<div> <div> <div> <p>Rapid melting of sea ice and an increased warming have been observed over the Arctic since 1990s and is expected to continue in future climate projections. Possible linkage between the Arctic sea ice and the Northern Hemisphere mid-latitude circulation has been studied previously but is not yet fully understood. This dissertation investigates the influence of the Arctic on the mid-latitudes and the underlying dynamical mechanisms. Specifically, we hypothesize that the stratosphere and its coupling with the troposphere play an important role in amplifying and extending the mid-latitude circulation response to arctic warming. </p><p><br></p> <p>First, we assess the robustness of the stratospheric pathway in linking the sea ice variability, specifically over the Barents-Kara Sea (BKS), in late autumn and early winter to the mid-latitude circulation in the subsequent winter using an ensemble of global climate model simulations. We analyze two groups of models from the Coupled Model Intercomparison Project phase 5 (CMIP5) archive, one with a well-resolved stratosphere (high-top models) and the other with a poorly-resolved stratosphere (low-top models) to distinguish the role of the stratospheric pathway. It has been found that, collectively, high-top models are able to capture the persistent mid-latitude circulation response in the subsequent winter. The response in low-top models is, however, weaker and not as long-lasting most likely due to lack of stratospheric variability. Diagnosis of eddy heat flux reveals that stronger vertical wave propagation leads to a stronger response in stratospheric polar vortex in high- top models. The results robustly demonstrate that multi-model ensemble of CMIP5 high-top models are able to capture the prolonged impact of sea ice variability on the mid-latitude circulation and outperforms the low-top models in this regard.</p><p><br></p></div></div></div><div><div><div> <p>We further explore the dynamical linkage between the BKS sea ice loss and the Siberian cold anomalies using a comprehensive Atmospheric General Circulation Model (AGCM), with a well-resolved stratosphere, with prescribed sea ice loss over BKS region. Decomposition of dynamic and thermodynamic components suggests a dynamically induced warm Arctic cold Siberia pattern in the winter following sea ice loss over the BKS in late autumn. Specifically, the results show that the meridional component of the horizontal temperature advection, from the Arctic into the Siberia, dominates in driving a cold temperature anomaly. Additionally, we conduct targeted experiments in order to quantitatively measure the role of the stratospheric pathway. We find that the stratosphere plays a critical role in the tropospheric circulation anomaly characterized by an intensified ridge-trough pattern that is attributable for the enhanced meridional temperature advection from the Arctic into the Siberia. </p><p><br></p> <p>Next, we extend our study to investigate the sensitivity to geographical location of Arctic sea ice loss and associated warming in modulating the atmospheric circulation. In particular, we assess the linear additivity of the regional Arctic sea ice loss and Arctic Amplification (AA), using a simplified dry dynamical core model. We find that the responses to regional AA over three key regions of the Arctic, i.e. Barents- Kara Sea, East Siberia-Chukchi sea and Baffin Bay-Labrador Sea, separately, show similar equatorward shift of the tropospheric jet but differences in the stratospheric polar vortex. In addition, responses to regional Arctic Amplification are not linearly additive and the residual resembles a positive Northern Annular Mode-like structure. Additional targeted experiments further diagnose the role of the stratosphere in the non-linearity. It is found that the stratosphere-troposphere coupling plays an important role in driving the non-linear circulation response to regional AA. </p><p><br></p> <p>The findings of our research leads to a systematic understanding of the role of the stratospheric pathway in modulating the mid-latitude circulation response to Arctic sea ice loss and accompanied surface warming. Our study suggests that the representation of the stratosphere in climate models plays an important role in correctly simulating the mid-latitude circulation response and could be accountable for the some of the discrepancies among recent studies. Additionally, the result indicates that studying the regional sea ice loss might not provide the full picture of pan-Arctic sea ice melting and caution the use of regional sea ice to explain the recent trend.</p></div></div></div>

