The impact of early summer snow properties on Antarctic landfast sea ice X band backscatter

Up to now, snow cover on Antarctic sea ice and its impact on radar backscatter, particularly after the onset of freeze/thaw processes, are not well understood. Here we present a combined analysis of in situ observations of snow properties from the landfast sea ice in Atka Bay, Antarctica, and high-resolution TerraSAR-X backscatter data, for the transition from austral spring (November 2012) to summer (January 2013). The physical changes in the seasonal snow cover during that time are reflected in the evolution of TerraSAR-X backscatter. We are able to explain 76–93% of the spatio-temporal variability of the TerraSAR-X backscatter signal with up to four snowpack parameters with a root-mean-squared error of 0.87–1.62 dB, using a simple multiple linear model. Over the complete study, and especially after the onset of early-melt processes and freeze/thaw cycles, the majority of variability in the backscatter is influenced by changes in snow/ice interface temperature, snow depth and top-layer grain size. This suggests it may be possible to retrieve snow physical properties over Antarctic sea ice from X-band SAR backscatter

Snow property controls on modelled Ku-band altimeter estimates of first-year sea ice thickness: Case studies from the Canadian and Norwegian Arctic

Uncertainty in snow properties impacts the accuracy of Arctic sea ice thickness estimates from radar altimetry. On firstyear sea ice (FYI), spatiotemporal variations in snow properties can cause the Ku-band main radar scattering horizon to appear above the snow/sea ice interface. This can increase the estimated sea ice freeboard by several centimeters, leading to FYI thickness overestimations. This study examines the expected changes in Kuband main scattering horizon and its impact on FYI thickness estimates, with variations in snow temperature, salinity and density derived from 10 naturally occurring Arctic FYI Cases encompassing saline/non-saline, warm/cold, simple/complexly layered snow (4 cm to 45 cm) overlying FYI (48 cm to 170 cm). Using a semi-empirical modeling approach, snow properties from these Cases are used to derive layer-wise brine volume and dielectric constant estimates, to simulate the Ku-band main scattering horizon and delays in radar propagation speed. Differences between modeled and observed FYI thickness are calculated to assess sources of error. Under both cold and warm conditions, saline snow covers are shown to shift the main scattering horizon above from the snow/sea ice interface, causing thickness retrieval errors. Overestimates in FYI thicknesses of up to 65% are found for warm, saline snow overlaying thin sea ice. Our simulations exhibited a distinct shift in the main scattering horizon when the snow layer densities became greater than 440 kg/m3 , especially under warmer snow conditions. Our simulations suggest a mean Ku-band propagation delay for snow of 39%, which is higher than 25%, suggested in previous studies

Landfast sea ice formation and deformation near Barrow, Alaska: variability and implications for ice stability

