Review Article: Global Monitoring of Snow Water Equivalent Using High-Frequency Radar Remote Sensing

Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth\u27s surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth\u27s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world\u27s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth\u27s cold regions\u27 ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements

Monitoring permafrost environments with Synthetic Aperture Radar (SAR) sensors

Permafrost occupies approximately 24% of the exposed land area in the Northern Hemisphere. It is an important element of the cryosphere and has strong impacts on hydrology, biological processes, land surface energy budget, and infrastructure. For several decades, surface air temperatures in the high northern latitudes have warmed at approximately twice the global rate. Permafrost temperatures have increased in most regions since the early 1980s, the averaged warming north of 60°N has been 1-2°C. In-situ measurements are essential to understanding physical processes in permafrost terrain, but they have several limitations, ranging from difficulties in drilling to the representativeness of limited single point measurements. Remote sensing is urgently needed to supplement ground-based measurements and extend the point observations to a broader spatial domain. This thesis concentrates on the sub-arctic permafrost environment monitoring with SAR datasets. The study site is selected in a typical discontinuous permafrost region in the eastern Canadian sub-Arctic. Inuit communities in Nunavik and Nunatsiavut in the Canadian eastern sub-arctic are amongst the groups most affected by the impacts of climate change and permafrost degradation. Synthetic Aperture Radar (SAR) datasets have advantages for permafrost monitoring in the Arctic and sub-arctic regions because of its high resolution and independence of cloud cover and solar illumination. To date, permafrost environment monitoring methods and strategies with SAR datasets are still under development. The variability of active layer thickness is a direct indication of permafrost thermal state changes. The Differential SAR Interferometry (D-InSAR) technique is applied in the study site to derive ground deformation, which is introduced by the thawing/freezing depth of active layer and underlying permafrost. The D-InSAR technique has been used for the mapping of ground surface deformation over large areas by interpreting the phase difference between two signals acquired at different times as ground motion information. It shows the ability to detect freeze/thaw-related ground motion over permafrost regions. However, to date, accuracy and value assessments of D-InSAR applications have focused mostly on the continuous permafrost region where the vegetation is less developed and causes fewer complicating factors for the D-InSAR application, less attention is laid on the discontinuous permafrost terrain. In this thesis, the influencing factors and application conditions for D-InSAR in the discontinuous permafrost environment are evaluated by using X- band and L-band data. Then, benefit from by the high-temporal resolution of C-band Sentinel-1 time series, the seasonal displacement is derived from small baseline subsets (SBAS)-InSAR. Landforms are indicative of permafrost presence, with their changes inferring modifications to permafrost conditions. A permafrost landscape mapping method was developed which uses multi-temporal TerraSAR-X backscatter intensity and interferometric coherence information. The land cover map is generated through the combined use of object-based image analysis (OBIA) and classification and regression tree analysis (CART). An overall accuracy of 98% is achieved when classifying rock and water bodies, and an accuracy of 79% is achieved when discriminating between different vegetation types with one year of single-polarized acquisitions. This classification strategy can be transferred to other time-series SAR datasets, e.g., Sentinel-1, and other heterogeneous environments. One predominant change in the landscape tied to the thaw of permafrost is the dynamics of thermokarst lakes. Dynamics of thermokarst lakes are developed through their lateral extent and vertical depth changes. Due