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This Ph.D. thesis presents advancements in the analysis of radar sounder data. Radar sounders (RSs) are remote sensors that transmit an electromagnetic (EM) wave at the nadir direction that penetrates the subsurface. The backscattered echoes captured by the RS antenna are coherently summed to generate an image of the subsurface profile known as a radargram. The first focus of this work is to automate the segmentation of radargrams using deep learning methodologies while minimizing the need for labeled training data. The surge in radar sounding data volume necessitates efficient automated methods. However, the amount of training labeled data in this field is strongly limited. This first work introduces a transfer learning framework based on deep learning tailored for radar sounder data that minimizes the training data requirements. This method automatically identifies and segments geological units within radargrams acquired in the cryosphere. With the cryosphere being a critical indicator of climate change, understanding its dynamics is paramount. Geological details within radargrams, such as the basal interface or the inland and floating ice, are key to this understanding. Our work shifts the focus to uncharted territory: the coastal areas of Antarctica. Novel targets such as floating ice and crevasses add complexity to the data, but the transfer learning framework minimizes the need for extensive labeled training data. The results, based on data from Antarctica, confirm the effectiveness of the approach, promising adaptability to other targets and radar data from existing and future planetary missions like RIME and SRS. The second focus of this thesis explores the generation of novel and improved geological data products by harnessing the unique characteristics of radar sounder data, including subsurface information and so-called “unwanted” clutter. The thesis introduces two methods that use RS data to generate geological products. The first contribution proposes a global high-frequency radar image of Mars. This product delivers a novel, comprehensive global radar image of Mars, capturing both surface and shallow subsurface structures. The method unlocks the potential to explore concealed Martian geology and further understand Martian geological features like dust, revealing possible candidate large dust deposits that were unknown until now. Furthermore, this method can potentially offer insights into celestial bodies beyond Mars, such as the detection of new lunar facets and Venusian geological formations. The third contribution aims to generate Digital Elevation Models (DEM) from single swath radargrams. The activity addresses the challenge of precise bed DEM estimations in Antarctica. Bed topography is critical in ice modeling and mass balance calculations, yet existing methods face limitations. To overcome these, we employ a generative adversarial network (GAN) approach that utilizes clutter information from single radargrams. This innovative technique promises to refine bed DEMs and enhance our understanding of glacier erosion and ice dynamics. The proposed methodologies were validated with data acquired on both Earth and Mars, showing promising results and confirming their effectiveness.

Lakes play a major role in the global carbon (C) cycle, despite making up a small area of earth’s surface. Lakes receive, transport and process sizable amounts of C, emitting a substantial amount of the greenhouse gases, carbon dioxide (CO2) and methane (CH4), into the atmosphere. Ice-covered lakes are particularly sensitive to climate change, as future reductions to the duration of lake ice cover will have profound effects on the biogeochemical cycling of C in lakes. It is still largely unknown how reduced ice cover duration will affect CO2 and CH4 emissions from ice-covered lakes. Thus, the primary aim of this thesis was to fill this knowledge gap by monitoring the spatial and temporal dynamics of CO2 and CH4 in ice-covered lakes. The results of this thesis demonstrate that below ice CO2 and CH4 were spatially and temporally variable. Nutrients were strongly linked to below ice CO2 and CH4 oxidation variations across lakes. In addition, below ice CO2 was generally highest in small shallow lakes, and in bottom waters. Whilst below ice CH4 was elevated in surface waters near where bubbles from anoxic lake sediment were trapped. During the ice-cover period, CO2 accumulation below ice was not linear, and at ice-melt incomplete mixing of lake waters resulted in a continued CO2 storage in bottom waters. Further, CO2 transported from the catchment and bottom waters contributed to high CO2 emissions. The collective findings of this thesis indicate that CO2 and CH4 emissions from ice-covered lakes will likely increase in the future. The strong relationship between nutrients and C processes below ice, imply that future changes to nutrient fluxes within lakes will influence the biogeochemical cycling of C in lakes. Since catchment and lake sediment C fluxes play a considerable role in below ice CO2 and CH4 dynamics, changes to hydrology and thermal stability of lakes will undoubtedly alter CO2 and CH4 emissions. Nevertheless, ice-covered lakes constitute a significant component of the global C cycle, and as such, should be carefully monitored and accounted for when addressing the impacts of global climate change.

An emerging trend towards non-laboratory based biological and microbiological marker analysis is occurring in multiple sectors of science and industry. In the medical sector, these trends have demonstrated that conducting sample analyses away from centralised laboratories not only makes analyses quicker and more convenient (e.g. a home pregnancy test), but can offer services that are otherwise impractical (e.g. mobile laboratories to diagnose disease in the developing world). In the environmental sector, similar benefits, plus the ability to develop and test hypotheses, protocols and sampling strategies within a field campaign, are possible with in-field analyses. Icy environments in particular would benefit from in situ or in-field life detection as they are typically remote, and hence impart high logistical costs for repeated field campaigns and associated sample return with the implication that the efficiency of scientific return is poor. Unfortunately, most equipment and protocols developed for microbiological analyses in other sectors of science and industry are unsuitable for direct application to in-field use in icy environments because of poor compatibility with icy environment sample matrices and frequently inappropriate microbiological targets. Hence within this work, two hypotheses were tested: that (i) microbiological detection infield in icy environments is possible and through this (ii) unique and more efficient scientific studies can be conducted. Cont/d.

