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

Electromagnetic Modeling for Radar Remote Sensing of Snow-Covered Terrain

This thesis investigates the radar remote sensing of snow-covered terrain for estimation of snow equivalent water on global scale. The importance and impact of this research stems from the fact that water from snowmelt is the major source of water for inland cities and agriculture during summer. This effort is focused on developing a physics-based model for snow and a fully coherent polarimetric scattering model for snow above ground. Both the physical model and the forward polarimetric scattering model present a significant improvement compared to the existing models for snowpack. Computer-generated snow media are constructed using 3-D spatial exponential correlation functions, along with Lineal-Path functions that serve to preserve the connectivity of the snow particles. A fully-coherent model is presented through the use of the Statistical S-matrix Wave Propagation in Spectral-Domain (SSWaP-SD) technique. The SSWaP-SD depends on the discretization of the medium into thin slabs. Several realizations of a thin snow slab are solved numerically to form the statistics of the scattering matrix representing such a thin snow layer. For each thin slab of the snow-pack, a corresponding polarimetric N-port (representing different directions of scattering) S-matrix is generated. These S-matrices are cascaded using the SSWaP-SD method to calculate the total forward and backward bistatic scattered fields in a fully coherent way. The SSWaP-SD, in conjunction with a Method of Moments (MoM) code based on the Discrete-Dipole Approximation (DDA), is chosen to leverage both the time-efficient computations of the DDA and the full-coherency of the SSWaP-SD method, simultaneously. In addition to the MoM-DDA, a Finite Element Method (FEM) based on commercial software is used for cross-comparison and validation. The simulation results of the backscattering from an arbitrary thick snow layer are presented and validated with measurements. The underlying rough ground surface response is then estimated through both an analytical technique based on the Physical Optics (PO) method and a numerical solver based on MoM using a commercial full-wave solver. Finally, the complete response is then calculated by cascading the S-matrices representing the snow and the rough surface responses. The simulation results of the backscattering are presented using a Monte-Carlo process, which show very good agreement with measurements.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/167972/1/mzaky_1.pd

Remote Sensing Observations of Tundra Snow with Ku- and X-band Radar

Seasonal patterns of snow accumulation in the Northern Hemisphere are changing in response to variations in Arctic climate. These changes have the potential to influence global climate, regional hydrology, and sensitive ecosystems as they become more pronounced. To refine our understanding of the role of snow in the Earth system, improved methods to characterize global changes in snow extent and mass are needed. Current space-borne observations and ground-based measurement networks lack the spatial resolution to characterize changes in volumetric snow properties at the scale of ground observed variation. Recently, radar has emerged as a potential complement to existing observation methods with demonstrated sensitivity to snow volume at high spatial resolutions (< 200 m). In 2009, this potential was recognized by the proposed European Space Agency Earth Explorer mission, the Cold Regions High Resolution Hydrology Observatory (CoReH2O); a satellite based dual frequency (17.2 and 9.6 GHz) radar for observation of cryospheric variables including snow water equivalent (SWE). Despite increasing international attention, snow-radar interactions specific to many snow cover types remain unevaluated at 17.2 or 9.6 GHz, including those common to the Canadian tundra. This thesis aimed to use field-based experimentation to close gaps in knowledge regarding snow-microwave interaction and to improve our understanding of how these interactions could be exploited to retrieve snow properties in tundra environments. Between September 2009 and March 2011, a pair of multi-objective field campaigns were conducted in Churchill, Manitoba, Canada to collect snow, ice, and radar measurements in a number of unique sub-arctic environments. Three distinct experiments were undertaken to characterize and evaluate snow-radar response using novel seasonal, spatial, and destructive sampling methods in previously untested terrestrial tundra environments. Common to each experiment was the deployment of a sled-mounted dual-frequency (17.2 and 9.6 GHz) scatterometer system known as UW-Scat. This adaptable ground-based radar system was used to collect