Thesis (M.S.) University of Alaska Fairbanks, 2013Climate change in the Arctic is having large and far-reaching effects. Sea ice is declining in annual extent and thinning with a warming of the atmosphere and the ocean. As a result, sea ice dynamic behaviour and processes are undergoing major changes, interacting with socio-economic changes underway in the Arctic. Near Barrow, Alaska, landfast sea ice is an integral part of native lñupiaq culture and impacts the natural resource extraction and maritime industries. Events known as breakouts of the landfast ice, in which stable landfast ice becomes mobile and detaches from the coast, have been occurring more frequently in recent years in northern Alaska. The current study investigates processes contributing to breakout events near Barrow, and environmental conditions related to the detachment of landfast sea ice from the coast. In this study, synoptic scale sea level pressure patterns are classified in an attempt to identify atmospheric preconditioning and drivers of breakout events. An unsupervised classification approach, so called Self-Organizing Maps, is employed to sort daily sea level pressure distributions across the study area into commonly observed patterns. The results did not point to any particular distributions which favored the occurrence of breakouts. Because of the comparatively small number of breakout events tracked at Barrow to date (nine events between 2006 and 2010), continued data collection may still yield data that support a relationship between breakout events and large scale sea level pressure distributions. Two case studies for breakout events in the 2008/09 and 2009/10 ice seasons help identify contributing and controlling factors for shorefast ice fragmentation and detachment. Observational data, primarily from components of the Barrow Sea Ice Observatory, are used to quantify stresses acting upon the landfast ice. The stability of the landfast ice cover is estimated through the calculation of the extent of grounded pressure ridges, which are stabilizing features of landfast ice. Using idealized ridge geometries and convergence derived from velocity fields obtained by coastal radar, effective grounding depths can be calculated. Processes acting to destabilize or precondition the ice cover are also observed. For a medium-severity breakout that occurred on March 24, 2010, the calculated atmospheric and oceanic stresses on the landfast ice overcame the estimated grounding strength of ridge keels, although interaction with rapidly moving pack ice cannot be ruled out as the primary breakout cause. For another medium-severity breakout that took place on February 27, 2009, the landfast ice was preconditioned by reducing the draft of grounded ridge keels, with subsequent detachment from the shore during the next period of oceanic and atmospheric conditions favoring a breakout. For both of these breakouts, in addition to their potential role in destabilizing the landfast ice by overcoming the ridge grounding strength, current and/or wind forcing on the landfast ice were found to be important factors in moving the stationary ice away from shore.Chapter 1. Introduction to Barrow, Alaska and local sea ice conditions -- 1.1. Introduction -- 1.2. Barrow, Alaska and local sea ice conditions -- 1.3. The Barrow sea ice observatory -- 1.4. Thesis overview -- Chapter 2. Using self-organizing maps to identify regional weather patterns contributing to landfast sea ice breakouts near Barrow, Alaska -- 2.1. Introduction -- 2.2. Purpose -- 2.3. Background on self-organizing maps -- 2.4. Methods and data -- 2.5. Results -- 2.6. Discussion -- 2.7. Conclusions -- Chapter 3. Two case studies of landfast sea ice breakouts near Barrow, Alaska -- 3.1. Introduction -- 3.2. Background -- 3.2.1 Drift and dynamics of sea ice -- 3.2.2. Breakout events: ridge failure -- 3.2.3. Breakout events: failure in tension -- 3.2.4. Changes in sea level -- 3.3. Data for breakout case studies -- 3.3.1. Sea ice mass balance site -- 3.3.2. Marine radar and webcam -- 3.3.3. Satellite products -- 3.3.4. Offshore moorings -- 3.3.5. Local ice observations -- 3.4. Methods -- 3.4.1. Detection of breakout events -- 3.4.2. Tracking sea ice through radar imagery -- 3.4.3. Estimation of grounded ridge extent -- 3.5. Breakout events -- 3.5.1. February 27, 2009 breakout event: pre-breakout ice conditions -- 3.5.2. February 27, 2009 breakout event: conditions during the breakout event -- 3.5.3. February 27, 2009 breakout event: discussion -- 3.5.4. March 24, 2010 breakout event: pre-breakout ice conditions -- 3.5.5. March 24, 2010 breakout event: conditions during the breakout event -- 3.5.6. March 24, 2010 breakout event: discussion -- 3.6. Discussion of errors -- 3.7. Conclusions -- Chapter 4. Landfast sea ice breakout events: general conclusions -- List of symbols -- References

The SIMMS Program: A Study of Change and Variability within the Marine Cryosphere