to different water depth, ice cover over shallow thermokarst ponds/lakes can freeze completely to the lake bed in winter, resulting in grounded ice; while ice cover over deep thermokarst ponds/lakes cannot, which have liquid water persisting under the ice cover all winter, resulting in floating ice. Winter ice cover regimes are related to water depths and ice thickness. In the lakes having floating ice, the liquid water induces additional heat in the remaining permafrost underneath and surroundings, which contributes to further intensified permafrost thawing. SAR datasets are utilized to detect winter ice cover regimes based on the character that liquid water has a remarkably high dielectric constant, whereas pure ice has a low value. Patterns in the spatial distribution of ice-cover regimes of thermokarst ponds in a typical discontinuous permafrost region are first revealed. Then, the correlations of these ice-cover regimes with the permafrost degradation states and thermokarst pond development in two historical phases (Sheldrake catchment in the year 1957 and 2009, Tasiapik Valley 1994 and 2010) were explored. The results indicate that the ice-cover regimes of thermokarst ponds are affected by soil texture, permafrost degradation stage and permafrost depth. Permafrost degradation is difficult to directly assess from the coverage area of floating-ice ponds and the percentage of all thermokarst ponds consisting of such floating-ice ponds in a single year. Continuous monitoring of ice-cover regimes and surface areas is recommended to elucidate the hydrological trajectory of the thermokarst process. Several operational monitoring methods have been developed in this thesis work. In the meanwhile, the spatial distribution of seasonal ground thaw subsidence, permafrost landscape, thermokarst ponds and their winter ice cover regimes are first revealed in the study area. The outcomes help understand the state and dynamics of permafrost environment.Der Permafrostboden bedeckt etwa 24% der exponierten Landfläche in der nördlichen Hemisphäre. Es ist ein wichtiges Element der Kryosphäre und hat starke Auswirkungen auf die Hydrologie, die biologischen Prozesse, das Energie-Budget der Landoberfläche und die Infrastruktur. Seit mehreren Jahrzehnten erhöhen sich die Oberflächenlufttemperaturen in den nördlichen hohen Breitengraden etwa doppelt so stark wie die globale Rate. Die Temperaturen der Permafrostböden sind in den meisten Regionen seit den frühen 1980er Jahren gestiegen. Die durchschnittliche Erwärmung nördlich von 60° N beträgt 1-2°C. In-situ-Messungen sind essentiell für das Verständnis der physischen Prozesse im Permafrostgelände. Es gibt jedoch mehrere Einschränkungen, die von Schwierigkeiten beim Bohren bis hin zur Repräsentativität begrenzter Einzelpunktmessungen reichen. Fernerkundung ist dringend benötigt, um bodenbasierte Messungen zu ergänzen und punktuelle Beobachtungen auf einen breiteren räumlichen Bereich auszudehnen. Diese Dissertation konzentriert sich auf die Umweltbeobachtung der subarktischen Permafrostböden mit SAR-Datensätzen. Das Untersuchungsgebiet wurde in einer typischen diskontinuierlichen Permafrostzone in der kanadischen östlichen Sub-Arktis ausgewählt. Die Inuit-Gemeinschaften in den Regionen Nunavik und Nunatsiavut in der kanadischen östlichen Sub-Arktis gehören zu den Gruppen, die am stärksten von den Auswirkungen des Klimawandels und Permafrostdegradation betroffen sind. Synthetische Apertur Radar (SAR) Datensätze haben Vorteile für das Permafrostmonitoring in den arktischen und subarktischen Regionen aufgrund der hohen Auflösung und der Unabhängigkeit von Wolkendeckung und Sonnenstrahlung. Bis heute sind die Methoden und Strategien mit SAR-Datensätzen für Umweltbeobachtung der Permafrostböden noch in der Entwicklung. Die Variabilität der Auftautiefe der aktiven Schicht ist eine direkte Indikation der Veränderung des thermischen Zustands der Permafrostböden. Die Differential-SAR-Interferometrie(D-Insar)-Technik wird im Untersuchungsgebiet zur Ableitung der Bodendeformation, die durch Auftau- / und Gefriertiefe der aktiven Schicht und des unterliegenden Permafrostbodens eingeführt wird, eingesetzt. Die D-InSAR-Technik wurde für Kartierung der Landoberflächendeformation über große Flächen verwendet, indem der