<div> <div> <p>Global Navigation Satellite System Reflectometry (GNSS-R) has presented a great potential as an important approach for ocean remote sensing. Numerous studies have demonstrated that the shape of a code-correlation waveform of forward-scattered Global Positioning System (GPS) signals may be used to measure ocean surface roughness and related geophysical parameters such as wind speed. Recent experiments have extended the reflectometry technique to transmissions from communication satellites. Due to the high power and frequencies of these signals, they are more sensitive to smaller scale ocean surface features, which makes communication satellites a promising signal of opportunity (SoOp) for ocean remote sensing. Recent advancements in fundamental physics are represented by the new scattering model and bistatic radar function developed by Voronovich and Zavorotny based on the SSA (Small Slope Approximation). This new model allows the partially coherent scattering in low wind conditions to be correctly described, which overcomes the limitations of diffuse scattering inherited in the conventional KA-GO (Kirchhoff Approximation-Geometric Optics) model. Furthermore, exploration and practice using spaceborne platforms have become a primary research focus, which is highlighted by the launch of CYGNSS (Cyclone Global Navigation Satellite System) in 2016. CYGNSS is a NASA (National Aeronautics and Space Administration) Earth Venture Mission consisting of an 8 micro-satellite constellation of GNSS-R instruments designed to observe tropical cyclones.</p><p>However, in spite of the significant achievements made in the past 10 years, there are still a variety of challenges to be addressed currently in the ocean reflectometry field. To begin with, the airborne demonstration experiments conducted previously for S-band reflectometry provided neither sufficient amount of data nor the desired scenarios to assess high wind retrieval performance of S-band signals. The current L-band empirical model function theoretically does not also apply to S-band reflectometry. With respect to scattering models, there have been no results of actual data processing so far to verify the performance of the SSA model, especially on low wind retrievals. Lastly, the conventional model fitting methods for ocean wind retrievals were proposed for airborne missions, and new approaches will need to be developed to satisfy the requirement of spaceborne systems.<br></p><p>The research described in this thesis is mainly focused on the development, application and evaluation of new models and algorithms for ocean wind remote sensing. The first part of the thesis studies the extension of reflectometry methods to the general class of SoOps. The airborne reception of commercial satellite S-band transmissions is demonstrated under both low and high wind speed conditions. As part of this effort, a new S-band geophysical model function (GMF) is developed for ocean wind remote sensing using S-band data collected in the 2014 NOAA (National Oceanic and Atmospheric Administration) hurricane campaign. The second part introduces a dual polarization L- and S-band reflectometry experiment, performed in collaboration with Naval Research Lab (NRL), to retrieve and analyze surface winds and compare the results with CYGNSS satellite retrievals and NOAA data buoy measurements. The problems associated with low wind speed retrieval arising from near specular surface reflections are studied. Results have shown improved wind speed retrieval accuracy using bistatic radar cross section (BRCS) modeled by the SSA when compared with KA-GO, in the cases of low to medium diffuse scattering. The last part focuses on the contributions to the NASA-funded spaceborne CYGNSS project. It shows that the accuracy of CYGNSS ocean wind retrieval is improved by an Extended Kalman Filter (EKF) algorithm. Compared with the baseline observable methods, preliminary results showed promising accuracy improvement when the EKF was applied to actual CYGNSS data.<br><br></p></div></div>

Les vagues courtes sont omniprésentes à la surface des océans, avec des longueurs de quelques dizaines de mètres au mètre typiquement. Connaitre leurs directions de propagation en mer est important à plusieurs titres, notamment pour la compréhension de la dynamique de l'état de mer, des échanges air-mer ou de la dérive de particules en surface. Ces distributions directionnelles sont étudiées ici au regard des progrès récents réalisés en techniques d'instrumentation. L'analyse du bruit sismo-acoustique enregistré en grandes profondeurs permet d'extraire un comportement quasi-universel qui dépend indirectement de cette distribution à travers ladite intégrale de recouvrement. Il est cohérent avec des observations directes du champ de vagues obtenues à partir de reconstructions tridimensionnelles de la surface de l'océan. Alors que la direction de propagation des vagues longues s'aligne avec celle du vent, les vagues courtes s'en détachent d'autant plus à mesure que leurs échelles diminuent (bimodalité).La comparaison de ces observations avec les prédictions d'un modèle numérique de vagues, basé sur l'environnement WAVEWATCH®III, permet de constater que ces modèles sont qualitativement valables mais encore quantitativement incorrects. Une des possibilités explorées pour corriger cet effet est la prise en compte de sources de vagues courtes à ±90° de la direction du vent, qui pourraient être associées au déferlement des vagues longues. Une telle source à elle seule n'explique pas les formes des distributions directionnelles observées. D'autres mécanismes pourraient intervenir que de futures investigations pourront tenter de clarifier. / Short surface gravity waves are ubiquitous at the ocean surface, with lengths from a few tens of meters to a meter typically.Knowing their propagation directions at sea is important in several respects, especially for the understanding of sea-state dynamics, airsea interactions and particles surface drift.Their directional distributions are here investigated in the light of the recent progress made in instrumentation techniques. The analysis