Sea ice is of great interest due to its effect on the global climate, the Earth's ecosystem, and human activities. Microwave remote sensing has proven to be an effective way to measure many of the characteristics of sea ice. In particular, several algorithms map the daily sea ice extent using a variety of instruments. Enhanced resolution images generated from the Scatterometer Image Reconstruction (SIR) algorithm can be used to generate a high resolution ice extent map. Previous algorithms using SIR images were developed for scatterometers which are no longer operational. The Advanced Scatterometer (ASCAT) is a newer scatterometer which has different characteristics from the earlier scatterometers. The previous algorithms do not perform as well when applied to ASCAT. This thesis presents a new algorithm for ASCAT developed to discriminate sea ice from the open ocean and create daily maps of the ice extent. It is developed from previous algorithms used on earlier scatterometers. The algorithm uses an iterative Bayes decision rule to classify pixels as sea ice or ocean. Digital image processing techniques are used to reduce misclassifications. The ice maps from the new algorithm are compared with the NASA Team sea ice concentration maps from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The comparisons include: difference in area, distance between ice edges, number of missed and false detections. The new ice maps are also compared with the Remund-Long algorithm for the QuikSCAT satellite using the same metrics. The ice edge is verified with high resolution Synthetic Aperture Radar (SAR) data. The new ice maps perform similarly to previous ice mapping algorithms for scatterometers.

Reliable ocean wind vector measurements can be obtained using active microwave remote sensing (scatterometry) techniques. With the increase in the number of severe hurricanes making landfall in the United States, there is increased emphasis on operational monitoring of hurricane winds from aircraft. This thesis presents a data processing algorithm to provide real-time hurricane wind vector retrievals (wind speed and direction) from conically scanning airborne microwave scatterometer measurements of ocean surface backscatter. The algorithm is developed to best suit the specifications for the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division's airborne scatterometer – Integrated Wind and Rain Airborne Profiler (IWRAP). Based on previous scatterometer wind retrieval methodologies, the main focus of the work is to achieve rapid data processing to provide real-time measurements to the NOAA Hurricane Center. A detailed description is presented of special techniques used. Because IWRAP flight data were not available at the time of this development, the wind retrieval performance was evaluated using a Monte Carlo simulation, whereby radar backscatter measurements were simulated with instrument and geophysical noise and then used to infer the surface wind conditions in a simulated (numerical weather model) hurricane wind field

No description available.

No description available.

Sea ice is a vital component of the cryosphere and does not only influence the polar regions but has a more global influence. Indeed, sea ice plays a major role in the regulation of the global climate system as the sea ice cover reflects the sun radiation back to the atmosphere keeping the polar regions cool. The shrinkage of the sea ice cover entails the warming up of the oceans and as a consequence, a further amplification of the melting of sea ice. Therefore, the polar regions are sensitive to climate change and monitoring the sea ice cover is very important. To assess sea ice change in the polar regions, satellite active microwave sensors, scatterometers, are used to observe the evolution of sea ice extent and sea ice types. Thus, this research aims at creating a historic record of daily global Arctic and Antarctic sea ice extents and analysing the change in sea ice types with scatterometer data. A Bayesian sea ice detection algorithm, developed for the Advanced scatterometer (ASCAT), is applied and tuned to the configurations of the scatterometers on board the European Remote Sensing satellites, ERS\textendash 1 and ERS\textendash 2. The sea ice geophysical model functions (GMFs) of ERS and ASCAT are studied together to validate the use of ASCAT sea ice GMF extrapolated to the lower incidence angles of ERS. The main adaptations from the initial algorithm aim at compensating for the lower observation densities afforded by ERS with a refined spatial filter and time\textendash variable detection thresholds. To further analyse the backscatter response from sea ice and derive information on the different sea ice types, a new model of sea ice backscattering at C\textendash band is proposed in this study. This model has been derived using ERS and ASCAT backscatter data and describes the variation of sea ice backscatter with incidence angle as a function of sea ice type. The improvement of the sea ice detection algorithm for ERS\textendash 1 and ERS\textendash 2, operating between 1992 and 2001, leads to the extension of the existing records of daily global sea ice extents from the Quick scatterometer (QuikSCAT) which operated from 1999 to 2009 and ASCAT operating from 2007 onwards. The sea ice extents from ERS, QuikSCAT and ASCAT show excellent agreement during the overlapping periods, attesting to the consistency and homogeneity of the long\textendash term scatterometer sea ice record. The new climate record is compared against passive microwave derived sea ice extents, revealing consistent differences between spring and summer which are attributed to the lower sensitivity of the passive microwave technique to melting sea ice. The climate record shows that the minimum Arctic summer sea ice extent has been declining, reaching the lowest record of sea ice extent in 2012. The new model for sea ice backscatter is used on ERS and ASCAT backscatter data and provides a more precise normalization of sea ice backscatter than was previously available. An application of this model in sea ice change analysis is performed by classifying sea ice types based on their normalized backscatter values. This analysis reveals that the extent of multi\textendash year Arctic sea ice has been declining remarkably over the period covered by scatterometer observations.