Phasenunterschied zwischen zwei zu verschiedenen Zeitpunkten als Bodenbewegungsinformation erfassten Signalen interpretiert wurde. Es zeigt die Fähigkeit, tau- und gefrierprozessbedingte Bodenbewegungen über Permafrostregionen zu detektieren. Jedoch fokussiert sich die Genauigkeit und Wertschätzung der D-InSAR-Anwendung bis heute hauptsächlich auf kontinuierliche Permafrostregion, wo die Vegetation wenig entwickelt ist und weniger komplizierte Faktoren für D-InSAR-Anwendung verursacht. Das diskontinuierliche Permafrostgelände wurde nur weniger berücksichtigt. In dieser Dissertation wurden die Einflussfaktoren und Anwendungsbedingungen für D-InSAR im diskontinuierlichen Permafrostgebiet mittels X-Band und L-Band Daten ausgewertet. Dann wurde die saisonale Verschiebung dank der hohen Auflösung der C-Band Sentinel-1 Zeitreihe von „Small Baseline Subsets (SBAS)-InSAR“ abgeleitet. Landformen weisen auf die Präsenz des Permafrosts hin, wobei deren Veränderungen auf die Modifikation der Permafrostbedingungen schließen. Eine Kartierungsmethode der Permafrostlandschaft wurde entwickelt, dabei wurde Multi-temporal TerraSAR-X Rückstreuungsintensität und interferometrische Kohärenzinformationen verwendet. Die Landbedeckungskarte wurde durch kombinierte Anwendung objektbasierter Bildanalyse (OBIA) und Klassifikations- und Regressionsbaum Analyse (CART) generiert. Eine Gesamtgenauigkeit in Höhe von 98% wurde bei Klassifikation der Gesteine und Wasserkörper erreicht. Bei Unterscheidung zwischen verschiedenen Vegetationstypen mit einem Jahr einzelpolarisierte Akquisitionen wurde eine Genauigkeit von 79% erreicht. Diese Klassifikationsstrategie kann auf andere Zeitreihen der SAR-Datensätzen, z.B. Sentinel-1, und auch anderen heterogenen Umwelten übertragen werden. Eine vorherrschende Veränderung in der Landschaft, die mit dem Auftauen des Permafrosts verbunden ist, ist die Dynamik der Thermokarstseen. Die Dynamik der Thermokarstseen ist durch Veränderungen der seitlichen Ausdehnung und der vertikalen Tiefe entwickelt. Aufgrund der unterschiedlichen Wassertiefen kann die Eisdecke über den flachen Thermokarstteichen/-seen im Winter bis auf den Wasserboden vollständig gefroren sein, was zum geerdeten Eis führt, während die Eisdecke über den tiefen Thermokarstteichen/-seen es nicht kann. In den tiefen Thermokarstteichen/-seen bleibt den ganzen Winter flüssiges Wasser unter der Eisdecke bestehen, was zum Treibeis führt. Das Wintereisdeckenregime bezieht sich auf die Wassertiefe und die Eisdicke. In den Seen mit Treibeis leitet das flüssige Wasser zusätzliche Wärme in den restlichen Permafrost darunter oder in der Umgebung, was zur weiteren Verstärkung des Permafrostauftauen beiträgt. Basiert auf den Charakter, dass das flüssige Wasser eine bemerkenswert hohe Dielektrizitätskonstante besitzt, während reines Eis einen niedrigen Wert hat, wurden die SAR Datensätzen zur Erkennung des Wintereisdeckenregimes verwendet. Zunächst wurden Schemen in der räumlichen Verteilung der Eisdeckenregimes der Thermokarstteiche in einer typischen diskontinuierlichen Permafrostregion abgeleitet. Dann wurden die Zusammenhänge dieser Eisdeckenregimes mit dem Degradationszustand des Permafrosts und der Entwicklung der Thermokarstteiche in zwei historischen Phasen (Sheldrake Einzugsgebiet in 1957 und 2009, Tasiapik Tal in 1994 und 2010) erforscht. Die Ergebnisse deuten darauf, dass die Eisdeckenregimes der Thermokarstteiche von der Bodenart, dem Degradationszustand des Permafrosts und der Permafrosttiefe beeinflusst werden. Es ist schwer, die Permafrostdegradation in einem einzelnen Jahr direkt durch den Abdeckungsbereich der Treibeis-Teiche und die Prozentzahl aller aus solchen Treibeis-Teichen bestehenden Thermokarstteiche abzuschätzen. Ein kontinuierliches Monitoring der Eisdeckenregimes und -oberflächen ist empfehlenswert, um den hydrologischen Verlauf des Thermokarstprozesses zu erläutern. In dieser Dissertation wurden mehrere operativen Monitoringsmethoden entwickelt. In der Zwischenzeit wurden die räumliche Verteilung der saisonalen Bodentauabsenkung, die Permafrostlandschaft, die Thermokarstteiche und ihre Wintereisdeckenregimes erstmals in diesem Untersuchungsgebiet aufgedeckt. Die Ergebnisse tragen dazu bei, den Zustand und die Dynamik der Permafrostumwelt zu verstehen