backscatter measurements across a range of representative tundra snow conditions at remote terrestrial sites. The assembled set of measurements provide an extensive database from which to evaluate the influence of seasonal processes of snow accumulation and metamorphosis on radar response. Several advancements to our understanding of snow-radar interaction were made in this thesis. First, proof-of-concept experiments were used to establish seasonal and spatial observation protocols for ground-based evaluation. These initial experiments identified the presence of frequency dependent sensitivity to evolving snow properties in terrestrial environments. Expanding upon the preliminary experiments, a seasonal observation protocol was used to demonstrate for the first time Ku-band and X-band sensitivity to evolving snow properties at a coastal tundra observation site. Over a 5 month period, 13 discrete scatterometer observations were collected at an undisturbed snow target where Ku-band measurements were shown to hold strong sensitivity to increasing snow depth and water equivalent. Analysis of longer wavelength X-band measurements was complicated by soil response not easily separable from the target snow signal. Definitive evidence of snow volume scattering was shown by removing the snowpack from the field of view which resulted in a significant reduction in backscatter at both frequencies. An additional set of distributed snow covered tundra targets were evaluated to increase knowledge of spatiotemporal Ku-band interactions. In this experiment strong sensitivities to increasing depth and SWE were again demonstrated. To further evaluate the influence of tundra snow variability, detailed characterization of snow stratigraphy was completed within the sensor field of view and compared against collocated backscatter response. These experiments demonstrated Ku-band sensitivity to changes in tundra snow properties observed over short distances. A contrasting homogeneous snowpack showed a reduction in variation of the radar signal in comparison to a highly variable open tundra site. Overall, the results of this thesis support the single frequency Ku-band (17.2 GHz) retrieval of shallow tundra snow properties and encourage further study of X-band interactions to aid in decomposition of the desired snow volume signal.4 month

Analyse de la modélisation de l'émission multi-fréquences micro-onde des sols et de la neige, incluant les croutes de glace à l'aide du modèle Microwave Emission Model of Layered Snowpacks (MEMLS).

Résumé : L'étude du couvert nival est essentielle afin de mieux comprendre les processus climatiques et hydrologiques. De plus, avec les changements climatiques observés dans l'hémisphère nord, des événements de dégel-regel ou de pluie hivernale sont de plus en plus courants et produisent des croutes de glace dans le couvert nival affectant les moeurs des communautés arctiques en plus de menacer la survie de la faune arctique. La télédétection micro-ondes passives (MOP) démontre un grand potentiel de caractérisation du couvert nival. Toutefois, a fin de bien comprendre les mesures satellitaires, une modélisation adéquate du signal est nécessaire. L'objectif principal de cette thèse est d'analyser le transfert radiatif (TR) MOP des sols, de la neige et de la glace a fin de mieux caractériser les propriétés géophysiques du couvert nival par télédétection. De plus, un indice de détection des croutes de glace par télédétection MOP a été développé. Pour ce faire, le modèle Microwave Emission Model of Layered Snowpacks (MEMLS) a été étudié et calibré afin de minimiser les erreurs des températures de brillance simulées en présences de croutes de glace. La première amélioration faite à la modélisation du TR MOP de la neige a été la caractérisation de la taille des grains de neige. Deux nouveaux instruments, utilisant la réflectance dans le proche infrarouge, ont été développés afin de mesurer la surface spécifique de la neige (SSA). Il a été démontré que la SSA est un paramètre plus précis et plus objectif pour caractériser la taille des grains de neige. Les deux instruments ont démontré une incertitude de 10% sur la mesure de la SSA. De plus, la SSA a été calibré pour la modélisation MOP a n de minimiser l'erreur sur la modélisation de la température de brillance. Il a été démontré qu'un facteur multiplicatif [phi] = 1.3 appliqué au paramètre de taille des grains de neige dans MEMLS, paramètre dérivé de la SSA, est nécessaire afin de minimiser l'erreur des simulations. La deuxième amélioration apportée à la modélisation du TR MOP a été l'estimation de l'émission du sol. Des mesures radiométriques MOP in-situ ainsi que des profils de températures de sols organiques arctiques gelés ont été acquis et caractérisés a fin de simuler l'émission MOP de ces sols. Des constantes diélectriques