Radar-based remote sensing is consistently growing, and new technologies and subsequent techniques for characterization are changing the feasibility of understanding the environment. The emergence of easily accessible unmanned aircraft system (UAS) has broadened the scope of possibilities for efficiently surveying the world. The continued development of low-cost sensing systems has greatly increased the accessibility to characterize physical phenomena. In this thesis, we explore the viability and implementation of using UAS as a means of radar-based remote sensing for ground penetrating radar (GPR) and polarimetric scatterometry. Additionally, in this thesis, we investigate the capabilities and implementations of low-cost microwave technologies for applications in radar-based remote sensing compared to higher fidelity and more expensive technologies of similar scope.

A dual-frequency system is needed to better understand natural processes that constitute the environment and seasonal cycles of the Earth. A system working at two different wavelengths acquiring data simultaneously will give a valuable dataset since the conditions on the ground will be exactly the same. Hence, elements such as wind, soil moisture or any other changes on the ground will not interfere in the mea- surements. This thesis explains how an S-band radar was built and tested. Moreover, the experiments done with a Ka-band radar used as a scatterometer are explained as well as the data processing and analysis. Finally, the two systems are used to get dual-frequency measurements from an airborne platform. The dual-frequency data is explored, showing the differences in normalized radar cross-section between frequencies and discussing the interferometric measurements.