Monitoring permafrost environments with Synthetic Aperture Radar (SAR) sensors

Permafrost occupies approximately 24% of the exposed land area in the Northern Hemisphere. It is an important element of the cryosphere and has strong impacts on hydrology, biological processes, land surface energy budget, and infrastructure. For several decades, surface air temperatures in the high northern latitudes have warmed at approximately twice the global rate. Permafrost temperatures have increased in most regions since the early 1980s, the averaged warming north of 60°N has been 1-2°C. In-situ measurements are essential to understanding physical processes in permafrost terrain, but they have several limitations, ranging from difficulties in drilling to the representativeness of limited single point measurements. Remote sensing is urgently needed to supplement ground-based measurements and extend the point observations to a broader spatial domain. This thesis concentrates on the sub-arctic permafrost environment monitoring with SAR datasets. The study site is selected in a typical discontinuous permafrost region in the eastern Canadian sub-Arctic. Inuit communities in Nunavik and Nunatsiavut in the Canadian eastern sub-arctic are amongst the groups most affected by the impacts of climate change and permafrost degradation. Synthetic Aperture Radar (SAR) datasets have advantages for permafrost monitoring in the Arctic and sub-arctic regions because of its high resolution and independence of cloud cover and solar illumination. To date, permafrost environment monitoring methods and strategies with SAR datasets are still under development. The variability of active layer thickness is a direct indication of permafrost thermal state changes. The Differential SAR Interferometry (D-InSAR) technique is applied in the study site to derive ground deformation, which is introduced by the thawing/freezing depth of active layer and underlying permafrost. The D-InSAR technique has been used for the mapping of ground surface deformation over large areas by interpreting the phase difference between two signals acquired at different times as ground motion information. It shows the ability to detect freeze/thaw-related ground motion over permafrost regions. However, to date, accuracy and value assessments of D-InSAR applications have focused mostly on the continuous permafrost region where the vegetation is less developed and causes fewer complicating factors for the D-InSAR application, less attention is laid on the discontinuous permafrost terrain. In this thesis, the influencing factors and application conditions for D-InSAR in the discontinuous permafrost environment are evaluated by using X- band and L-band data. Then, benefit from by the high-temporal resolution of C-band Sentinel-1 time series, the seasonal displacement is derived from small baseline subsets (SBAS)-InSAR. Landforms are indicative of permafrost presence, with their changes inferring modifications to permafrost conditions. A permafrost landscape mapping method was developed which uses multi-temporal TerraSAR-X backscatter intensity and interferometric coherence information. The land cover map is generated through the combined use of object-based image analysis (OBIA) and classification and regression tree analysis (CART). An overall accuracy of 98% is achieved when classifying rock and water bodies, and an accuracy of 79% is achieved when discriminating between different vegetation types with one year of single-polarized acquisitions. This classification strategy can be transferred to other time-series SAR datasets, e.g., Sentinel-1, and other heterogeneous environments. One predominant change in the landscape tied to the thaw of permafrost is the dynamics of thermokarst lakes. Dynamics of thermokarst lakes are developed through their lateral extent and vertical depth changes. Due to different water depth, ice cover over shallow thermokarst ponds/lakes can freeze completely to the lake bed in winter, resulting in grounded ice; while ice cover over deep thermokarst ponds/lakes cannot, which have liquid water persisting under the ice cover all winter, resulting