The sea ice extent change and variability of the Canadian Arctic Archipelago (CAA) are quite different compared to the Arctic as a whole due to its unique geographic settings. In this thesis, the sea ice retreat processes, the connection with other Arctic regions, and the linkages to the surface radiation flux in the CAA are examined. The sea ice retreat processes in the CAA follow a four-phase process: a slow ice melt phase that usually lasts until early June (phase 1); a quick melt phase with large daily sea ice extent change which lasts close to half-a-month (phase 2); a slow melt phase that looks like slow sea ice melt or even a small ice increase that lasts another half-a-month (phase 3); and a steady ice decrease phase (phase 4). With the help of Moderate-Resolution Imaging Spectroradiometer (MODIS) data, it is identified that the quick melt in phase 2 is actually melt ponding, with melt ponds being falsely identified as open water by passive microwave. A simplified data assimilation method is then developed to improve the passive microwave sea ice concentration estimation by fusion with MODIS ice surface temperature data. The ice concentration from the analysis is found to improve the original passive microwave sea ice concentration estimation, with the largest improvements during sea ice melt. The sea ice retreat patterns in the CAA region are correlated with the sea ice retreat patterns in other regions of the Arctic. A decision tree classifier is designed to segment the sea ice retreat patterns in the CAA into several classes and classification maps are generated. These maps are effective in identifying the geographic locations that have large changes in the sea ice retreat patterns through the years. The daily progressions of the surface radiation components are described in detail. Due to the lack of multiple reflection, the percentage of shortwave radiation at the top of atmosphere that reaches the surface is influenced by the form of melt ponds over ice surface. The roles that each surface radiation component plays in forcing sea ice retreat are different in different years.

This thesis examines the role of remote sensing technology in providing information to northern residents of Kugluktuk and Cambridge Bay, Kitikmeot region of Nunavut, Western Canadian Arctic, for the purpose of improving sea ice trafficability and safety. The main objectives of this thesis include 1) the identification of northern community sea ice information needs that can be addressed using remote sensing, and 2) the creation of remote sensing-based products showing sea ice surface roughness information useful to community sea ice trafficability and safety. Thesis outcomes include the refinement and dissemination of information and products with these communities. Research methods involved interviews with northern community members that were analysed using thematic analysis, as well as quantitative assessments of sea ice roughness using satellite datasets. Maps of sea ice surface roughness were created using Sentinel-1 synthetic aperture radar and the Multi-angle Imaging Spectroradiometer, and were evaluated against fine-scale airborne LiDAR data. / Graduate / 2020-07-31

Arctic sea ice has undergone a dramatic transformation in recent decades, including a substantial reduction in sea ice extent in summer months. Such changes, combined with relatively recent advancements in seasonal (1-12 months) to decadal forecasting, have prompted a rapidly-growing body of research on forecasting Arctic sea ice on seasonal timescales. These forecasts are anticipated to benefit a vast array of end-users whose activities are dependent on Arctic sea ice conditions. The research goal of this thesis is to address fundamental challenges pertaining to seasonal forecasts of Arcitc sea ice, with a particular focus placed on improving operational sea ice forecasts in the Canadian Seasonal to Interannual Prediction System (CanSIPS). Seasonal forecasts are strongly dependent on the accuracy of observations used as initial condition inputs. A key challenge initializing Arctic sea ice is the sparse availability of Arctic sea ice thickness (SIT) observations. I present on the development of three statistical models that can be used for estimating Arctic SIT in real time for sea ice forecast initialization. The three statistical models are shown to vary in their ability to capture the recent thinning of sea ice, as well as their ability to capture interannual variations in SIT anomalies; however, each of the models is shown to dramatically improve the representation of SIT compared to the climatological SIT estimates used to initialize CanSIPS. I conduct a thorough assessment of sea ice hindcast skill using the Canadian Climate Model, version 3 (one of two models used in CanSIPS), in which the dependence of hindcast skill on SIT initialization is investigated. From this assessment, it can be concluded that all three statistical models are able to estimate SIT sufficiently to improve hindcast