867 research outputs found

    Facing the storm:Assessing global storm tide hazards in a changing climate

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    Coastal flooding is one of the most frequent natural hazards around the globe and can have devastating societal impacts. It is caused by extreme storm tides, which are composed of storm surges and tides, on top of mean sea levels. Due to socio-economic developments in the world’s coastal zones, the impacts of coastal floods have increased in recent decades. In addition, projected changes in the frequency and intensity of storms, as well as sea level rise due to climate change are expected to increase the coastal flood hazard. These trends show that it is crucial to further improve coastal flood hazard assessments to support coastal flood management. A lack of understanding of the influence of tropical cyclones (TCs) on storm tide level return periods (RPs) currently prevails. Available meteorological data does not adequately capture the structure of TCs, and the temporal length of this data is too short to accurately compute RPs because TCs are low-probability events. Existing large scale coastal flood hazard assessments assume an infinite flood duration and do not capture the physical hydrodynamic processes that drive coastal flooding. Furthermore, future changes in the frequency and intensity of TCs and extratropical cyclones (ETCs) are often neglected in coastal flood hazard assessments. As such, the goal of this thesis is to improve global storm tide modelling through the better representation of TC-related extremes and enable dynamic flood mapping in both current and future climates. The research in this thesis contributes to ongoing efforts in the coastal risk community to better understand coastal flood hazards and risks on a global scale. The COAST-RP dataset can help identify hotspot regions most prone to coastal flooding. Such information can then be used to determine where more detailed local-scale coastal flood hazard assessments are most needed. Combining data from COAST-RP with the HGRAPHER method allows us to move away from planar towards more advanced dynamic inundation methods. This will improve the accuracy of the coastal flood hazard maps. Lastly, the developed TC intensity Δ method that is applicable to different kinds of future climate TC datasets opens the door to studying the future intensity of TCs and corresponding storm surges by placing them in a future climate

    Satellite remote sensing of surface winds, waves, and currents: Where are we now?

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    This review paper reports on the state-of-the-art concerning observations of surface winds, waves, and currents from space and their use for scientific research and subsequent applications. The development of observations of sea state parameters from space dates back to the 1970s, with a significant increase in the number and diversity of space missions since the 1990s. Sensors used to monitor the sea-state parameters from space are mainly based on microwave techniques. They are either specifically designed to monitor surface parameters or are used for their abilities to provide opportunistic measurements complementary to their primary purpose. The principles on which is based on the estimation of the sea surface parameters are first described, including the performance and limitations of each method. Numerous examples and references on the use of these observations for scientific and operational applications are then given. The richness and diversity of these applications are linked to the importance of knowledge of the sea state in many fields. Firstly, surface wind, waves, and currents are significant factors influencing exchanges at the air/sea interface, impacting oceanic and atmospheric boundary layers, contributing to sea level rise at the coasts, and interacting with the sea-ice formation or destruction in the polar zones. Secondly, ocean surface currents combined with wind- and wave- induced drift contribute to the transport of heat, salt, and pollutants. Waves and surface currents also impact sediment transport and erosion in coastal areas. For operational applications, observations of surface parameters are necessary on the one hand to constrain the numerical solutions of predictive models (numerical wave, oceanic, or atmospheric models), and on the other hand to validate their results. In turn, these predictive models are used to guarantee safe, efficient, and successful offshore operations, including the commercial shipping and energy sector, as well as tourism and coastal activities. Long-time series of global sea-state observations are also becoming increasingly important to analyze the impact of climate change on our environment. All these aspects are recalled in the article, relating to both historical and contemporary activities in these fields

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    BDS GNSS for Earth Observation

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    For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earth’s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earth’s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earth’s surface in a certain scan time (properly called ’temporal resolution’), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour l’Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community

