Effects of Surfactants on the Generation of Sea Spray During Tropical Cyclones

Despite significant improvement in computational and observational capabilities, predicting intensity and intensification of major tropical cyclones remains a challenge. In 2017 Hurricane Maria intensified to a Category 5 storm within 24 hours, devastating Puerto Rico. In 2019 Hurricane Dorian, predicted to remain tropical storm, unexpectedly intensified into a Category 5 storm and destroyed the Bahamas. The official forecast and computer models were unable to predict rapid intensification of these storms. One possible reason for this is that key physics, including microscale processes at the air-sea interface, are poorly understood and parameterized in existing forecast models. Under tropical cyclones, the air-sea interface becomes a multiphase environment involving bubbles, foam, and spray. The presence of surface-active materials (surfactants) alters these microscale processes in an unknown way that may affect tropical cyclone intensity. The current understanding of the relationship between surfactants, wind speed, and sea spray generation remains limited. Here we show that surfactants significantly affect the generation of sea spray, which provides some of the fuel for tropical cyclones and their intensification. A computational fluid dynamics (CFD) model was used to simulate spray radii distributions starting from a 100 micrometer radius as observed in laboratory experiments at the University of Miami Rosenstiel School of Marine and Atmospheric Sciences SUSTAIN facility. Results of the model were verified with laboratory experiments and demonstrate that surfactants increase spray generation by 34% under Category 1 tropical cyclone conditions (~40 m s-1 wind). In the model, we simulated Category 1 (4 Nm-2 wind stress), 3 (10 Nm-2 wind stress), and 5 (20 Nm-2 wind stress) conditions and found that surfactants increased spray generation by 20-34%. The global distribution of bio-surfactants on the earth is virtually unknown at this point. Satellite oceanography may be a useful tool to identify the presence of surfactants in the ocean in relation to tropical cyclones. Color satellite imagery of chlorophyll concentration, which is a proxy for surfactants, may assist in identifying surfactant areas that tropical cyclones may pass over. Synthetic aperture radar imagery also may assist in tropical cyclone prediction in areas of oil spills, dispersants, or surfactant slicks. We anticipate that bio-surfactants affect heat, energy, and momentum exchange through altered size distribution and concentration of sea spray, with consequences for tropical cyclone intensification or decline, particularly in areas of algal blooms and near coral reefs, as well as in areas affected by oil spills and dispersants

A Study of Types of Sensors used in Remote Sensing

Of late, the science of Remote Sensing has been gaining a lot of interest and attention due to its wide variety of applications. Remotely sensed data can be used in various fields such as medicine, agriculture, engineering, weather forecasting, military tactics, disaster management etc. only to name a few. This article presents a study of the two categories of sensors namely optical and microwave which are used for remotely sensing the occurrence of disasters such as earthquakes, floods, landslides, avalanches, tropical cyclones and suspicious movements. The remotely sensed data acquired either through satellites or through ground based- synthetic aperture radar systems could be used to avert or mitigate a disaster or to perform a post-disaster analysis

A Study of Types of Sensors used in Remote Sensing

Of late, the science of Remote Sensing has been gaining a lot of interest and attention due to its wide variety of applications. Remotely sensed data can be used in various fields such as medicine, agriculture, engineering, weather forecasting, military tactics, disaster management etc. only to name a few. This article presents a study of the two categories of sensors namely optical and microwave which are used for remotely sensing the occurrence of disasters such as earthquakes, floods, landslides, avalanches, tropical cyclones and suspicious movements. The remotely sensed data acquired either through satellites or through ground based- synthetic aperture radar systems could be used to avert or mitigate a disaster or to perform a post-disaster analysis

Rôle de la perturbation par le vent dans les forêts tropicales via un modèle dynamique de végétation et l'observation satellitaire

