Assessing firn processes withinGreenland and Antarctica is important in recent decades, as melt–refreezing processes can result in accelerated meltwater runoff and land-ice discharge. Meanwhile, surface and depth hoar crystal formation have an impact on the surface warming and surface mass balance (SMB) of the ice sheets. Typically, these processes are monitored using in situ firn core measurements, or estimated using climate models. However, the in situ measurements are sparse due to the harsh conditions of the polar regions, while the climate models are based on simplified assumptions which introduce various uncertainties. The recent advancements of satellite remote sensing techniques provide the opportunity to monitor the firn processes over the ice sheets, due to a vast spatial coverage and a frequent revisit time.

This thesis explores the capability of satellite radiometers, scatterometers and altimeters to assess firn processes, including firn density variation and melt–refreezing processes. Conventionally, satellite radiometers and scatterometers are used in detecting melt events over the ice sheets, based on the principle that melt events change the dielectric constant within the firn layer, while the satellite altimeter is typically used for estimating surface elevation changes over ice sheets. This thesis, on the contrary, explores the feasibility of using radiometers and scatterometers to assess the dry-firn density; meanwhile, it assesses the potential of using the altimeters to observe the melt– refreezing events of firn. The rationale behind this thesis is that the long-term variations in satellite radiometer and scatterometer observations depend on the changing scattering properties due to variations in near-surface firn densities, which provides the opportunity for using satellite radiometer and scatterometer observations to estimate long-term changes in firn densities. Meanwhile, the shape of the waveform obtained by a satellite radar altimeter can be influenced by volume and surface scattering of firn. By assessing the variation of firn scattering properties using the waveform information, the occurrence and impact of melt–refreezing processes within the firn layer can be assessed. Therefore, more potentials lie in the application and interpretation of remote sensing data in the studies of the cryosphere. To study the aforementioned application…
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Firn density plays a crucial role in assessing the surface mass balance of the Antarctic ice sheet. However, our understanding of the spatial and temporal variations in firn density is limited due to (i) spatial and temporal limitations of in situ measurements, (ii) potential modelling uncertainties, and (iii) lack of firn density products driven by satellite remote-sensing data. To address this gap, this paper explores the potential of satellite microwave radiometer (Special Sensor Microwave Imager/Sounder (SSMIS)) and scatterometer (Advanced Scatterometer (ASCAT)) observations for assessing spatial and temporal dynamics of dry-firn density over the Antarctic ice sheet. Our analysis demonstrates a clear relation between density anomalies at a depth of 40 cm and fluctuations in satellite observations. However, a linear relationship with individual satellite observations is insufficient to explain the spatial and temporal variation in snow density. Hence, we investigate the potential of a non-linear random forest (RF) machine learning approach trained on radiometer and scatterometer data to derive the spatial and temporal variations in dry-firn density. In the estimation process, 10 years of SSMIS observations (brightness temperature) and ASCAT observations (backscatter intensity) is used as input features to a random forest (RF) regressor. The regressor is first trained on time series of modelled density and satellite observations at randomly sampled pixels and then applied to estimate densities in dry-firn areas across Antarctica. The RF results reveal a strong agreement between the spatial patterns estimated by the RF regressor and the modelled densities. The estimated densities exhibit an error of ±10 kg m−3 in the interior of the ice sheet and ±35 kg m−3 towards the ocean. However, the temporal patterns show some discrepancies, as the RF regressor tends to overestimate summer densities, except for high-elevation regions in East Antarctica and specific areas in West Antarctica. These errors may be attributed to underestimations of short-term or seasonal variations in the modelled density and the limitations of RF in extrapolating values outside the training data. Overall, our study presents a potential method for estimating unknown Antarctic firn densities using known densities and satellite parameters.@en

Satellite radar altimetry has been an important tool for cryospheric applications such as measuring ice-sheet height or assessing anomalies in snow and ice properties (e.g. the extensive melt in Greenland in 2012). Although accurate height measurements are key for such applications, slope-induced errors due to undulating topography within the kilometre-wide beam-limited footprint can cause multi-metre errors. Two main correction methods that have been developed (referred to as the slope- and point-based methods) neglect either the actual topography or the actual footprint that can be estimated by a combination of the leading edge and topography. Therefore, a leading edge point-based (LEPTA) method is presented that corrects for the slope-induced error by including the leading edge information of the radar waveform to determine the impact point. The principle of the method is that only the points on the ground that are within the range determined by the beginning and end of the leading edge are used to determine the impact point. Benchmarking of the LEPTA method against the slope- and point-based methods based on CryoSat-2 Low Resolution Mode (LRM) acquisitions over Greenland in 2019 shows that, when compared to ICESat-2 observations, the LEPTA method has a stable performance both in the flat, interior regions of Greenland and in regions with more complex topography. The median difference between the slope-corrected CryoSat-2 heights using LEPTA and the ICESat-2 heights is at the millimetre level, whereas the slope and point-based methods can have a 0.21 and 0.48 m difference, respectively, and the Level-2I (L2I) data provided by ESA have a 0.01 m difference. The median absolute deviation of height differences between CryoSat-2 and ICESat-2, which we use as an indicator of the variation in errors, is also the lowest for LEPTA (0.09 m) in comparison to the aforementioned methods (0.19 m for slope method and 0.10 m for point-based method) and ESA Level-2 data (0.14 m). Although ESA Level-2 products and the point-based method have good performance in either the median or the median absolute deviation, LEPTA shows a good performance in both metrics. Based on that, we recommend considering LEPTA for obtaining accurate height measurements with radar altimetry data, especially towards the margins of the LRM coverage where the surface slopes increase.@en

Surface meltwater drains on several Antarctic ice shelves, resulting in surface and sub-surface lakes that are potentially critical for the ice shelf collapse. Despite these phenomena, our understanding and assessment of the drainage and refreezing of these lakes is limited, mainly due to lack of field observations and to the limitations of optical satellite imagery during polar night and in cloudy conditions. This paper explores the potential of backscatter intensity and of interferometric coherence and phase from synthetic aperture radar (SAR) imagery as an alternative to assess the dynamics of meltwater lakes. In four case study regions over Amery and Roi Baudouin ice shelves, East Antarctica, we examine spatial and temporal variations in SAR backscatter intensity and interferometric (InSAR) coherence and phase over several lakes derived from Sentinel-1A/B C-band SAR imagery. Throughout the year, the lakes are observed in a completely frozen state, in a partially frozen state with a floating ice lid and as open-water lakes. Our analysis reveals that the meltwater lake delineation is challenging during the melting period when the contrast between melting snow and lakes is indistinguishable. Despite this finding, we show using a combination of backscatter and InSAR observations that lake dynamics can be effectively captured during other non-summertime months. Moreover, our findings highlight the utility of InSAR-based observations for discriminating between refrozen ice and sub-surface meltwater and indicate the potential for phase-based detection and monitoring of rapid meltwater drainage events. The potential of this technique to monitor these meltwater change events is, however, strongly determined by the satellite revisit interval and potential changes in scattering properties due to snowfall or melt events.@en