in floating ice. Winter ice cover regimes are related to water depths and ice thickness. In the lakes having floating ice, the liquid water induces additional heat in the remaining permafrost underneath and surroundings, which contributes to further intensified permafrost thawing. SAR datasets are utilized to detect winter ice cover regimes based on the character that liquid water has a remarkably high dielectric constant, whereas pure ice has a low value. Patterns in the spatial distribution of ice-cover regimes of thermokarst ponds in a typical discontinuous permafrost region are first revealed. Then, the correlations of these ice-cover regimes with the permafrost degradation states and thermokarst pond development in two historical phases (Sheldrake catchment in the year 1957 and 2009, Tasiapik Valley 1994 and 2010) were explored. The results indicate that the ice-cover regimes of thermokarst ponds are affected by soil texture, permafrost degradation stage and permafrost depth. Permafrost degradation is difficult to directly assess from the coverage area of floating-ice ponds and the percentage of all thermokarst ponds consisting of such floating-ice ponds in a single year. Continuous monitoring of ice-cover regimes and surface areas is recommended to elucidate the hydrological trajectory of the thermokarst process. Several operational monitoring methods have been developed in this thesis work. In the meanwhile, the spatial distribution of seasonal ground thaw subsidence, permafrost landscape, thermokarst ponds and their winter ice cover regimes are first revealed in the study area. The outcomes help understand the state and dynamics of permafrost environment.Der Permafrostboden bedeckt etwa 24% der exponierten Landfläche in der nördlichen Hemisphäre. Es ist ein wichtiges Element der Kryosphäre und hat starke Auswirkungen auf die Hydrologie, die biologischen Prozesse, das Energie-Budget der Landoberfläche und die Infrastruktur. Seit mehreren Jahrzehnten erhöhen sich die Oberflächenlufttemperaturen in den nördlichen hohen Breitengraden etwa doppelt so stark wie die globale Rate. Die Temperaturen der Permafrostböden sind in den meisten Regionen seit den frühen 1980er Jahren gestiegen. Die durchschnittliche Erwärmung nördlich von 60° N beträgt 1-2°C. In-situ-Messungen sind essentiell für das Verständnis der physischen Prozesse im Permafrostgelände. Es gibt jedoch mehrere Einschränkungen, die von Schwierigkeiten beim Bohren bis hin zur Repräsentativität begrenzter Einzelpunktmessungen reichen. Fernerkundung ist dringend benötigt, um bodenbasierte Messungen zu ergänzen und punktuelle Beobachtungen auf einen breiteren räumlichen Bereich auszudehnen. Diese Dissertation konzentriert sich auf die Umweltbeobachtung der subarktischen Permafrostböden mit SAR-Datensätzen. Das Untersuchungsgebiet wurde in einer typischen diskontinuierlichen Permafrostzone in der kanadischen östlichen Sub-Arktis ausgewählt. Die Inuit-Gemeinschaften in den Regionen Nunavik und Nunatsiavut in der kanadischen östlichen Sub-Arktis gehören zu den Gruppen, die am stärksten von den Auswirkungen des Klimawandels und Permafrostdegradation betroffen sind. Synthetische Apertur Radar (SAR) Datensätze haben Vorteile für das Permafrostmonitoring in den arktischen und subarktischen Regionen aufgrund der hohen Auflösung und der Unabhängigkeit von Wolkendeckung und Sonnenstrahlung. Bis heute sind die Methoden und Strategien mit SAR-Datensätzen für Umweltbeobachtung der Permafrostböden noch in der Entwicklung. Die Variabilität der Auftautiefe der aktiven Schicht ist eine direkte Indikation der Veränderung des thermischen Zustands der Permafrostböden. Die Differential-SAR-Interferometrie(D-Insar)-Technik wird im Untersuchungsgebiet zur Ableitung der Bodendeformation, die durch Auftau- / und Gefriertiefe der aktiven Schicht und des unterliegenden Permafrostbodens eingeführt wird, eingesetzt. Die D-InSAR-Technik wurde für Kartierung der Landoberflächendeformation über große Flächen verwendet, indem der Phasenunterschied zwischen zwei zu verschiedenen Zeitpunkten als Bodenbewegungsinformation erfassten Signalen interpretiert wurde. Es zeigt