Os padrões de circulação do Atlântico Sudoeste são caracterizados por uma diversidade de massas de água. A presença das correntes associadas ao giro subtropical e a incursão para norte da Corrente Circumpolar Antártica (CCA) determinam extensas regiões de largo gradiente de Temperatura da Superfície do Mar (TSM). Ao mesmo tempo, circulações de mesoescala geram intensos gradientes setorizados, ou reforçam o contraste de larga-escala. Consequentemente, frentes oceânicas de diferentes escalas são formadas ao longo desses gradientes. Quando o vento sopra sobre essas frentes, os fluidos trocam calor e momentum alterando suas propriedades dinâmicas e termodinâmicas. Nesse trabalho visamos caracterizar as alterações no campo de vento superficial que podem ser atribuídas a essas trocas. Para isso, foi aplicado um algoritmo de detecção de frentes em campos de Temperatura da Superfície do Mar (TSM) derivados do conjunto OSTIA. Em situações de escoamento atmosférico sinótico homogêneo, foram calculados o divergente e rotacional do vento medido pelo escaterômetro QuickSCAT ao longo das zonas frontais, bem como suas componentes perpendicular e paralela às frentes. Ao longo de 8 anos mais 96.000 frentes oceânicas foram detectadas, co-localizadas com a disponibilidade de dados de vento dando origem a 40.000 composições. O sistema de coordenadas dessas composições foi rotacionado para que as frentes oceânicas tivessem a mesma orientação. Nós empilhamos as composições em um arranjo 3D e foram obtidas médias das circulações atmosféricas induzidas. As perturbações médias obtidas indicaram que há convergência do vento quando este sopra do lado quente para o lado frio da frente com a frenagem do escoamento. De forma oposta, há divergência e aceleração do vento quando este sopra no sentido oposto. Nós identificamos alterações locais no rotacional do campo de vento capazes de induzir o bombeamento de Ekman no oceano. Esse processo pode gerar mecanismos de retroalimentação no sistema. Nossos resultados corroboram o de diversos estudos sobre o tema presentes literatura. / The southwest Atlantic circulation patterns are characterized by a diversity of water masses. The presence of currents associated with the subtropical gyre and the northward incursion of Antarctic Circumpolar Current (ACC) determine extensive regions of strong sea surface temperature gradient (SST). At the same time, mesoscale circulations generate intense local gradients, or reinforce the large-scale contrast. Consequently, oceanic fronts are formed along these gradients on different scales. When the wind blows over these fronts, the fluids exchange heat and momentum, and that changes their dynamic and thermodynamic properties. In this work we aim to characterize the changes in the surface wind field that might be attributed to these exchanges. To do it, a frontal detection algorithm was applied to the SST field derived from OSTIA set. We selected situations of synoptic homogeneous atmospheric flow and calculated the divergent and rotational wind, in addition to its perpendicular and parallel components to the oceanic fronts. We used wind measurements recorded by the QuickSCAT scatterometer along the frontal zones. More than 96,000 oceanic fronts were detected along 8 years of data. We matched them to available wind data and formed more than 40,000 SST-WIND compositions. The coordinate system of these compositions was rotated so that all oceanic fronts have the same horizontal orientation. We piled up the compositions in a 3D array and the temporal mean of the induced circulations was calculated. The average disturbance obtained indicated that there is wind convergence when it blows from the warm side of the front to the cold side because the flow is slowed down. Conversely, there is wind divergence when it blows in the opposite direction due to speeding up flow. We identified local changes in wind field curl capable of inducing Ekman pumping over the ocean. This process can generate feedback mechanisms in the system. Our results were consistent with the literature.