This paper describes the scientific context of an experimental program for an eight year study of change and variability within the marine cryosphere in the Canadian Arctic and summarizes the field program since its inception in 1990. The focus is on understanding the process linkages between the atmosphere, cryosphere and ocean at the sea ice interface and in establishing a method by which these processes can be modeled numerically. Remote sensing plays a significant role as a major source of temporally and spatially consistent data in this relatively inaccessible region. In this program, we combine in situ measurement of geophysical characteristics of the sea ice interface, electromagnetic radiation interactions with the interface, and numerical modeling of marine cryosphere processes operating across this interface. Our primary objective is to observe and simulate the mechanisms that may contribute to change and variability. We conclude by proposing a conceptual spatial signature of an icescape as the basis for integration of these processes and illustrate how remote sensing data can be used to identify these functional signatures.Key words: Canadian Arctic, marine cryosphere, remote sensing, atmosphere-cryosphere interactions, snow and sea iceCet article décrit le contexte scientifique d'un programme expérimental consistant en une étude portant sur une période de huit ans des changements et de la variabilité au sein de la cryosphère marine dans l'Arctique canadien, et il résume le programme de terrain depuis sa création en 1990. On se concentre sur la compréhension des liens entre les processus à l'oeuvre, à l'interface de la glace de mer, qui impliquent l'atmosphère, la cryosphère et l'océan, ainsi que sur l'élaboration d'une méthode permettant de faire une modélisation numérique de ces processus. La télédétection joue un rôle important comme source principale de données cohérentes sur les plans temporel et spatial provenant de cette région relativement inaccessible. Dans ce programme on combine les mesures in situ des caractéristiques géophysiques de l'interface de la glace de mer, les interactions du rayonnement électromagnétique avec l'interface et la modélisation numérique des processus de la cryosphère agissant à cette interface. Notre objectif premier est d'observer et de simuler les mécanismes qui peuvent contribuer au changement et à la variabilité. On conclut en proposant sur le plan conceptuel une signature spatiale d'un panorama glaciaire comme base d'intégration de ces processus, et on illustre la façon dont les données obtenues par la télédétection peuvent servir à identifier ces signatures fonctionnelles.Mots clés: Arctique canadien, cryosphère marine, télédétection, interactions atmosphère-cryosphère, neige et glace de me

Geostatistical and statistical classification of sea-ice properties and provinces from SAR data

Recent drastic reductions in the Arctic sea-ice cover have raised an interest in understanding the role of sea ice in the global system as well as pointed out a need to understand the physical processes that lead to such changes. Satellite remote-sensing data provide important information about remote ice areas, and Synthetic Aperture Radar (SAR) data have the advantages of penetration of the omnipresent cloud cover and of high spatial resolution. A challenge addressed in this paper is how to extract information on sea-ice types and sea-ice processes from SAR data. We introduce, validate and apply geostatistical and statistical approaches to automated classification of sea ice from SAR data, to be used as individual tools for mapping sea-ice properties and provinces or in combination. A key concept of the geostatistical classification method is the analysis of spatial surface structures and their anisotropies, more generally, of spatial surface roughness, at variable, intermediate-sized scales. The geostatistical approach utilizes vario parameters extracted from directional vario functions, the parameters can be mapped or combined into feature vectors for classification. The method is flexible with respect to window sizes and parameter types and detects anisotropies. In two applications to RADARSAT and ERS-2 SAR data from the area near Point Barrow, Alaska, it is demonstrated that vario-parameter maps may be utilized to distinguish regions of different sea-ice characteristics in the Beaufort Sea, the Chukchi Sea and in Elson Lagoon. In a third and a fourth case study the analysis is taken further by utilizing multi-parameter feature vectors as inputs for unsupervised and supervised statistical classification. Field measurements and high-resolution aerial observations serve as basis for validation of the geostatistical-statistical classification methods. A combination of supervised classification and vario-parameter mapping yields best results, correctly identifying several sea-ice provinces in the shore-fast ice and the pack ice. Notably, sea ice does not have to be static to be classifiable with respect to spatial structures. In consequence, the geostatistical-statistical classification may be applied to detect changes in ice dynamics, kinematics or environmental changes, such as increased melt ponding, increased snowfall or changes in the equilibrium line