effectives à 10.7, 19 et 37 GHz ainsi qu'une rugosité de surface effective des sols ont été déterminés pour simuler l'émission des sols. Une erreur quadratique moyenne (RMSE) de 4.65 K entre les simulations et les mesures MOP a été obtenue. Suite à la calibration du TR MOP du sol et de la neige, un module de TR de la glace a été implémenté dans MEMLS. Avec ce nouveau module, il a été possible de démontré que l'approximation de Born améliorée, déjà implémenté dans MEMLS, pouvait être utilisé pour simuler des croutes de glace pure à condition que la couche de glace soit caractérisée par une densité de 917 kg m[indice supérieur _3] et une taille des grains de neige de 0 mm. Il a aussi été démontré que, pour des sites caractérisés par des croutes de glace, les températures de brillances simulées des couverts de neige avec des croutes de glace ayant les propriétés mesurées in-situ (RMSE=11.3 K), avaient une erreur similaire aux températures de brillances simulées des couverts de neige pour des sites n'ayant pas de croutes de glace (RMSE=11.5 K). Avec le modèle MEMLS validé pour la simulation du TR MOP du sol, de la neige et de la glace, un indice de détection des croutes de glace par télédétection MOP a été développé. Il a été démontré que le ratio de polarisation (PR) était très affecté par la présence de croutes de glace dans le couvert de neige. Avec des simulations des PR à 10.7, 19 et 37 GHz sur des sites mesurés à Churchill (Manitoba, Canada), il a été possible de déterminer des seuils entre la moyenne hivernale des PR et les valeurs des PR mesurés indiquant la présence de croutes de glace. Ces seuils ont été appliqués sur une série temporelle de PR de 33 hivers d'un pixel du Nunavik (Québec, Canada) où les conditions de sols étaient similaires à ceux observés à Churchill. Plusieurs croutes de glace ont été détectées depuis 1995 et les mêmes événements entre 2002 et 2009 que (Roy, 2014) ont été détectés. Avec une validation in-situ, il serait possible de confirmer ces événements de croutes de glace mais (Roy, 2014) a démontré que ces événements ne pouvaient être expliqués que par la présence de croutes de glace dans le couvert de neige. Ces mêmes seuils sur les PR ont été appliqués sur un pixel de l'Île Banks (Territoires du Nord-Ouest, Canada). L'événement répertorié par (Grenfell et Putkonen, 2008) a été détecté. Plusieurs autres événements de croutes de glace ont été détectés dans les années 1990 et 2000 avec ces seuils. Tous ces événements ont suivi une période où les températures de l'air étaient près ou supérieures au point de congélation et sont rapidement retombées sous le point de congélation. Les températures de l'air peuvent être utilisées pour confirmer la possibilité de présence de croutes de glace mais seul la validation in-situ peut définitivement confirmer la présence de ces croutes.Abstract : Snow cover studies are essential to better understand climatic and hydrologic processes. With recent climate change observed in the northern hemisphere, more frequent rain-on-snow and meltrefreeze events have been reported, which affect the habits of the northern comunities and the survival of arctique wildlife. Passive microwave remote sensing has proven to be a great tool to characterize the state of snow cover. Nonetheless, proper modeling of the microwave signal is needed in order to understand how the parameters of the snowpack affect the measured signal. The main objective of this study is to analyze the soil, snow and ice radiative transfer in order to better characterize snow cover properties and develop an ice lens detection index with satellite passive microwave brightness temperatures. To do so, the passive microwave radiative transfer modeling of the Microwave Emission Model of Layered Snowpacks (MEMLS) was improved in order to minimize the errors on the brightness temperature simulations in the presence of ice lenses. The first improvement to passive microwave radiative transfer modeling of snow made was the snow grain size parameterization. Two new instruments, based on short wave infrared reflectance to measure the snow specific surface area (SSA) were developed. This parameter was shown to be a more accurate and objective to characterize snow grain size. The instruments showed an uncertainty of 10% to measure the SSA of snow. Also, the SSA of snow was calibrated for passive microwave modeling in order to reduce the errors on the simulated brightness temperatures. It was showed that a correction factor of φ = 1.3 needed to be applied to the grain size parameter of MEMLS, obtain through the SSA measurements, to minimize the simulation error. The second improvement to passive microwave radiative transfer modeling was the estimation of passive microwave soil emission. In-situ microwave measurements and physical temperature profiles of frozen organic