skill relative to the climatological initialization. However, the accuracy with which the initialization fields represent both the thinning of the ice pack over time and interannual variability impacts predictive skill for pan-Arctic sea ice area (SIA) and regional sea ice concentration (SIC), with the most robust improvements obtained with two statistical models that adequately represent both processes. The final goal of this thesis is to improve the quantification of uncertainty in seasonal forecasts of regional Arctic sea ice coverage. Information regarding forecast uncertainty is crucial for end-users who want to quantify the risk associated with trusting a particular forecast. I develop statistical post-processing methodology for improving probabilistic forecasts of Arctic SIC. The first of these improvements is intended to reduce sampling uncertainty by fitting ensemble SIC forecasts to a parametric probability distribution, namely the zero- and one- inflated beta (BEINF) distribution. It is shown that overall, probabilistic forecast skill is improved using the parametric distribution relative to a simpler count-based approach; however, model biases can degrade this skill improvement. The second of these improvements is the introduction of a novel calibration method, called trend-adjusted quantile mapping (TAQM), that explicitly accounts for SIC trends and is specifically designed for the BEINF distribution. It is shown that applying TAQM greatly reduces model errors, and results in probabilistic forecast skill that generally surpasses that of a climatological reference forecast, and to some degree that of a trend-adjusted climatological reference forecast, particularly at shorter lead times. / Graduate

IP25 is a highly branched isoprenoid alkene derived from certain Arctic sea ice diatoms that, when detected in marine sediments, has been used as a proxy for past Arctic sea ice over the last decade. In the current study, the structure of this biomarker was determined following large-scale extraction from sediment material collected from the Canadian Arctic. After purification, the structure of IP25 was confirmed by NMR spectroscopy as being the same as that of a laboratory standard. The purified IP25 was subsequently used to obtain a quantitative (GC-MS) instrumental response factor that could be used to improve the future quantification of IP25 and would help to produce a robust database. IP25, other highly branched isoprenoid (HBI) lipids and some other phytoplanktonic lipids (sterols) were analysed to provide modern and past sediment-based sea ice reconstructions for the Barents Sea. First, a surface sediment study was conducted and biomarker distributions were compared to satellite sea ice records. The occurrence of IP25 was consistent with the presence/absence of seasonal sea ice but there was also evidence of lateral transport of IP25 and other biomarkers in sediments from the southern Barents Sea. In contrast to some previous studies, abundances of IP25, and of those combined with other biomarkers, including sterols, did not show strong quantitative relationships to sea ice concentration. The surface study was used to relate biomarker distributions to recent sea ice and oceanographic conditions and apply this information to long-term sediment records in the eastern and western Barents Sea covering ca. 2 kyr and 11 kyr (Holocene) respectively. IP25 concentrations for the former were found to be very variable and were used to identify the period with maximum sea ice cover occurring from ca. 900 - 400 cal. yr BP where the highest abundances of IP25 and IRD were observed. Similarly, biomarker results from the eastern Barents Sea provided evidence for a dynamic advance of the marginal sea ice zone potentially situated at ca. 78° N (maximum extent) during ca 9.4 – 5.9 cal. kyr BP, to late Holocene and modern day maximum MIZ advance ca. 75° N. Replicate analysis of various biomarkers in individual push-cores collected from a box core obtained from Rijpfjorden (north Svalbard) demonstrated some variability between cores. Variability in individual biomarker concentrations was lowest for HBI lipids and greatest for sterols. These data are consistent with a selective and relatively minor source of the former. In contrast, the somewhat more generic origins of sedimentary sterols likely explain the greater variability in their distributions between cores Finally, the strong abundance relationship between IP25 and a structurally related di-unsaturated HBI (C25:2) was confirmed in all sediments, similar to that found between two tri-unsaturated HBIs, consistent with co-production by certain marine phytoplankton. The progressive use of novel HBIs with two or three degrees of unsaturation (e.g. C25:2 and C25:3) could provide further valuable insights into environmental conditions.