of ocean bottom seismo-acoustic noise records allows for the extraction of a quasi-universal behavior which indirectly depends on this distribution through the socalled overlap integral. It is coherent with direct observations of the wave field obtained from tri-dimensional reconstructions of the ocean surface elevation field. While the propagation direction of long waves aligns with the wind direction, short waves progressively detach from it towards small scales (bimodality).Comparing those measurements with the predictions of a spectral numerical wave model, based on WAVEWATCH®III environment, allows to realize that they provide qualitatively correct but quantitatively incorrect predictions. One of the possibilities here explored to correct for it, is by accounting for the sources of energy at ±90° to the wind direction, which could be associated with the breaking of long waves. This source term on its own does not explain the shapes of the observed directional distributions. Other mechanisms could come into play that future investigations will help clarify.

Chapter 2 The sea surface microlayer is a biogenic thin layer, comprising less than one millimeter of the ocean surface. This surface layer has gained much attention due to its dampening effect on ocean capillary ripples. The chemistry of the air-sea interface has been studied for decades; however, the structure and function of the marine bacterial community within the sea surface microlayer are still understudied. Although various sea surface microlayer sampling techniques were developed over the past decades, aseptic bacterial sampling in the open ocean is a rather challenging task. In this study, a new approach is presented. It is designed for bacterial sampling of the sea surface microlayer, which intends to reduce sampling contamination from the vessel, subsurface water and the investigators. A 47mm polycarbonate membrane was utilized at each sampling site. In addition, the metagenomic approach using the new generation 454 high-throughput DNA sequencing system was employed to compensate for the small sample size. Two sample sets were collected in summer 2010 and fall 2011 from the sea surface microlayer and underlying water (20 cm deep). A contamination assessment was carried out to determine that contamination might have been caused during the use of the sampling techniques. A total of 14,120 bacterial 16S rRNA gene sequences with an average length of 437.8 bp were obtained. A total of 1,254 Operational Taxonomic Units (OTUs) were constructed and 268 genera were identified. The results indicated that the bacterial compositions of the sea surface microlayer samples were distinct from those of the underlying water samples. This experiment demonstrated that the new generation sequencing platform and microbial metagenomics analysis software together served as powerful tools to gain a deeper understanding of microbial communities within the sea surface microlayer. Furthermore, it is suggested that the newly employed sampling methods could be used to obtain a snapshot of bacterial community structure as well as environmental conditions. Chapter 3 Synthetic aperture radar (SAR) remote sensing captures various fine-scale features on the ocean surface such as coastal discharge, oil pollution, vessel traffic, algal blooms and sea slicks. Although numerous factors potentially affect the SAR imaging process, the influence of biogenic and anthropogenic surfactants has been suggested as one of the primary parameters, especially under relatively low wind conditions. Surfactants have a tendency to dampen the short gravity-capillary ocean waves causing the sea surface to smoothen, thus allowing the radar to detect areas of surfactants. Surfactants are found in sea slicks, which are the accumulation of organic material shaped as elongated bands on the ocean’s surface. Sea slicks are often observable with the naked eye due to their glassy appearance and can also be seen on SAR images as dark scars. While the sources of surfactants can vary, some are known to be associated with marine bacteria. Countless numbers of marine bacteria are present in the oceanic environment, and their biogeochemical contributions cannot be overlooked. Not only do marine bacteria produce surfactants, but they also play an important role in the transformation of surfactants. In this study, we profiled the surfactant-associated bacteria composition within the biogenic thin layer of the ocean surface more commonly referred as the sea surface microlayer (SML). Bacterial samples were collected from the SML for comparative analysis from both within and outside of sea slick areas as well as the respective underlying subsurface water. The bacterial microlayer sampling coincided with SAR satellite, RADARSAT-2, overpasses to demonstrate the simultaneous in-situ measurements during a satellite image capture. The SML sampling method was designed to enable aseptic bacterial sampling. A 47 mm polycarbonate membrane was utilized at each sampling site to obtain a snapshot of the bacterial community structure at a specific space and time. Also, a new generation high-throughput sequencing method was employed to compensate for the small sample size acquired. A total of 27,006 nucleotide sequences (16S rRNA genes) with an average 437.8 bp in length were analyzed. The results revealed the presence of industrially important surfactant-producing marine bacteria, Acinetobacter, Bacillus, Corynebacterium and surfactant-degrading marine bacteria, Escherichia. In addition, Pseudomonas was detected which can be either a producer, decomposer or both. Recognizing that there is still a large number of marine bacterial species that have not been taxonomically classified nor recognized as surfactant-associated species, the effects on SAR imaging due to a high number of surfactant-associated marine bacteria is expected. This study has provided the basis for the biological importance for fine-scale synthetic aperture satellite imaging. Moreover, this new approach is expected to have applications in monitoring biological and chemical properties of the sea surface across the globe.