A 10-year record of Arctic summer sea ice freeboard from CryoSat-2

Satellite observations of pan-Arctic sea ice thickness have so far been constrained to winter months. For radar altimeters, conventional methods cannot differentiate leads from meltwater ponds that accumulate at the ice surface in summer months, which is a critical step in the ice thickness calculation. Here, we use over 350 optical and synthetic aperture radar (SAR) images from the summer months to train a 1D convolution neural network for separating CryoSat-2 radar altimeter returns from sea ice floes and leads with an accuracy >80%. This enables us to generate the first pan-Arctic measurements of sea ice radar freeboard for May–September between 2011 and 2020. Results indicate that the freeboard distributions in May and September compare closely to those from a conventional ‘winter’ processor in April and October, respectively. The freeboards capture expected patterns of sea ice melt over the Arctic summer, matching well to ice draft observations from the Beaufort Gyre Exploration Program (BGEP) moorings. However, compared to airborne laser scanner freeboards from Operation IceBridge and airborne EM ice thickness surveys from the Alfred Wegener Institute (AWI) IceBird program, CryoSat-2 freeboards are underestimated by 0.02–0.2 m, and ice thickness is underestimated by 0.28–1.0 m, with the largest differences being over thicker multi-year sea ice. To create the first pan-Arctic summer sea ice thickness dataset we must address primary sources of uncertainty in the conversion from radar freeboard to ice thickness

Toward quantifying the increasing role oceanic heat in sea ice loss in the new Arctic

Author Posting. © American Meteorological Society, 2015. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 96 (2015): 2079–2105, doi:10.1175/BAMS-D-13-00177.1.The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions.2016-06-0

Towards quantifying the increasing role of oceanic heat in sea ice loss in the new Arctic

The loss of Arctic sea ice has emerged as a leading signal of global warming. This, together with acknowledged impacts on other components of the Earth system, has led to the term “the new Arctic.” Global coupled climate models predict that ice loss will continue through the twenty-first century, with implications for governance, economics, security, and global weather. A wide range in model projections reflects the complex, highly coupled interactions between the polar atmosphere, ocean, and cryosphere, including teleconnections to lower latitudes. This paper summarizes our present understanding of how heat reaches the ice base from the original sources—inflows of Atlantic and Pacific Water, river discharge, and summer sensible heat and shortwave radiative fluxes at the ocean/ice surface—and speculates on how such processes may change in the new Arctic. The complexity of the coupled Arctic system, and the logistic and technological challenges of working in the Arctic Ocean, require a coordinated interdisciplinary and international program that will not only improve understanding of this critical component of global climate but will also provide opportunities to develop human resources with the skills required to tackle related problems in complex climate systems. We propose a research strategy with components that include 1) improved mapping of the upper- and middepth Arctic Ocean, 2) enhanced quantification of important process, 3) expanded long-term monitoring at key heat-flux locations, and 4) development of numerical capabilities that focus on parameterization of heat-flux mechanisms and their interactions.publishedVersio

Sea-ice surface properties and their impact on the under-ice light field from remote sensing data and in-situ measurements