    Ocean carbon from space: Current status and priorities for the next decade

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    This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data for Fig. 1a were generated from a free Scopus (https://www.scopus.com/) search of the terms "Ocean carbon satellite" (using All fields) in March 2022. Data from Fig. 1b and 1c were generated from the workshop registration and are available within the figure (participation number, geographical representation and gender split).The ocean plays a central role in modulating the Earth’s carbon cycle. Monitoring how the ocean carbon cycle is changing is fundamental to managing climate change. Satellite remote sensing is currently our best tool for viewing the ocean surface globally and systematically, at high spatial and temporal resolutions, and the past few decades have seen an exponential growth in studies utilising satellite data for ocean carbon research. Satellite-based observations must be combined with in-situ observations and models, to obtain a comprehensive view of ocean carbon pools and fluxes. To help prioritise future research in this area, a workshop was organised that assembled leading experts working on the topic, from around the world, including remote-sensing scientists, field scientists and modellers, with the goal to articulate a collective view of the current status of ocean carbon research, identify gaps in knowledge, and formulate a scientific roadmap for the next decade, with an emphasis on evaluating where satellite remote sensing may contribute. A total of 449 scientists and stakeholders participated (with balanced gender representation), from North and South America, Europe, Asia, Africa, and Oceania. Sessions targeted both inorganic and organic pools of carbon in the ocean, in both dissolved and particulate form, as well as major fluxes of carbon between reservoirs (e.g., primary production) and at interfaces (e.g., air-sea and land–ocean). Extreme events, blue carbon and carbon budgeting were also key topics discussed. Emerging priorities identified include: expanding the networks and quality of in-situ observations; improved satellite retrievals; improved uncertainty quantification; improved understanding of vertical distributions; integration with models; improved techniques to bridge spatial and temporal scales of the different data sources; and improved fundamental understanding of the ocean carbon cycle, and of the interactions among pools of carbon and light. We also report on priorities for the specific pools and fluxes studied, and highlight issues and concerns that arose during discussions, such as the need to consider the environmental impact of satellites or space activities; the role satellites can play in monitoring ocean carbon dioxide removal approaches; economic valuation of the satellite based information; to consider how satellites can contribute to monitoring cycles of other important climatically-relevant compounds and elements; to promote diversity and inclusivity in ocean carbon research; to bring together communities working on different aspects of planetary carbon; maximising use of international bodies; to follow an open science approach; to explore new and innovative ways to remotely monitor ocean carbon; and to harness quantum computing. Overall, this paper provides a comprehensive scientific roadmap for the next decade on how satellite remote sensing could help monitor the ocean carbon cycle, and its links to the other domains, such as terrestrial and atmosphere.European Space AgencySimons FoundationUK National Centre for Earth Observation (NCEO)UKRIAtlantic Meridional Transect ProgrammeSwiss National Science Foundatio

    Explotación sinérgica de datos multiespectrales y radar para la estimación de variables biofísicas de la vegetación mediante tecnologías de sensoramiento remoto

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    Las variables biofísicas de la vegetación (VBV) son indicadores directos del crecimiento y productividad de los cultivos. Los sistemas de observación de la Tierra (EO–Earth observation) presentan oportunidades sin precedentes para el monitoreo de las variables biofísicas del trigo. Sentinel–2 (S2) es una constelación de satélites que forma parte de las misiones Sentinel del programa Copernicus de EO. El período de revisita, así como su resolución espacial y espectral, han convertido a S2 en un sistema de EO trascendental para el monitoreo de VBV. Los sistemas ópticos de EO se ven limitados con frecuencia por las condiciones climáticas tales como nubosidad o precipitaciones. En este sentido, la tecnología radar, presenta nuevas oportunidades para el monitoreo de VBV que deben explorarse en profundidad. Sentinel–1 (S1) es una constelación radar de la familia Sentinel. Debido a la complejidad de la interacción de la señal radar con las superficies cultivadas y al ruido aditivo inherente de speckle, la estimación de VBV con tecnología radar aún sigue siendo un desafío. El objetivo de esta tesis doctoral es desarrollar modelos de estimación de variables biofísicas del trigo, en una zona irrigada de cultivo intensivo al sureste de Argentina, basados en medidas in situ de la vegetación, a partir de: i) datos multiespectrales de S2; ii) datos radar de S1; y iii) la sinergia S1 & S2. Para abordar la problemática planteada, se desarrollaron en primer lugar, modelos de estimación del índice de área foliar, del contenido de clorofila de la cubierta vegetal y del contenido de agua del trigo, utilizando una base de datos multitemporal de VBV tomadas in situ, algoritmos de aprendizaje automático, una base de datos de espectros de reflectividad bidireccional de la vegetación simulados con un modelo de transferencia radiativa y datos multiespectrales de S2. Se obtuvieron modelos híbridos de estimación de estas VBV que se ajustaron con alta precisión a los datos de campo y se logró reconstruir con éxito la curva fenológica del cultivo de trigo. En segundo lugar, se implementó un modelo de estimación de LAI basado en datos radar de S1 adquiridos en diferentes geometrías de adquisición. Se probó que la estructura tridimensional de la vegetación cuando es observada desde ángulos de incidencia local diferentes proporciona información muy valiosa que puede ser utilizada para mejorar los modelos existentes. Por último, se desarrolló una estrategia de fusión de datos de S1 & S2 para reconstruir series temporales de VWC. Se aplicaron varios modelos de procesos Gaussianos de salidas múltiples para analizar la correlación cruzada existente, en el dominio de la frecuencia, entre los canales ópticos y radar. La combinación sinérgica de datos radar y ópticos mostró ser un novedoso enfoque para abordar el monitoreo de variables biofísicas del trigo en regiones intensamente cultivadas con frecuente nubosidad