Les perturbations naturelles ont une influence importante sur la structure, la composition et le fonctionnement des forêts tropicales et un rôle dans la régulation des cycles biogéochimiques. La fréquence et l'intensité des perturbations naturelles sont modifiés par les changements climatiques : une meilleure connaissance de leur mécanisme d'action est nécessaire pour prédire les conséquences de cette modification. La modélisation permet d'évaluer le rôle de chacun des processus écologiques et leur lien avec les facteurs environnementaux. Les outils de la télédétection nous informent sur la structure et le fonctionnement des forêts à large échelle, et peuvent être utiles à la calibration et la validation des modèles de végétation. Dans cette thèse, j'ai employé ces deux approches pour examiner comment les forêts tropicales sont façonnées par les perturbations naturelles, notamment le vent, qui est un facteur majeur de perturbation dans de nombreuses régions tropicales. Dans un premier temps, j'ai évalué la transférabilité d'un modèle individu-centré et spatialement explicite via un test de sensibilité et la calibration des paramètres globaux. Le modèle prédit correctement la structure de la forêt sur deux sites contrastés, et sa réponse est cohérente avec les variations du forçage climatique. La calibration d'un petit nombre de paramètres clés a été nécessaire, dont notamment celui qui contrôle la mortalité. Pour étudier la sensibilité du modèle à la mortalité, j'ai mis en œuvre un module de dégâts de vents fondé sur les principes biophysiques et couplé avec la vitesse de vent, afin de modéliser les réponses de la forêt aux évènements de vent extrême. Avec l'augmentation du niveau de perturbation, la hauteur de la canopée diminue de manière constante mais la biomasse montre une réponse non-linéaire. L'intensité du vent a un fort impact sur la hauteur de la canopée et la biomasse, mais pas la fréquence des évènements de vent extrême. Finalement, j'ai testé si les données radar des satellites Sentinel-1 pourraient servir à détecter les trouées dues aux perturbations naturelles en Guyane française. Les données Sentinel-1 détectent plus de trouées naturelles au-dessus de 0.2 ha que les données satellitaires optiques, et elles présentent un patron spatial cohérent avec les images optiques. Le niveau de perturbation ne varie pas en fonction de l'altitude. Nous avons trouvé plus de perturbations pendant les saisons sèches, ce qui pourrait être dû à la réponse tardive des précipitations plutôt qu'à la réponse directe de la sècheresse. En conclusion, cette thèse démontre que l'intégration entre la modélisation et la télédétection éclairent les effets des perturbations naturelles sur les forêts tropicales. Les résultats qui en découlent peuvent servir à étudier d'autres types de perturbations et leurs interactions sur une large échelle.Natural disturbances have an important influence on the structure, composition and functioning of tropical forests and a role in the regulation of biogeochemical cycles. The frequency and intensity of natural disturbances are modified by climate change: a better knowledge of their mechanism of action is necessary to predict the consequences of this modification. Modeling allows us to evaluate the role of each of the ecological processes and their link with environmental factors. Remote sensing tools inform us about the structure and functioning of forests at large scales, and can be useful for the calibration and validation of vegetation models. In this thesis, I employed both approaches to examine how tropical forests are shaped by natural disturbances, particularly wind, which is a major disturbance factor in many tropical regions. First, I evaluated the transferability of a spatially explicit, individual-based model via sensitivity testing and calibration of global parameters. The model correctly predicts forest structure at two contrasting sites, and its response is consistent with variations in climate forcing. Calibration of a small number of key parameters was required, including the parameter controlling mortality and crown allometry. To investigate the sensitivity of the model to mortality, I implemented a wind damage module based on biophysical principles and coupled with wind speed to model forest responses to extreme wind events. With increasing disturbance level, canopy height decreased steadily but biomass showed a non-linear response. Wind intensity had a strong impact on canopy height and biomass, but not the frequency of extreme wind events. Finally, I tested whether radar data from Sentinel-1 satellites could be used to detect gaps due to natural disturbances in French Guiana. The Sentinel-1 data detected more natural gaps above 0.2 ha than the optical satellite data, and they showed a spatial pattern consistent with the optical images. The level of disturbance did not vary with altitude. We found more disturbance during dry seasons, which could be due to the delayed response of precipitation rather than the direct response of drought. In conclusion, this thesis demonstrates that the integration between modeling and remote sensing sheds light on the effects of natural disturbances on tropical forests. The resulting results can be used to study other types of disturbances and their interactions on a large scale

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

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

Ocean Remote Sensing with Synthetic Aperture Radar

The ocean covers approximately 71% of the Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. The Synthetic Aperture Radar (SAR) can image the ocean surface in all weather conditions and day or night. SAR remote sensing on ocean and coastal monitoring has become a research hotspot in geoscience and remote sensing. This book—Progress in SAR Oceanography—provides an update of the current state of the science on ocean remote sensing with SAR. Overall, the book presents a variety of marine applications, such as, oceanic surface and internal waves, wind, bathymetry, oil spill, coastline and intertidal zone classification, ship and other man-made objects’ detection, as well as remotely sensed data assimilation. The book is aimed at a wide audience, ranging from graduate students, university teachers and working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the state-of-the-art technologies in the field of SAR Oceanography

Earth resources: A continuing bibliography with indexes (issue 61)

This bibliography lists 606 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1 and March 31, 1989. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors, and economic analysis

Potential Effect of Bio-Surfactants on Sea Spray Generation in Tropical Cyclone Conditions

Despite significant improvement in computational and observational capabilities, predicting intensity and intensification of major tropical cyclones remains a challenge. In 2017 Hurricane Maria intensified to a Category 5 storm within 24 h, devastating Puerto Rico. In 2019 Hurricane Dorian, predicted to remain tropical storm, unexpectedly intensified into a Category 5 storm and destroyed the Bahamas. The official forecast and computer models were unable to predict rapid intensification of these storms. One possible reason for this is that key physics, including microscale processes at the air-sea interface, are poorly understood and parameterized in existing forecast models. Here we show that surfactants significantly affect the generation of sea spray, which provides some of the fuel for tropical cyclones and their intensification, but also provides some of the drag that limits intensity and intensification. Using a numerical model verified with a laboratory experiment, which predicts spray radii distribution starting from a 100 μm radius, we show that surfactants increase spray generation by 20–34%. We anticipate that bio-surfactants affect heat, energy, and momentum exchange through altered size distribution and concentration of sea spray, with consequences for tropical cyclone intensification or decline, particularly in areas of algal blooms and near coral reefs, as well as in areas affected by oil spills and dispersants