die Fähigkeit, tau- und gefrierprozessbedingte Bodenbewegungen über Permafrostregionen zu detektieren. Jedoch fokussiert sich die Genauigkeit und Wertschätzung der D-InSAR-Anwendung bis heute hauptsächlich auf kontinuierliche Permafrostregion, wo die Vegetation wenig entwickelt ist und weniger komplizierte Faktoren für D-InSAR-Anwendung verursacht. Das diskontinuierliche Permafrostgelände wurde nur weniger berücksichtigt. In dieser Dissertation wurden die Einflussfaktoren und Anwendungsbedingungen für D-InSAR im diskontinuierlichen Permafrostgebiet mittels X-Band und L-Band Daten ausgewertet. Dann wurde die saisonale Verschiebung dank der hohen Auflösung der C-Band Sentinel-1 Zeitreihe von „Small Baseline Subsets (SBAS)-InSAR“ abgeleitet. Landformen weisen auf die Präsenz des Permafrosts hin, wobei deren Veränderungen auf die Modifikation der Permafrostbedingungen schließen. Eine Kartierungsmethode der Permafrostlandschaft wurde entwickelt, dabei wurde Multi-temporal TerraSAR-X Rückstreuungsintensität und interferometrische Kohärenzinformationen verwendet. Die Landbedeckungskarte wurde durch kombinierte Anwendung objektbasierter Bildanalyse (OBIA) und Klassifikations- und Regressionsbaum Analyse (CART) generiert. Eine Gesamtgenauigkeit in Höhe von 98% wurde bei Klassifikation der Gesteine und Wasserkörper erreicht. Bei Unterscheidung zwischen verschiedenen Vegetationstypen mit einem Jahr einzelpolarisierte Akquisitionen wurde eine Genauigkeit von 79% erreicht. Diese Klassifikationsstrategie kann auf andere Zeitreihen der SAR-Datensätzen, z.B. Sentinel-1, und auch anderen heterogenen Umwelten übertragen werden. Eine vorherrschende Veränderung in der Landschaft, die mit dem Auftauen des Permafrosts verbunden ist, ist die Dynamik der Thermokarstseen. Die Dynamik der Thermokarstseen ist durch Veränderungen der seitlichen Ausdehnung und der vertikalen Tiefe entwickelt. Aufgrund der unterschiedlichen Wassertiefen kann die Eisdecke über den flachen Thermokarstteichen/-seen im Winter bis auf den Wasserboden vollständig gefroren sein, was zum geerdeten Eis führt, während die Eisdecke über den tiefen Thermokarstteichen/-seen es nicht kann. In den tiefen Thermokarstteichen/-seen bleibt den ganzen Winter flüssiges Wasser unter der Eisdecke bestehen, was zum Treibeis führt. Das Wintereisdeckenregime bezieht sich auf die Wassertiefe und die Eisdicke. In den Seen mit Treibeis leitet das flüssige Wasser zusätzliche Wärme in den restlichen Permafrost darunter oder in der Umgebung, was zur weiteren Verstärkung des Permafrostauftauen beiträgt. Basiert auf den Charakter, dass das flüssige Wasser eine bemerkenswert hohe Dielektrizitätskonstante besitzt, während reines Eis einen niedrigen Wert hat, wurden die SAR Datensätzen zur Erkennung des Wintereisdeckenregimes verwendet. Zunächst wurden Schemen in der räumlichen Verteilung der Eisdeckenregimes der Thermokarstteiche in einer typischen diskontinuierlichen Permafrostregion abgeleitet. Dann wurden die Zusammenhänge dieser Eisdeckenregimes mit dem Degradationszustand des Permafrosts und der Entwicklung der Thermokarstteiche in zwei historischen Phasen (Sheldrake Einzugsgebiet in 1957 und 2009, Tasiapik Tal in 1994 und 2010) erforscht. Die Ergebnisse deuten darauf, dass die Eisdeckenregimes der Thermokarstteiche von der Bodenart, dem Degradationszustand des Permafrosts und der Permafrosttiefe beeinflusst werden. Es ist schwer, die Permafrostdegradation in einem einzelnen Jahr direkt durch den Abdeckungsbereich der Treibeis-Teiche und die Prozentzahl aller aus solchen Treibeis-Teichen bestehenden Thermokarstteiche abzuschätzen. Ein kontinuierliches Monitoring der Eisdeckenregimes und -oberflächen ist empfehlenswert, um den hydrologischen Verlauf des Thermokarstprozesses zu erläutern. In dieser Dissertation wurden mehrere operativen Monitoringsmethoden entwickelt. In der Zwischenzeit wurden die räumliche Verteilung der saisonalen Bodentauabsenkung, die Permafrostlandschaft, die Thermokarstteiche und ihre Wintereisdeckenregimes erstmals in diesem Untersuchungsgebiet aufgedeckt. Die Ergebnisse tragen dazu bei, den Zustand und die Dynamik der Permafrostumwelt zu verstehen