    Determinants of growth, biomass and productivity of Mediterranean forests under different levels of aridity and ecological scales

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    El Sur de la Península Ibérica, según los diferentes escenarios pronosticados, se tornará cada vez más árido, lo cual afectará al funcionamiento de los ecosistemas. Sin embargo, todavía no se conoce en detalle cómo esto puede afectar a los bosques y su interacción con otros factores abióticos y bióticos. Por ese motivo es necesario entender cuál es la respuesta fisiológica que la aridez puede provocar en la vegetación, y hasta qué punto puede afectar el crecimiento de los árboles, la biomasa y la producción de los bosques mediterráneos. Para analizar el impacto generalizado de los factores abióticos y bióticos sobre el funcionamiento del ecosistema es necesario un diseño sistemático a diferentes escalas ecológicas (desde el nivel de individuo hasta el nivel de ecosistema). La presente tesis tuvo por objetivo general entender cómo los ecosistemas forestales pueden responder ante el aumento de la aridez. Para eso fueron estudiadas las respuestas ecológicas de los ecosistemas forestales en un gradiente de aridez a varias escalas utilizando la información del inventario forestal nacional (IFN). Inicialmente, se analizó la respuesta de los rasgos funcionales foliares y de madera, la tasa de crecimiento relativo a nivel de individuo, y la biomasa y la producción forestal a nivel de parcela de especies forestales claves del mediterráneo como Pinus halepensis, Pinus pinaster, Quercus faginea y Quercus ilex. Una vez modelada la biomasa y la producción forestal, se proyectaron los posibles escenarios climáticos frente a un hipotético aumento de la aridez. Además, se estudió el impacto de la aridez sobre la diversidad taxonómica y funcional del matorral que acompaña a los bosques de Q. ilex. Por último, se analizó el impacto de la aridez sobre la fenología de las especies forestales más abundantes en el sur peninsular usando series temporales de NDVI (índice de vegetación normalizado). Los resultados mostraron una respuesta significativa de rasgos funcionales como la densidad de la hoja y madera (LD y WD) frente a la aridez, los nutrientes y textura del medio edáfico para el modelo del conjunto de especies estudiadas. En los modelos específicos, la aridez y el contenido de arcilla explicaron significativamente el peso foliar específico (LMA), el grosor de la hoja (LT) y la densidad de la madera (WD) en P. halepensis, Q. faginea y Q. ilex. Por otro lado, la tasa de crecimiento relativo (RGR) no respondió a factores abióticos, pero se relacionó negativamente con el tamaño del individuo. A escala local, la biomasa forestal del conjunto de especies mostró relaciones con el área foliar (LA), el contenido de arcilla y el tamaño medio de los árboles. La aridez mostró relevancia para algunos de los modelos de biomasa específicos (Q. ilex) así como a escala regional en toda Andalucía (6924 parcelas) donde el NDVI y la densidad forestal también se mostraron significativas. La producción forestal a escala local respondió positivamente al medio edáfico (nutrientes y contenido en arcilla), RGR, biomasa media de los árboles y densidad forestal. A 3 escala regional la aridez afectó negativamente en la mayoría de los modelos de producción forestal. Las proyecciones de la aridez para los diferentes escenarios climáticos mostraron reducciones considerables de biomasa y producción forestal. La composición y riqueza taxonómica y funcional del matorral también se vio afectada por la aridez y el contenido de arcilla. En lugares más áridos, la comunidad se compone por especies más xerófilas, con valores elevados de LMA. La fenología de las especies forestales respondió a la aridez mostrando un retraso del inicio y final de la estación (SOS y EOS respectivamente) en lugares más áridos. La duración del ciclo fenológico (LOS) mostró gran variabilidad sin una respuesta homogénea frente a la aridez. El análisis temporal de las métricas fenológicas no mostró relación con la aridez, aun existiendo un aumento de las temperaturas medias en el tiempo. La mayoría de las especies reflejaron resiliencia frente a los eventos climáticos extremos con un incremento en NDVI (reverdecimiento) a lo largo del tiempo en la mayoría de las especies. En conclusión, la aridez y el medio edáfico afectan al comportamiento fisiológico de la vegetación y la composición del matorral, reduciendo la biomasa forestal y su producción. Esto puede originar cambios en la estructura y funcionalidad del ecosistema poniendo en riesgo su estabilidad y subsistencia a largo plazo.The South of the Iberian Peninsula is expected to become increasingly arid under different forecast scenarios, potentially affecting the functioning of ecosystems. However, the specific impacts of aridity on forests and its interactions with abiotic and biotic factors are not fully understood. Therefore, it is necessary to investigate the physiological responses of vegetation to aridity and how it can affect tree growth, biomass, and forest production, across different ecological scales from individual to ecosystem. The main objective of this thesis was to understand how forest ecosystems can respond to increased aridity by studying ecological responses at various scales along an aridity gradient, using information from the Spanish National Forest Inventory (SNFI). The study focused on key Mediterranean forest species, including Pinus halepensis, Pinus pinaster, Quercus faginea, and Quercus ilex, and examined their foliar and wood functional traits, relative growth rate at the individual level, biomass and forest productivity at the plot level. The study also modeled the predicted change in biomass and forest productivity under different possible climate scenarios with hypothetical increases in aridity. In addition, the study investigated the impact of aridity on the taxonomic and functional diversity of shrub communities accompanying Q. ilex forests and analyzed the phenology of the most abundant forest species in the south of the peninsula using NDVI time series. The results showed that aridity, as alongside soil nutrients and texture, significantly affected functional traits such as leaf and wood density (LD and WD) across the set of species studied. For specific models, aridity and clay content were significant factors for leaf specific weight (LMA), leaf thickness (LT), and wood density (WD) in P. halepensis, Q. faginea, and Q. ilex. On the other hand, the relative growth rate (RGR) did not respond to abiotic factors but was negatively related to the size of the individual. At the local scale, forest biomass of the set of species showed relationships with the leaf area (LA), clay content, and average tree size. Aridity significantly explained some specific biomass models (Q. ilex) as well as at a regional scale throughout Andalusia (6924 plots), where NDVI and forest density were also the main drivers. Forest productivity at a local scale responded positively to the edaphic environment (nutrients and clay content), RGR, average tree biomass, and forest density, while aridity negatively affected most forest productivity models at a regional scale. Projections of aridity under different climate scenarios showed considerable reductions in biomass and forest productivity. The composition, taxonomic, and functional diversity of shrub communities were also affected by aridity and clay content, with more xerophytic species and higher LMA values in more arid places. The phenology of forest species responded to aridity, showing a delay in the beginning and end of the season (SOS and EOS, respectively) in more arid places, but with great variability in the length of the phenological cycle (LOS) without a homogeneous response to aridity. The temporal analysis of phenological metrics did not show a relationship with aridity, despite an increase in average temperatures over time. Overall, the study revealed that aridity and the edaphic environment can affect the physiological behavior of vegetation and the composition of shrub communities, resulting in reduced forest biomass and production and potentially altering the structure and functionality of ecosystems, with implications for its stability and long-term survival

