uncorrected Envisat data set (RMSE = 178-179 cm).The comparison of the improved Envisat radar freeboard data set is then extended to the rest of the Envisat mission to demonstrate the validity of PP correction from the calibration period. The good agreement between the improved Envisat data set and the in situ ice draught data set (RMSE = 13-32 cm) demonstrates the potential of the PP correction to produce accurate freeboard estimates over the entire Envisat mission lifetime.

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Section: Comparison Of Gridded Radar Freeboard Estimatesmentioning

confidence: 84%

“…To average CryoSat-2 and Envisat waveform echoes, we use the same methodology as in the study by Zygmuntowska et al (2013). All waveform echoes are normalised and shifted so their maximum power is located in the same sampling bin (the 67th bin here).…”

Section: Comparison Of Cryosat-2 and Envisat Waveform Echoesmentioning

confidence: 99%

Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

et al. 2017

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“…11. This information could be used in the future to obtain an ice-type classification directly from the CS-2 data, similar to the approach of Zygmuntowska et al (2013). The gradient inside the MYI area in Fig.…”

Section: Differences Between the Retrievals Of Different Thresholdsmentioning

confidence: 99%

Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation

et al. 2014

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Abstract. 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 K u band synthetic aperture radar altimeter SIRAL (Synthetic Aperture Interferometric Radar Altimeter), 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 of the order of centimetres are necessary to achieve the required accuracy of the freeboardto-thickness conversion. Besides uncertainties of the actual sea-surface height and limited knowledge of ice and snow properties, the composition of radar backscatter 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-2 measurement. In this study 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 the current literature. By using the selected retrackers and additionally results from airborne validation measurements, we evaluate the uncertainties of sea-ice freeboard and higher-level products that arise from the choice of the retracker threshold only, independent of the uncertainties related to snow and ice properties. Our study shows that the choice of retracker thresholds does have a significant impact on magnitudes of estimates of sea-ice freeboard and thickness, but that the spatial distributions of these parameters are less affected.

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“…In radar altimetry, the waveform abruptness is commonly called "pulse peakiness" (e.g. Peacock and Laxon, 2004;Zygmuntowska et al, 2013).…”

Section: Determination Of Waveform Abruptness From Level 1b Datamentioning

confidence: 99%

Self-affine subglacial roughness: consequences for radar scattering and basal water discrimination in northern Greenland

et al. 2017

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Abstract. Subglacial roughness can be determined at a variety of length scales from radio-echo sounding (RES) data either via statistical analysis of topography or inferred from basal radar scattering. Past studies have demonstrated that subglacial terrain exhibits self-affine (power law) roughness scaling behaviour, but existing radar scattering models do not take this into account. Here, using RES data from northern Greenland, we introduce a self-affine statistical framework that enables a consistent integration of topographicscale roughness with the electromagnetic theory of radar scattering. We demonstrate that the degree of radar scattering, quantified using the waveform abruptness (pulse peakiness), is topographically controlled by the Hurst (roughness power law) exponent. Notably, specular bed reflections are associated with a lower Hurst exponent, with diffuse scattering associated with a higher Hurst exponent. Abrupt waveforms (specular reflections) have previously been used as a RES diagnostic for basal water, and to test this assumption we compare our radar scattering map with a recent prediction for the basal thermal state. We demonstrate that the majority of thawed regions (above pressure melting point) exhibit a diffuse scattering signature, which is in contradiction to the prior approach. Self-affine statistics provide a generalised model for subglacial terrain and can improve our understanding of the relationship between basal properties and ice-sheet dynamics.

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

Cited by 40 publications

References 47 publications

Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

Comparison of CryoSat-2 and ENVISAT radar freeboard over Arctic sea ice: toward an improved Envisat freeboard retrieval

Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation

Self-affine subglacial roughness: consequences for radar scattering and basal water discrimination in northern Greenland

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