Ocean-surface Wireless Sensor Networks (WSN) are essential in various thalassic applications, such as maritime communication, ocean monitoring, seawater examination, pollution detection, etc. Formed by simple structured sensor nodes, ocean-surface WSN can improve the data transmission rate, enhance the monitoring resolution, expand the geographical coverage, extend the observation period, and lower the cost compared to the vessel-based monitoring approaches. Despite the importance and the broad applications of ocean-surface WSNs, little is known about the stability of the wireless links among the sensors. Especially, research suffers from the lack of an accurate model that describes the environmnetal effects, including the ocean surface movements and the wind speed on the link stability. The inappropriate understanding of link stability can result in network protocols that are not robust to environmental interruptions. Such a shortcoming decreases the network reliability and degrades the accuracy of the network planning. To compensate for this shortcoming, in this dissertation, we provide a thorough analysis on the stability of the wireless links over the ocean. In particular, we investigate and capture the effects of ocean waves on the link stability through the following steps. First, we use the linear wave theory and obtain a novel stochastic model of Line-of-Sight (LoS) links over the ocean based on the realistic behavior of ocean waves. Second, we present and prove an important theorem on the level-crossing of Wide Sense Stationary (WSS) random processes, and combine that with our stochastic model of LoS links to study two important indicators of link stability, i.e., the blockage probability and the blockage and connectivity periods. The former indicates the probability that a LoS link is blocked by the ocean waves while the latter determines the duration of on/off periods of the LoS links over the ocean. The aforementioned stability parameters directly affect different stages of network design, such as choosing the antenna height, planning the sensors' deployment distances, determining the packet length, designing the retransmission and scheduling strategies in the Medium Access Control (MAC) protocols and transport layer protocols, selecting the fragmentation threshold in Internet Protocol (IP), etc., which will be discussed in the respective chapters. In the last part of our dissertation, we investigate the problem of linear prediction of ocean waves, which has special importance in the design of ocean-surface WSNs. In this regard, we first introduce a low-complexity metric for effectiveness of k-step-ahead linear prediction, which we refer to as efficiency curve. The significance of efficiency curve becomes evident when we decide upon the number of previous samples in the linear prediction model, and determine the extent to which the predictor forecasts the future. After efficiency curve, we formulate an adaptive Wiener filter to predict the ocean waves and adapt the prediction model according to the environmental changes. / Doctor of Philosophy / Covering almost three quarters of the earth and supplying half of its oxygen, oceans are vital to the support of life on our planet. It is important to continuously monitor different parts of the ocean environment for tracking climate changes, detecting pollution, etc. However, the existing monitoring approaches have serious weaknesses, which prevent us from constantly monitoring the state of ocean, and drastically limit the geographical coverage. For instance, the traditional ocean monitoring system using oceanographic research vessels is time-consuming and expensive. Besides, it has low resolution in time and space, which poses serious challenges to oceanographers by providing under-sampled records of the ocean. To compensate for these defects, one of the promising alternatives is to employ Wireless Sensor Networks (WSN) which has many advantages, such as real-time access to data for a longer period of time and a larger geographical coverage of the ocean, higher resolution of monitoring, faster processing of collected data and instantaneous transmission to onshore monitoring centers. With the benefit of simple structure sensor nodes, ocean-surface WSNs can also decrease the cost by at least one order of magnitude compared to the conventional approaches. Despite the advantages that ocean surface WSN have over traditional ocean monitoring methods, ocean surface WSN research suffers from the lack of an accurate model that describes the stability of wireless links among sensor nodes. While some of the existing literature has developed accurate models of the electromagnetic wave propagation over the ocean surface, they have failed to consider the environmental effects, such as ocean waves on the stability of the links. To fill this void, in this dissertation, we investigate ocean surface waves' effects on the Line-of-Sight (LoS) link between the sensors in an ocean-surface WSN. Specifically, we derive the blockage probability, and the blockage and connectivity periods of LoS links between a transmitter and receiver pair due to wave movements. In addition to the link stability analysis, we dedicate the last part of this dissertation to look into the problem of linear prediction of ocean waves, which has special importance in the design process of ocean-surface WSNs. In this regard, we present a low-complexity metric for effectiveness of k-step-ahead linear prediction, and formulate an adaptive Wiener filter to predict the ocean waves and adapt the prediction model according to the environmental changes.