    Variation of soil suction and application of remote sensing in evaluating unsaturated soil behavior within vadose zone

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    Moisture movement in pavements and road embankments is receiving more attention in pavement and geotechnical engineering. Water from rainfall is the primary source of moisture in soils. Following a rainstorm event, large quantities of moisture can be absorbed by the soil when the water migrates into the soil mass. The passage of moisture has an impact on the mechanical performance and functionality of the pavement infrastructure. When the pavement infrastructure is built on expansive soils, water flow can cause damage to pavements due to the swelling and shrinking of expansive soils through adsorption and desorption of moisture. Such damage can result in severe financial loss; in fact, the estimated yearly cost of damage from expanding soil problems is $2.3 billion in the United States. Oklahoma contains large expanses of medium to highly expansive clays. The state's largest cities are located in these areas, and significant and costly highway systems have been built to support the population density. These areas have relatively high average annual precipitation, which worsens the expansive clay problems. The swelling or shrinking of expansive clays causes distortion and cracking in pavements, reducing pavement service life. Thus, it is critical to understand how water moves in road embankments of expansive soils subjected to seasonal rainfall and to predict the vertical movement of pavements built on expansive soils. This study used Oklahoma Mesonet measurements to develop a data-driven statistical model for estimating soil diffusivity and soil suction in order to predict the movement of expansive soils over time. The first component of the study used unsupervised learning and a nonlinear least squares model to estimate soil diffusivity. The second component of the study presents a mechanistic-numerical model for predicting equilibrium suction that considers the diffusion coefficient's effects and uses surface field suction measurements. The final component of the study utilized Interferometric Synthetic Aperture Radar (InSAR) technique for effective displacement monitoring using time series of SAR data. The study investigated the performance of moisture barriers on two state highways in Oklahoma, where expansive soils are a major problem
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