arctic soils were acquired and characterized to improve the modeling of the soil emission. Effective permittivities at 10.7, 19 and 37 GHz and effective surface roughness were determined for this type of soil and the soil brightness temperature simulations were obtain with a minimal root mean square error (RMSE) of 4.65K. With the snow grain size and soil contributions to the emitted brightness temperature optimized, it was then possible to implement a passive microwave radiative transfer module of ice into MEMLS. With this module, it was possible to demonstrate that the improved Born approximation already implemented in MEMLS was equivalent to simulating a pure ice lens when the density of the layer was set to 917 kg m−3 and the grain size to 0 mm. This study also showed that by simulating ice lenses within the snow with there measured properties, the RMSE of the simulations (RMSE= 11.3 K) was similar to the RMSE for simulations of snowpacks where no ice lenses were measured (only snow, RMSE= 11.5 K). With the validated MEMLS model for snowpacks with ice lenses, an ice index was created. It is shown here that the polarization ratio (PR) was strongly affected by the presence of ice lenses within the snowpack. With simulations of the PR at 10.7, 19 and 37 GHz from measured snowpack properties in Chucrhill (Manitoba, Canada), thresholds between the measured PR and the mean winter PR were determined to detect the presence of ice within the snowpack. These thresholds were applied to a timeseries of nearly 34 years for a pixel in Nunavik (Quebec, Canada) where the soil surface is similar to that of the Churchill site. Many ice lenses are detected since 1995 with these thresholds and the same events as Roy (2014) were detected. With in-situ validation, it would be possible to confirm the precision of these thresholds but Roy (2014) showed that these events can not be explained by anything else than the presence of an ice layer within the snowpack. The same thresholds were applied to a pixel on Banks island (North-West Territories, Canada). The 2003 event that was reported by Grenfell et Putkonen (2008) was detected by the thresholds. Other events in the years 1990 and 2000’s were detected with these thresholds. These events all follow periods where the air temperature were warm and were followed by a quick drop in air temperature which could be used to validate the presence of ice layer within the snowpack. Nonetheless, without in-situ validation, these events can not be confirmed

Télédétection micro-onde de surfaces enneigées en milieu arctique : étude des processus de surface de la calotte glaciaire Barnes, Nunavut, Canada

Résumé : La région de l'archipel canadien, située en Arctique, connaît actuellement d'importants changements climatiques, se traduisant notamment par une augmentation des températures, une réduction de l'étendue de la banquise marine et du couvert nival terrestre ou encore une perte de masse significative des calottes glaciaires disséminées sur les îles de l'archipel. Parmi ces calottes glaciaires, la calotte Barnes, située en Terre de Baffin, ne fait pas exception comme le montrent les observations satellitaires qui témoignent d'une importante perte de masse ainsi que d'une régression de ses marges, sur les dernières décennies. Bien que les calottes glaciaires de l'archipel canadien ne représentent que quelques dizaines de centimètres d'élévation potentielle du niveau des mers, leur perte de masse est une composante non négligeable de l'augmentation actuelle du niveau des mers. Les projections climatiques laissent à penser que cette contribution pourrait rester significative dans les décennies à venir. Cependant, afin d'estimer les évolutions futures de ces calottes glaciaires et leur impact sur le climat ou le niveau des mers, il est nécessaire de caractériser les processus physiques tels que les modifications du bilan de masse de surface. Cette connaissance est actuellement très limitée du fait notamment du sous-échantillonnage des régions arctiques en terme de stations météorologiques permanentes. Une autre particularité de certaines calottes de l'archipel canadien, et de la calotte Barnes en particulier, est de présenter un processus d'accumulation de type glace surimposée, ce phénomène étant à prendre en compte dans l'étude des processus de surface. Pour pallier au manque de données, l'approche retenue a été d'utiliser des données de télédétection, qui offrent l'avantage d'une couverture spatiale globale ainsi qu'une bonne répétitivité temporelle. En particulier les données acquises dans le domaine des micro-ondes passives sont d'un grand intérêt pour l'étude de surfaces enneigées. En complément de ces données, la modélisation du manteau neigeux, tant d'un point de vue des processus physiques que de l'émission électromagnétique permet d'avoir