River discharge can affect ocean surface temperature by altering stratification within the oceanic mixed layer. A hitherto unexplored aspect of present climate is the feedback of river runoff onto climate. This thesis presents an investigation of the impact of global river runoff on oceans and climate using a fully coupled global climate model, Community Climate System Model (CCSM). Two model simulations for a period of 100 years have been carried out: 1) a reference run (CTRL) that incorporates all the features of a global coupled model with river runoff into the ocean embedded in it, and 2) a sensitivity run (NoRiv) in which the global river runoff into the ocean is blocked. Comparison of model climate devoid of fluvial discharge with the reference run reveals the significance of fluvial discharge in the present climate. By the end of 50 years of NoRiv experiment, salinity growth slows down and reaches a quasi-stable state. Regions close to river mouths exhibited maximum salinity rise that can potentially alter local density and stratification. On an average, denser and saltier waters in the NoRiv run annihilate barrier layer and form a deeper mixed layer, compared to CTRL run. Density gradient created by the modulation in salinity set forth anomalous currents and circulation across coastlines that carries coastal anomalies to open ocean, preventing local salinity buildup. Arctic Ocean, Bay of Bengal, northern high latitude Pacific and the Atlantic are the most affected regions in terms of changes in salinity and temperature. Model simulations demonstrate that major transformation in Arctic freshwater budget can have potential impact on northern Pacific and Atlantic climate. In the absence of runoff, global average sea surface temperature (SST) rise by about ~ 0.5oC, with major contribution from northern higher latitude oceans. In the Pacific, high latitude warming is related to deepening of mixed layer as well as the northward transport of low latitude warmer waters. Substantial cooling in the central equatorial Pacific (~1oC during winter) can alter large-scale ocean-atmosphere circulation, including El Niño-Southern Oscillation (ENSO). The reinforcement of Pacific and Atlantic western boundary currents aids the transport of warm saline water from low latitudes to higher latitudes. The results suggest that the river runoff can have potential impact on oceanic climate. Response of Indian summer monsoon rainfall to global continental runoff is also examined. In the NoRiv run, average summer monsoon rainfall over India increased by ~ 0.55 mm day−1. Consistent with the increase in annual average Indian monsoon rainfall, all other northern hemispheric monsoon systems showed an increase, while southern hemispheric monsoons weakened. Associated with enhanced monsoon, the periodicity of ENSO in the NoRiv run changes as a result of cooling tendency in the equatorial Pacific, a sign of consistent La Niña. Equatorial Pacific cooling, in spite of a global ocean warming trend, is found to be primarily because of the enhanced local easterly winds and resultant strong equatorial upwelling. Cold anomaly due to upwelling spread entire equatorial Pacific basin within a span of 50 years. The La Niña situation in the Pacific favored increased monsoon rainfall over Indian subcontinent. Another surprising result of this study is the strengthening of ENSO-monsoon relationship in the NoRiv run. This suggests that the river discharge can be considered as a dampening force in the ENSO-monsoon relationship. Northern hemisphere showed a clear warming in the NoRiv simulation compared to CTRL, the result of which is an enhanced trans-hemispheric gradient. Cross-equatorial winds triggered by this gradient blow from southern hemisphere and shift the Inter Tropical Convergence Zone (ITCZ) northward, increasing the precipitation in the northern hemisphere. The cooling in the eastern equatorial Indian Ocean and the warming in the west, reflected in the increase in number of positive Indian Ocean Dipole (IOD) events (9 positive and 5 negative IOD events in the last 50 years), also favored summer-time rainfall over India.