Because of climate change and resource development there is an ongoing increase in the attention directed towards high latitude areas. Over the last years, warming in the Arctic has accelerated quickly. The warming climate can possibly lead to thawing of ground ice, which in turn leads to alterations of the cryosphere. This can have a huge influence on the terrestrial hydrology of the Arctic and, more specifically, on the presence and distribution of lakes in arctic regions since both are coupled to subsurface ice. In this thesis data from remote sensing were used to look at the change in the size distribution of lakes for the Nadym catchment in northern Russia. The aim was to find out if there has been an increase or decrease in the number of lakes in the area over the past years. Results suggest that there were 229 lakes less (representing a 4% decrease) in 2007–2009 compared to 1987, indicating that lakes are slowly disappearing. Also, the total lake surface area decreased with 5%. Almost half of the lakes that disappeared (49%) can be found among the smallest lakes ranging between 10–20 ha. In the entire catchment this size class was also found to be the class with by far the highest number of lakes.

This thesis focuses on the physics of static sea-level changes following variations in the distribution of grounded ice and the influence of these changes on the stability and dynamics of marine ice sheets. Gravitational, deformational and rotational effects associated with changes in grounded ice mass lead to markedly non-uniform spatial patterns of sea-level change. I outline a revised theory for computing post-glacial sea-level predictions and discuss the dominant physical effects that contribute to the patterns of sea-level change associated with surface loading on different timescales. I show, in particular, that a large sea-level fall (rise) occurs in the vicinity of a retreating (advancing) ice sheet on both short and long timescales. I also present an application of the sea-level theory in which I predict the sea-level changes associated with a new model of North American ice sheet evolution and consider the implications of the results for efforts to establish the sources of Meltwater Pulse 1A. These results demonstrate that viscous deformational effects can influence the amplitude of sea-level changes observed at far-field sea-level sites, even when the time window being considered is relatively short (≤ 500 years). / Earth and Planetary Sciences

Fully-polarimetric UAVSAR data of Hofsjokull Ice Cap, central Iceland, taken in June 2009 was decomposed using Pauli-based coherent decomposition as well as Cloude and H/A/alpha eigenvector-based decomposition methods. The goals of this research were to evaluate the effect of the near-surface conditions of temperate glaciers on polarized SAR data and investigate the potential of creating a model of the radar scattering mechanisms based on the decomposed elements and local temperature. The results of this data analysis show a strong relationship between the Pauli and H/A/alpha decomposition elements and the near-surface conditions. Fitting curves to the normalized Pauli decomposition elements shows consistent trends across several spatially independent regions of the ice cap suggesting that the Pauli elements might be useful for modeling the scattering mechanisms of temperate ice with various surface conditions. / text

Organic matter (OM) in arctic permafrost ground contains about twice as much carbon (C) as is currently present in the atmosphere. Climate change is particularly strong in the Arctic, and could cause a considerable part of the OM in permafrost to thaw out, decompose, and be released as greenhouse gases; further enhancing global warming. The exact size of the northern circumpolar C pool remains unclear, and processes that control decomposition and mineralization rates are even more uncertain. Superimposed on the long-term release of C through microbial decomposition of OM in the gradually deepening active layer, is the rapid release of currently sequestered OM through geomorphological processes. This thesis considers the quantity, quality, and availability of permafrost C, and explores interactions and common controls. To better understand the potential effects of thawing permafrost, it is vital to: i) obtain more accurate size and distribution estimates of permafrost C stocks, and develop methods to accurately and efficiently implement these in models, ii) identify OM characteristics that control decomposition, specifically for permafrost material, and iii) determine and quantify key geomorphological processes that cause large amounts of OM to become available for rapid decomposition. Detailed C quantifications are valuable to increase our fundamental understanding of permafrost soil processes and C sequestration, but including high levels of heterogeneity in models is challenging. Simple upscaling tools based on e.g. elevation parameters (Paper I) can help to bridge the gap between detailed field studies and global C models. Permafrost OM quality is controlled by different factors than those commonly observed in temperate soils (without permafrost). We observed an unexpected (significant) correlation in upper permafrost samples, where material that is generally considered more recalcitrant showed the highest CO2 production rates per g C, indicating high lability (Paper II). In ancient Pleistocene permafrost, labile samples related significantly to OM that was enriched in decomposed microbial remains, whereas less-decomposed plant material was more stable (Paper III). Investigation of multiple incubation datasets revealed that the unusual relationship between %C and CO2 production occurred in contrasting field sites throughout the Arctic, indicating important permafrost-specific controls over OM quality (Paper IV). We discuss several possible explanations for the observed high lability of permafrost OM, such as a pool of labile dissolved organic C in the upper permafrost, or increased lability caused by past decomposition. In order to conclusively identify causal relationships, and to answer the question whether or not the same mechanisms control OM quality in different environments, further investigation of permafrost-specific OM quality is required. Geomorphology plays a key role in C reworking and OM decomposition. Vast amounts of OM can be released abruptly (e.g. in thaw slumps and thermokarst lakes, Paper II), resulting in C turnover that will likely outweigh decomposition through gradual active layer deepening. Climate change could enhance this rapid release of C, and changes in surface hydrology and increased fire activity are expected to become the largest contributors to C loss from permafrost regions. Together with C quantity and quality, availability through gradual and abrupt processes must be parameterized and included in models in order to accurately assess the potential permafrost C climate feedback. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 3: Manuscript. Paper 4: Manuscript.</p>