accès à une compréhension fine des processus de surface tels que l'accumulation de la neige, la fonte, les transferts d'énergie et de matière à la surface, etc. Ces différents termes sont regroupés sous la notion de bilan de masse de surface. L'ensemble du travail présenté dans ce manuscrit a donc consisté à développer des outils permettant d'améliorer la connaissance des processus de surface des calottes glaciaires du type de celles que l'on rencontre dans l'archipel canadien, l'ensemble du développement méthodologique ayant été réalisé sur la calotte Barnes à l'aide du schéma de surface SURFEX-CROCUS pour la modélisation physique et du modèle DMRT-ML pour la partie électromagnétique. Les résultats ont tout d'abord permis de mettre en évidence une augmentation significative de la durée de fonte de surface sur la calotte Barnes (augmentation de plus de 30% sur la période 1979-2010), mais aussi sur la calotte Penny, elle aussi située en Terre de Baffin et qui présente la même tendance (augmentation de l'ordre de 50% sur la même période). Ensuite, l'application d'une chaîne de modélisation physique contrainte par diverses données de télédétection a permis de modéliser de manière réaliste le bilan de masse de surface de la dernière décennie, qui est de +6,8 cm/an en moyenne sur la zone sommitale de la calotte, qui est une zone d'accumulation. Enfin, des tests de sensibilité climatique sur ce bilan de masse ont permis de mettre en évidence un seuil à partir duquel cette calotte voit disparaître sa zone d'accumulation. Les modélisations effectuées suggèrent que ce seuil a de fortes chances d'être atteint très prochainement, pour une augmentation de température moyenne inférieure à 1°C, ce qui aurait pour conséquence une accélération de la perte de masse de la calotte. // Abstract : Significant climate change is curently monitored in the Arctic, and especially in the region of the canadian arctic archipellago. This climate warming leads to recession of seaice extent and seasonnal snow cover, and also to large mass loss of the archipellago’s ice caps. One of the most southern ice cap, the Barnes Ice Cap, located on the Baffin Island, is no exception to significant mass loss and margins recession as satellite observations exhibited over the last decades. Despite the relative low sea level potential of the small ice caps located in the canadian arctic achipellago in regards to major ice sheets, Antarctica and Greenland, their contribution to the current sea level rise is significant. Climate projections show that this contribution could accelerate significant over the next decades. However, to estimate the future evolution of these ice caps and their impact on climate or sea level rise, a better characterisation of the surface processes such as the evolution of the surface mass balance is needed. This knowledge is currently very limited, mainly due to the sparse covering of automatic weather stations or in-situ measurements over the Arctic. Furthermore, several ice caps, among with the Barnes Ice Cap, present a superimposed ice accumulation area which particularities have to be taken into account in the surface processes studies. Given the lack of in-situ data, the approach choosen in this work is to use remote sensing data, that have the advantage to offer a good spatial and temporal coverage. In particular, passive microwave data are very suitable for snowy surfaces studies. To complement these data, physical and electromagnetic snowpack modeling provide a fine characterisation of surface processes such as snow accumulation. The whole work presented in this manuscript thus consisted in developping specific tools to improve the understanding of surface processes of small arctic ice caps. This methodological development was performed and applied on the Barnes Ice Cap using the surface scheme SURFEX-CROCUS and the electromagnetic model DMRT-ML. First results highlight a significant increase in surface melt duration over the past 3 decades on the Barnes Ice Cap (increase of more than 30% over 1979-2010 period). A similar trend is also monitored over the Penny Ice Cap, located in the south part of the Baffin Island (increase of more than 50% over the same period). Then, the surface mass balance over the last decade was modeled by using a physical based modeling chain constrained by remote sensing data. The results give a mean net accumulation of +6,8 cm y−1 on the summit area of the ice cap. Finaly, sensitivity tests, performed to investigate the climatic sensitivity of the surface mass balance, highlight a threshold effect that may lead to a complete disapearence of the accumulation area of the Barnes Ice Cap. With a temperature increase less than 1°C, modeling results suggest it is likely that the threshold will be reached rapidly leading to an increase in mass loss from the ice cap