La glace de mer couvre jusqu’à 6% de la surface de notre planète. Autour du continent Antarctique, sa superficie varie entre 3.8 et 19 millions de km² (en février et septembre respectivement). Cette superficie présente des variations interannuelles. En parallèle, une évolution de la superficie de la glace de mer a également pour origine le réchauffement climatique global, très médiatisé à l’heure actuelle. Dans ce contexte, et étant donné le rôle que joue la banquise au sein de l’Océan Austral, des études de l’évolution de la glace de mer sont devenues fondamentales. Ce travail a pour objectif d’étudier les relations complexes qui existent entre les processus chimiques, physiques et biologiques qui se déroulent au sein de la glace de mer. La détermination des propriétés physiques et de la composition chimique des glaces de mer correspond en effet à un pré-requis indispensable à l’étude des cycles géochimiques qui existent dans la banquise. Différentes glaces de mer, naturelles ou artificielles, ont été analysées. Pour ce faire, les caractéristiques spécifiques à ce type de glace font que des méthodes d’analyse de la composition en gaz particulières ont été nécessaires. Nous avons ainsi pu montrer que le contenu et la composition en gaz des différentes glaces analysées dépendent de facteurs physico-chimiques et de facteurs biologiques. L’impact des facteurs physico-chimiques se marque lors de l’incorporation initiale des impuretés dans la glace de mer et via une diffusion "post-génétique" tant que la glace est plus chaude que –5°C. En outre, les organismes photosynthétiques sont à l’origine d’une production d’oxygène et d’une consommation de dioxyde de carbone. La composition en gaz résultante peut donc être sensiblement différente de la composition atmosphérique ou de celle des gaz dissous dans l’eau de mer sous-jacente, en été comme en hiver. Il s’agit par conséquent de sérieusement envisager l’impact potentiel de la glace de mer et des microorganismes qu’elle contient, lors du réchauffement et de la débâcle, sur les échanges entre atmosphère et océan comme sur leurs compositions respectives.

Approved for public release; distribution is unlimited / Variability of the MABL and its effect on the electromagnetic (EM) refractive structure around the Greenland Sea marginal ice zone were examined. Rawinsonde profiles and surface observations collected from 3 ships during MIZEX-87(20 March-11 April) served as the data set. A program, developed to calculate the refractivity at each vertical level of the rawinsonde profiles, also identified the levels at which trapping, superrefraction and subrefraction occurred. Temporal studies showed that a higher incidence of anomalous refractive layers occurred during periods when the region was under the influence of high pressure. More than 50% of the time, trapping and super-refractive layers were attributed to development of a capping inversion just above the MABL during these periods. Spatial studies showed that the refractive structure varied relative to distance from the ice edge as did the depth of the MABL. An upward slope in refractive layer heights was observed from the ice toward the open water. Significant spatial inhomogeneity was observed over horizontal ranges of less than 100 km. This was attributed to both the large-scale synoptic forcing affecting the region and to variations in the surface fluxes of heat and moisture over the ice and over the water. A range-dependent ray trace model developed at the Naval Ocean Systems Center was used to show how the ray paths of EM waves vary with a changing refractive structures. Keywords: Air water interactions, Greenland Sea, Atmospheric refraction, Electromagnetic wave propagation, Heat flux, Sea ice. Theses. (EDC) / http://archive.org/details/temporalspatialv00grot / Lieutenant, United States Navy

Bering Sea storms regularly bring adverse environmental conditions, including large waves and storm surges of up to 4 m, to the west coast of Alaska. These conditions can cause flooding, erosion and other damage that affects marine subsistence activities and infrastructure in the low-lying coastal communities. Storm impacts also include interactions with sea ice in various states: large floes, shore-fast ice, the acceleration of sea-ice formation in frazil or slush state, and the formation of slush-ice berms. Slush-ice berms are accumulations of slush ice that develop under the right wind, water level, water and air temperature, and snow conditions. During a strong wind event, large amounts of slush may be formed and pushed onto the shore, where the slush can accumulate, solidify and protect communities from flooding and erosion. Slush