Os padrões de circulação do Atlântico Sudoeste são caracterizados por uma diversidade de massas de água. A presença das correntes associadas ao giro subtropical e a incursão para norte da Corrente Circumpolar Antártica (CCA) determinam extensas regiões de largo gradiente de Temperatura da Superfície do Mar (TSM). Ao mesmo tempo, circulações de mesoescala geram intensos gradientes setorizados, ou reforçam o contraste de larga-escala. Consequentemente, frentes oceânicas de diferentes escalas são formadas ao longo desses gradientes. Quando o vento sopra sobre essas frentes, os fluidos trocam calor e momentum alterando suas propriedades dinâmicas e termodinâmicas. Nesse trabalho visamos caracterizar as alterações no campo de vento superficial que podem ser atribuídas a essas trocas. Para isso, foi aplicado um algoritmo de detecção de frentes em campos de Temperatura da Superfície do Mar (TSM) derivados do conjunto OSTIA. Em situações de escoamento atmosférico sinótico homogêneo, foram calculados o divergente e rotacional do vento medido pelo escaterômetro QuickSCAT ao longo das zonas frontais, bem como suas componentes perpendicular e paralela às frentes. Ao longo de 8 anos mais 96.000 frentes oceânicas foram detectadas, co-localizadas com a disponibilidade de dados de vento dando origem a 40.000 composições. O sistema de coordenadas dessas composições foi rotacionado para que as frentes oceânicas tivessem a mesma orientação. Nós empilhamos as composições em um arranjo 3D e foram obtidas médias das circulações atmosféricas induzidas. As perturbações médias obtidas indicaram que há convergência do vento quando este sopra do lado quente para o lado frio da frente com a frenagem do escoamento. De forma oposta, há divergência e aceleração do vento quando este sopra no sentido oposto. Nós identificamos alterações locais no rotacional do campo de vento capazes de induzir o bombeamento de Ekman no oceano. Esse processo pode gerar mecanismos de retroalimentação no sistema. Nossos resultados corroboram o de diversos estudos sobre o tema presentes literatura. / The southwest Atlantic circulation patterns are characterized by a diversity of water masses. The presence of currents associated with the subtropical gyre and the northward incursion of Antarctic Circumpolar Current (ACC) determine extensive regions of strong sea surface temperature gradient (SST). At the same time, mesoscale circulations generate intense local gradients, or reinforce the large-scale contrast. Consequently, oceanic fronts are formed along these gradients on different scales. When the wind blows over these fronts, the fluids exchange heat and momentum, and that changes their dynamic and thermodynamic properties. In this work we aim to characterize the changes in the surface wind field that might be attributed to these exchanges. To do it, a frontal detection algorithm was applied to the SST field derived from OSTIA set. We selected situations of synoptic homogeneous atmospheric flow and calculated the divergent and rotational wind, in addition to its perpendicular and parallel components to the oceanic fronts. We used wind measurements recorded by the QuickSCAT scatterometer along the frontal zones. More than 96,000 oceanic fronts were detected along 8 years of data. We matched them to available wind data and formed more than 40,000 SST-WIND compositions. The coordinate system of these compositions was rotated so that all oceanic fronts have the same horizontal orientation. We piled up the compositions in a 3D array and the temporal mean of the induced circulations was calculated. The average disturbance obtained indicated that there is wind convergence when it blows from the warm side of the front to the cold side because the flow is slowed down. Conversely, there is wind divergence when it blows in the opposite direction due to speeding up flow. We identified local changes in wind field curl capable of inducing Ekman pumping over the ocean. This process can generate feedback mechanisms in the system. Our results were consistent with the literature.

In this thesis, three improved analysis techniques for scatterometer wind estimation are presented. These techniques build upon previous methods that help validate scatterometer data. This thesis examines the theory connecting the 1D and 2D kinetic energy spectra and uses QuikSCAT data to measure the 2D kinetic energy spectrum of ocean winds. The measured 2D kinetic energy spectrum is compared to the traditional 1D kinetic energy spectrum. The relationship between the 2D kinetic energy spectra and the 1D kinetic energy spectra confirms findings from previous studies that ocean winds modeled in 2D are isotropic and nondivergent. The 1D and 2D kinetic energy spectra also confirm the known conclusion that the zonal and meridional components of ocean winds are uncorrelated. Through simulation, the wind response function (WRF) is calculated for three different QuikSCAT processing algorithms. The WRF quantifies the contribution that the wind at each point of the surface makes to a given wind estimate. The spatial resolution of the different processing algorithms is estimated by their WRFs. The WRFs imply that the spatial resolution of ultrahigh resolution (UHR) processing is finer than the spatial resolution of conventional drop-in-the-bucket (DIB) processing; the spatial resolution of UHR processing is ~5-10 km while the spatial resolution of DIB slice processing is ~12-15 km and the spatial resolution of coarse resolution DIB egg processing is ~30 km. Simulation is used to analyze the effectiveness of various wind retrieval and ambiguity selection algorithms. To assist in the simulation, synthetic wind fields are created through extrapolating the 2D Fourier transform of a numerical weather prediction wind field. These synthetic wind fields are sufficiently realistic to evaluate ambiguity selection algorithms. The simulation employs the synthetic wind fields to compare wind estimation with and without direction interval retrieval (DIR) applied. Both UHR and DIB wind estimation processes are performed in the simulation and UHR winds are shown to resolve finer resolution wind features than DIB winds at the cost of being slightly noisier. DIR added to standard QuikSCAT UHR wind estimation drops the wind direction root-mean-squared error by ~10° to ~24.74° in the swath sweet spot.