The surface properties of sea ice dominate many key processes and drive important feedback mechanisms in the polar oceans of both hemispheres. Examining Arctic and Antarctic sea ice, the distinctly different dominant sea-ice and snow properties in spring and summer are apparent. While Arctic sea ice features a seasonal snow cover with widespread surface ponding in summer, a year-round snow cover and strong surface flooding at the snow/ice interface is observed on Antarctic sea ice. However, substantial knowledge gaps exist about the spatial distribution and temporal evolution of these properties, and their impacts on exchange processes across the atmosphere/ocean interface. This thesis aims to overcome these limitations by quantifying the influence of surface properties on the energy and mass budgets in the ice-covered oceans. Remote sensing data and in-situ observations are combined to derive the seasonal cycle of dominant sea-ice surface characteristics, and their relation to the transfer of solar radiation from the atmosphere through snow and sea ice into the upper ocean. This thesis shows that characteristics of the solar radiation under Arctic sea ice can be described directly as a function of sea-ice surface properties as, e.g., sea-ice type and melt pond coverage. Using this parameterization, an Arctic-wide calculation of solar radiation through sea ice identifies the surface melt onset as the main driver of the annual sea-ice mass and energy budgets. In contrast, an analysis of the spring-summer transition of Antarctic sea ice using passive microwave satellite observations indicates widespread diurnal freeze-thaw cycles in the top snow layers. While the associated temporary thawing is identified as the predominant melt process, subsequent continuous melt in deeper snow layers is rarely found on Antarctic sea ice. Instead of directly influencing the snow depth on Antarctic sea ice, these melt processes rather modify the internal stratigraphy and vertical density structure of the snowpack. An additional analysis of satellite scatterometer observations reveals that snow volume loss on Antarctic sea ice is mainly driven by changes in the lower snowpack, due to the widespread presence of sea-ice surface flooding and snow-ice formation prior to changes in the upper snowpack. As a consequence, the largely heterogeneous and metamorphous Antarctic snowpack prevents a direct correlation between surface properties and the respective characteristics of the penetrating solar radiation under the sea ice. However, surface flooding is identified as the key process governing the variability of the under-ice light regime on small scales. Overall, this thesis highlights that the mass and energy budgets of Antarctic sea ice are determined by processes at the snow/ice interface as well as the temporal evolution of physical snowpack properties. These results are in great contrast to presented studies on Arctic sea ice, where seasonally alternating interactions at the atmosphere/snow- or atmosphere/sea-ice interface control both the energy and mass budgets. An improved understanding of the seasonal cycle of dominant sea-ice and snow surface characteristics in the Arctic and Antarctic is crucial for future investigations retrieving sea-ice variables, such as sea-ice thickness and snow depth, from recent microwave satellite observations

Investigation of Sea Ice Using Multiple Synthetic Aperture Radar Acquisitions

The papers of this thesis are not available in Munin. Paper I: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Tomographic imaging of fjord ice using a very high resolution ground-based SAR system. Available in IEEE Transactions on Geoscience and Remote Sensing, 55 (2):698-714. Paper II: Yitayew, T. G., Ferro-Famil, L., Eltoft, T. & Tebaldini, S. (2017). Lake and fjord ice imaging using a multifrequency ground-based tomographic SAR system. Available in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(10):4457-4468. Paper III: Yitayew, T. G., Divine, D. V., Dierking, W., Eltoft, T., Ferro-Famil, L., Rosel, A. & Negrel, J. Validation of Sea ice Topographic Heights Derived from TanDEMX Interferometric SAR Data with Results from Laser Profiler and Photogrammetry. (Manuscript).The thesis investigates imaging in the vertical direction of different types of ice in the arctic using synthetic aperture radar (SAR) tomography and SAR interferometry. In the first part, the magnitude and the positions of the dominant scattering contributions within snow covered fjord and lake ice layers are effectively identified by using a very high resolution ground-based tomographic SAR system. Datasets collected at multiple frequencies and polarizations over two test sites in Tromsø area, northern Norway, are used for characterizing the three-dimensional response of snow and ice. The presented experimental results helped to improve our understanding of the interaction between radar waves and snow and ice layers. The reconstructed radar responses are also used for estimating the refractive indices and the vertical positions of the different sub-layers of snow and ice. The second part of the thesis deals with the retrieval of the surface topography of multi-year sea ice using SAR interferometry. Satellite acquisitions from TanDEM-X over the Svalbard area are used for analysis. The retrieved surface height is validated by using overlapping helicopter-based stereo camera and laser profiler measurements, and a very good agreement has been found. The work contributes to an improved understanding regarding the potential of SAR tomography for imaging the vertical scattering distribution of snow and ice layers, and for studying the influence of both sensor parameters such as its frequency and polarization and scene properties such as layer stratification, air bubbles and small-scale roughness of the interfaces on snow and ice backscattered signal. Moreover, the presented results reveal the potential of SAR interferometry for retrieving the surface topography of sea ice