ice berms can also be problematic, restricting access to the coast and presenting other hazards. Residents of Shishmaref and Shaktoolik, communities on the west coast of Alaska, observed the formation of slush-ice berms during storms that occurred in 2007, 2009 and 2011. These formations are important to the communities, and it would be useful to develop the capacity to predict their occurrence. However, scientific work has not been conducted on this phenomenon, with the result that a physical conceptual model describing the formation of slush-ice berms does not exist. In recognition of this need, a project thesis was designed, and had as its main objective to identify and document the environmental and synoptic weather conditions that lead to these types of events, and to develop a descriptive physical conceptual model of slush-ice berm formation. A key to this work was the engagement of traditional knowledge holders and local observers to gather data and information about slush ice and slush-ice berm formation, along with the specific dates when these events took place. This dissertation is organized around three major elements: development of a conceptual model of slush-ice berm formation; presenting the traditional knowledge gathered that led to the development of this model; and documenting the methods and tools used to engage traditional knowledge holders and local observers in this process. In this dissertation, the knowledge from traditional knowledge holders on slush ice formation is presented in the context of feeding into a physical scientific process – specifically, developing a descriptive physical conceptual model of slush-ice berm formation. It is expected that this type of research will contribute to slush-ice berm forecasting which would aid communities’ safety by improving assessment of environmental risk. / Graduate

La glace de mer Arctique connaît actuellement de profondes mutations dans sa structure et sa variabilité. Le déclin récent de la couverture estivale de glace de mer Arctique, qui a atteint un nouveau record en septembre 2012, a relancé l'intérêt stratégique de cette région longtemps oubliée. La prévision de glace de mer à l'échelle saisonnière est ainsi un problème d'océanographie opérationnelle qui pourrait intéresser nombre d'acteurs économiques (pêche, énergie, recherche, tourisme). De plus, en tant que conditions aux limites pour l'atmosphère, la glace de mer peut induire une prévisibilité de l'atmosphère à l'échelle saisonnière, au même titre que les anomalies de température de surface de l'océan sous les tropiques. Nous présentons dans cette thèse la construction d'un système de prévisions saisonnières dédié à la glace de mer Arctique avec le modèle couplé CNRM-CM5.1, développé conjointement par le CNRM-GAME et le CERFACS. Nous passons en revue la stratégie d'initialisation, la réalisation et l'évaluation des hindcasts (ou rétro-prévisions). La communauté dispose d'observations de concentration de glace de mer, mais de très peu de données d'épaisseur à l'échelle du bassin. Afin d'initialiser la glace de mer et l'océan dynamiquement et thermodynamiquement, nous avons choisi d'utiliser la composante océan-glace de mer de CNRM-CM5.1, NEMO-GELATO. L'initialisation consiste à forcer NEMO-GELATO avec les champs météorologiques issus de la réanalyse ERA-Interim, sur la période 1990-2010. Des corrections appliquées aux forçages basées sur des observations satellitaires et in-situ nous permettent d'obtenir une bonne simulation de l'océan et de la glace de mer en terme d'état moyen et de variabilité interannuelle. L'épaisseur reste néanmoins sous-estimée. Quelques propriétés de prévisibilité intrinsèque de la glace de mer Arctique sont ensuite présentées. Une étude de prévisibilité potentielle diagnostique nous a permis de distinguer deux modes de prévisibilité de la glace de mer à l'aide du volume et de la structure sous-maille d'épaisseur. Un « mode de persistance » concerne la prévisibilité de la couverture d'hiver. La surface de glace de mars est potentiellement prévisible à 3 mois à l'avance par la seule persistance, et dans une moindre mesure à l'aide des surfaces couvertes par la glace relativement fine. Un « mode de mémoire » concerne la prévisibilité de la couverture estivale. La surface de glace de septembre est potentiellement prévisible jusqu'à 6 mois à l'avance à l'aide du volume et surtout de la surface couverte par la glace relativement épaisse. Ces résultats suggèrent donc qu'une bonne initialisation du volume et de la structure d'épaisseur en fin d'hiver permettrait une bonne prévisibilité des étendues de fin d'été. Les prévisions d'été et d'hiver présentent des scores particulièrement