Remote Sensing of Environmental Changes in Cold Regions

This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing

Developing Parameter Constraints for Radar-based SWE Retrievals

Terrestrial snow is an important freshwater reservoir with significant influence on the climate and energy balance. It exhibits natural spatiotemporal variability which has been enhanced by climate change, thus it is important to monitor on a large scale. Active microwave, or radar remote sensing has shown frequency-dependent promise in this regard, however, interpretation remains a challenge. The aim of this thesis was to develop constraints for radar based SWE retrievals which characterize and limit uncertainty with a focus on the underlying physical processes, snowpack stratigraphy, the influence of vegetation, and effects of background scattering. The University of Waterloo Scatterometer (UWScat) was used to make measurements at 9.6 and 17.2 GHz of snow and bare ground in a series of field-based campaigns in Maryhill and Englehart, ON, Grand Mesa, CO (NASA SnowEx campaign, year 1), and Trail Valley Creek, NT. Additional measurements from Tobermory, ON, and Churchill, MB (Canadian Snow and Ice Experiment) were included. The Microwave Emission Model for Layered Snowpacks, Version 3, adapted for backscattering (MEMLS3&a) was used to explore snowpack parameterization and SWE retrieval and the Freeman-Durden three component decomposition (FD3c) was used to leverage the polarimetric response. Physical processes in the snow accumulation environment demonstrated influence on regional snowpack parameterization and constraints in a SWE retrieval context with a single-layer snowpack parameterization for Maryhill, ON and a two-layer snowpack parameterization for Englehart, ON resulting in a retrieval RMSE of 21.9 mm SWE and 24.6 mm SWE, respectively. Use of in situ snow depths improved RMSE to 12.0 mm SWE and 10.9 mm SWE, while accounting for soil scattering effects further improved RMSE by up to 6.3 mm SWE. At sites with vegetation and ice lenses, RMSE improved from 60.4 mm SWE to 21.1 mm SWE when in situ snow depths were used. These results compare favorably with the common accuracy requirement of RMSE ≤ 30 mm and underscore the importance of understanding the driving physical processes in a snow accumulation environment and the utility of their regional manifestation in a SWE retrieval context. A relationship between wind slab thickness and the double-bounce component of the FD3c in a tundra snowpack was introduced for incidence angles ≥ 46° and wind slab thickness ≥ 19 cm. Estimates of wind slab thickness and SWE resulted in an RMSE of 6.0 cm and 5.5 mm, respectively. The increased double-bounce scattering was associated with path length increase within a growing wind slab layer. Signal attenuation in a sub-canopy SWE retrieval was also explored. The volume scattering component of the FD3c yielded similar performance to forest fraction in the retrieval with several distinct advantages including a real-time description of forest condition, accounting for canopy geometry without ancillary information, and providing coincident information on forest canopy in remote locations. Overall, this work demonstrated how physical processes can manifest regional outcomes, it quantified effects of natural inclusions and background scattering on SWE retrievals, it provided a means to constrain wind slab thickness in a tundra environment, and it improved characterization of coniferous forest in a sub-canopy SWE retrieval context. Future work should focus on identifying ice and vegetation conditions prior to SWE retrieval, testing the spatiotemporal validity of the methods developed herein, and finally, improving the integration of snowpack attenuation within retrieval efforts

Evapotranspiration in a subarctic agroecosystem: field measurements, modeling and sustainability perspectives

Thesis (Ph.D.) University of Alaska Fairbanks, 2015Northern latitudes are known to be the most vulnerable regions already witnessing the impacts of climate change. These impacts have not only affected a broad spectrum of ecological conditions but also physical and socio-economic functions and activities across the region. Uncertainties in climate change and its progression exposes agroecosystem development and sustainability to a great risk. Yet, not fully understood, climate feedbacks and influencing factors such as human population growth and consumption imposes economical and financial stress in the sustainability of agroecosystem activities. On the opposite direction, trends in this activity can drive regional modifications to climate to an extent that is still unknown and not yet forecasted. Over time, as the acreages of agricultural lands increase from conversion of natural lands such as boreal forests, unexpected changes in surface energetics and particularly overturning of evapotranspiration rates and changes in soil moisture regime may potentially accentuate regional climate change. These changes therefore are expected to introduce new challenges for Alaskan agriculturists because of increasing vulnerabilities and affecting conditions that shape resilience of agricultural systems and production. This research focused on improving understanding of surface energetics in an agroecosystem of Interior Alaska. A synthesis study was conducted combining the analysis of intensive field experiments including direct measurements of micrometeorological, hydrological, meteorological variables and computational modelling during the summer growing season. The evaluation of evapotranspiration (ET) dynamical regime and surface energy processes showed that ET represented a large portion of surface energy balance with similar aspects to surface fluxing levels in Arctic tundra, and in contrast, with more abundant flux levels than in subarctic boreal forest. Surface heterogeneities due to soil moisture and temperature regime drive differences in energy balance closure as a function of spatial scales despite the mostly flat surfaces and stationary atmospheric surface layer flows in the experimental area. A fully coupled numerical simulation was performed to model fluxes at the land-atmosphere interface and compared to independent observations of surface energy. A final assessment of experimental methodologies and numerical modeling is presented in preparation for integrative data fusion analysis and studies involving new satellite remote sensing capabilities, physical modeling and network field observations

An Investigation into the Effects of Variable Lake Ice Properties on Passive and Active Microwave Measurements Over Tundra Lakes Near Inuvik, N.W.T.

The accurate estimation of snow water equivalent (SWE) in the Canadian sub-arctic is integral to climate variability studies and water availability forecasts for economic considerations (drinking water, hydroelectric power generation). Common passive microwave (PM) snow water equivalent (SWE) algorithms that utilize the differences in brightness temperature (Tb) at 37 GHz – 19 GHz falter in lake-rich tundra environments because of the inclusion of lakes within PM pixels. The overarching goal of this research was to investigate the use of multiple platforms and methodologies to observe and quantify the effects of lake ice and sub-ice water on passive microwave emission for the purpose of improving snow water equivalent (SWE) retrieval algorithms. Using in situ snow and ice measurements as input, the Helsinki University of Technology (HUT) multi-layer snow emission model was modified to include an ice layer below the snow layer. Emission for 6.9, 19, 37 and 89 GHz were simulated at horizontal and vertical polarizations, and were validated by high resolution airborne passive microwave measurements coincident with in situ sampling sites over two lakes near Inuvik, Northwest Territories (NWT). Overall, the general magnitude of brightness temperatures were estimated by the HUT model for 6.9 and 19 GHz H/V, however the variability was not. Simulations produced at 37 GHz exhibited the best agreement relative to observed temperatures. However, emission at 37 GHz does not interact with the radiometrically cold water, indicating that ice properties controlling microwave emission are not fully captured by the HUT model. Alternatively, active microwave synthetic aperture radar (SAR) measurements can be used to identify ice properties that affect passive microwave emission. Dual polarized X-band SAR backscatter was utilized to identify ice types by the segmentation program MAGIC (MAp Guided Ice Classification). Airborne passive microwave transects were grouped by ice type classes and compared to backscatter measurements. In freshwater, where there were few areas of high bubble concentration at the ice/water interface Tbs exhibited positive correlations with cross-polarized backscatter, corresponding to ice types (from low to high emission/backscatter: clear ice, transition zone between clear and grey ice, grey ice and rafted ice). SWE algorithms were applied to emission within each ice type producing negative or near zero values in areas of low 19 GHz Tbs (clear ice, transition zone), but also produced positive values that were closer to the range of in situ measurements in areas of high 19 GHz Tbs (grey and rafted ice). Therefore, cross-polarized X-band SAR measurements can be used as a priori ice type information for spaceborne PM algorithms, providing information on ice types and ice characteristics (floating, frozen to bed), integral to future tundra-specific SWE retrieval algorithms

Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices

Recent advances in remote sensing of seasonal snow

Remote sensing offers local, regional and global observations of seasonal snow, providing key information on snowpack processes. This brief review highlights advancements in instrumentation and analysis techniques that have been developed over the past decade. Areas of advancement include improved algorithms for mapping snow-cover extent, snow albedo, snow grain size, snow water equivalent, melt detection and snow depth, as well as new uses of instruments such as multiangular spectroradiometers, scatterometry and lidar. Limitations and synergies of the instruments and techniques are discussed, and remaining challenges such as multisensor mapping, scaling issues, vegetation correction and data assimilation are identified