encourageants, que ce soit en anomalies brutes ou en anomalies par rapport à la tendance linéaire. Cela suggère une prévisibilité liée à l'état initial et non aux forçages externes imposés. L'analyse des prévisions d'été montre que le volume et les structures d'épaisseur de l'état initial expliquent l'essentiel des différentes prévisions, ce qui confirme l'existence du « mode de mémoire » malgré un fort biais radiatif. L'analyse des prévisions d'hiver suggère que l'étendue initiale explique une partie des différentes prévisions, un indice du « mode de persistance » des prévisions hivernales. Une analyse régionale des prévisions d'hiver permet de préciser le rôle de l'océan dans ces prévisions, et montre dans quelle mesure nos prévisions pourraient être utilisées de manière opérationnelle, notamment en mer de Barents / Sea ice experiences some major changes in the early 21st century. The recent decline of the summer Arctic sea ice extent, reaching an all-time record low in September 2012, has woken renewed interest in this remote marine area. Sea ice seasonal forecasting is a challenge of operational oceanography that could benefit to several stakeholders : fishing, energy, research, tourism. Moreover, sea ice is a boundary condition of the atmosphere. As such, as tropical sea surface temperature, it may drive some atmosphere seasonal predictability. The goal of this PhD work was to set up a dedicated Arctic sea ice seasonal forecasting system, using CNRM-CM5.1 coupled climate model. We address the initialization strategy, the creation and the evaluation of the hindcasts (or re-forecasts). In contrast to sea ice concentration, very few thickness data are available over the whole Arctic ocean. In order to initialize sea ice and the ocean dynamically and thermodynamically, we used the ocean-sea ice component of CNRM-CM5.1, named NEMO-GELATO, in forced mode. The initialization run is a forced simulation driven by ERA-Interim forcing over the period 1990-2010. Corrections based on satellite data and in-situ measurements leads to skilful simulation of the ocean and sea ice mean state and interannual variability. Sea ice thickness seems overall underestimated, based on the most recent estimates. Some characteristics of sea ice inherent predictability are then addressed. A diagnostic potential predictability study allowed us to identify two regimes of predictability using sea ice volume and the ice thickness distribution. The first one is the 'persistence regime', for winter sea ice area. March sea ice area is potentially predictable up to 3 months in advance using simple persistence, and surface covered by thin ice to a lesser extent. The second one is the 'memory regime', for summer sea ice area. September sea ice area is potentially predictable up to 6 months in advance using volume and to a greater extent the area covered by relatively thick ice. These results suggest that a comprehensive winter volume and thickness initialization could improve the summer forecasts. Summer and winter seasonal hindcasts shows very encouraging skills, in terms of raw and detrended anomalies. These skills suggest a predicatibility from initial conditions besides predictability due to the trend. Summer forecasts analysis shows that the volume and the ice thickess distribution explains a high fraction of the variance of predicted sea ice extent, which confirms the existence of the 'memory regime'. Winter forecasts also suggest the 'persistence regime'. A regional investigation of the winter hindcast helps precising the role of the ocean in the forecasts, and shows to what extent our system predictions could be used operationally, especially in the Barents Sea

Marine phytoplankton are known to produce UV-absorbing compounds (UVACs) for protection against UV radiation. To assess whether the same strategy applies to sea ice-associated algal communities, MAAs were measured in algae associated with surface melt ponds, sea ice, sea ice−water interface, and underlying seawater in a coastal bay of the Canadian Arctic Archipelago during the 2011 spring melt transition. Six UVACs were detected as the spring melt progressed, namely shinorine, palythine, and porphyra-334 and three unknowns (U1, U2 and U3). U1 was most likely palythene, another MAA. The molecular identities of the other two UVACs, U2 and U3, which have an absorption maximum of 363 and 300 nm, respectively, remain to be structurally elucidated. The results confirm that Arctic sea ice-associated algal communities are capable of producing photoprotectants and that spatial and temporal variations in MAA and other UVAC synthesis are affected by snow cover and UV radiation exposure. / May 2016