112 research outputs found

    Azimuthal Dependence of GNSS‐R Scattering Cross‐Section in Hurricanes

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    Global Navigation Satellite System‐Reflectometry (GNSS‐R) measurements of the ocean surface are sensitive to roughness scales ranging from a few cms to several kms. Inside a hurricane the surface roughness changes drastically due to varying sea age and fetch length conditions and complex wave‐wave interactions caused by its cyclonic rotation and translational motion. As a result, the relationship between the surface roughness at different scale sizes becomes azimuthally dependent, as does the relationship between scattering cross‐section and wind speed as represented by a Geophysical Model Function (GMF). In this work, the impact of this azimuthal variation on the scattering cross‐section is assessed. An empirical GMF is constructed using measurements by the NASA CYclone GNSS (CYGNSS) matched to HWRF reanalysis surface winds for 19 hurricanes in 2017 and 2018. The analysis reveals a 2–8% variation in scattering cross‐section due to azimuthal location, and the magnitude of the azimuthal dependence is found to grow with wind speed.Plain Language SummaryGlobal Navigation Satellite System‐Reflectometry (GNSS‐R) is a technique of studying reflected GPS signals to extract useful information about the surface. CYGNSS is the first of its kind GNSS‐R constellation mission selected by NASAs earth venture program. The goal of the mission is to understand inner core processes in hurricanes by making accurate surface wind speed measurements there. Wind speed at the surface is determined using a GMF that maps the reflection measurement to a wind speed. Due to the complex nature of sea state and wave interactions inside a hurricane, measured scattering cross‐section depends on the azimuthal location of the measurement inside the hurricane system. A modified GMF is proposed here that accounts for the azimuthal dependence. The model is developed by matching up CYGNSS measurements to hurricane winds estimated by the NOAA HWRF model for 19 hurricanes during 2017 and 2018. The new GMF accounts for a 2–8% variation in the measurements due to azimuthal location which increases with wind speed.Key PointsAzimuthal variations of GNSS‐R scattering cross‐section in hurricanes are modeled with sinusoidal harmonicsThe azimuthal harmonics explain 2–8% of the overall variation in scattering cross‐sectionThe magnitude of the azimuthal harmonics increases with increasing wind speedPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156153/2/jgrc24060.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156153/1/jgrc24060_am.pd

    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

    Remote Sensing of Tropical Cyclones: Applications from Microwave Radiometry and Global Navigation Satellite System Reflectometry

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    Tropical cyclones (TCs) are important to observe, especially over the course of their lifetimes, most of which is spent over the ocean. Very few in situ observations are available. Remote sensing has afforded researchers and forecasters the ability to observe and understand TCs better. Every remote sensing platform used to observe TCs has benefits and disadvantages. Some remote sensing instruments are more sensitive to clouds, precipitation, and other atmospheric constituents. Some remote sensing instruments are insensitive to the atmosphere, which allows for unobstructed observations of the ocean surface. Observations of the ocean surface, either of surface roughness or emission can be used to estimate ocean surface wind speed. Estimates of surface wind speed can help determine the intensity, structure, and destructive potential of TCs. While there are many methods by which TCs are observed, this thesis focuses on two main types of remote sensing techniques: passive microwave radiometry and Global Navigation Satellite System reflectometry (GNSS-R). First, we develop and apply a rain rate and ocean surface wind speed retrieval algorithm for the Hurricane Imaging Radiometer (HIRAD). HIRAD, an airborne passive microwave radiometer, operates at C-band frequencies, and is sensitive to rain absorption and emission, as well as ocean surface emission. Motivated by the unique observing geometry and high gradient rain scenes that HIRAD typically observes, a more robust rain rate and wind speed retrieval algorithm is developed. HIRAD’s observing geometry must be accounted for in the forward model and retrieval algorithm, if high rain gradients are to be estimated from HIRAD’s observations, with the ultimate goal of improving surface wind speed estimation. Lastly, TC science data products are developed for the Cyclone Global Navigation Satellite System (CYGNSS). The CYGNSS constellation employs GNSS-R techniques to estimate ocean surface wind speed in all precipitating conditions. From inputs of CYGNSS level-2 wind speed observations and the storm center location, a variety of products are created: integrated kinetic energy, wind radii, radius of maximum wind speed, and maximum wind speed. These products provide wind structure and intensity information—valuable for situational awareness and science applications.PHDAtmospheric, Oceanic & Space ScienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137109/1/marygm_1.pd

    Investigating the Sensitivity of Spaceborne GNSS-R Measurements to Ocean Surface Winds and Rain

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    Earth remote sensing using reflected Global Navigation Satellite System (GNSS) signals is an emerging trend, especially for ocean surface wind measurements. GNSS-Reflectometry (GNSS-R) measurements of ocean surface scattering cross section are directly related to the surface roughness at scale sizes ranging from small capillary waves to long gravity waves. These roughness scales are predominantly due to swell, surface winds and other meteorological phenomena such as rain. In this study we are interested in understanding and characterizing the impact of these phenomena on GNSS-R signals in order to develop a better understanding of the geophysical parameters retrieved from these measurements. In the first part of this work, we look at GNSS-R measurements made by the NASA Cyclone Global Navigation Satellite System (CYGNSS) for developing an effective wind retrieval model function for GNSS-R measurements. In a fully developed sea state, the wind field has a constant speed and direction. In this case, a single Fully Developed Seas (FDS) Geophysical Model Function (GMF) is constructed which relates the scattering cross-section to the near surface wind speed. However, the sea age and fetch length conditions inside a hurricane are in general not consistent with a fully developed sea state. Therefore, a separate empirical Young Sea Limited Fetch (YSLF) GMF is developed to represent the conditions inside a hurricane. Also, the degree of under development of the seas is not constant inside hurricanes and conditions vary significantly with azimuthal location within the hurricane due to changes in the relative alignment of the storms forward motion and its cyclonic rotation. The azimuthal dependence of the scattering cross-section is modelled and a modified azimuthal YSLF GMF is constructed using measurements by CYGNSS over 19 hurricanes in 2017 and 2018. Next, we study the impact of rain on CYGNSS measurements. At L-band rain has a negligible impact on the transmitted signal in terms of path attenuation. However, there are other effects due to rain, such as changes in surface roughness and rain induced local winds, which can significantly alter the measurements. In this part of the study we propose a 3-fold rain model for GNSS-R signals which accounts for: 1) attenuation; 2) surface effects of rain; and 3) rain induced local winds. The attenuation model suggests a total of 96% or greater transmissivity at L-Band up to 30mm/hr of rain. A perturbation model is used to characterize the other two rain effects. It suggests that rain is accompanied by an overall reduction in the scattering cross-section of the ocean surface and, most importantly, this effect is observed only up to 15 m/s of surface winds, beyond which the gravity capillary waves dominate the scattering in the quasi-specular direction. This work binds together several rain-related phenomena and enhances our overall understanding of rain effects on GNSS-R measurements. Finally, one of the important objectives for the CYGNSS mission is to provide high quality global scale GNSS-R measurements that can reliably be used for ocean science applications. In this part of the work we develop a Neural Network based quality control filter for automated outlier detection for CYGNSS retrieved winds. The primary merit of the proposed Machine Learning (ML) filter is its ability to better account for interactions between the individual engineering, instrument and measurement conditions than can separate threshold quality flags for each one.PHDClimate and Space Sciences and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/166140/1/rajibala_1.pd

    KARAKTERISTIK POTENSI ANGIN SEBAGAI SUMBER ENERGI TERBARUKAN DI INDONESIA DARI DATA SATELIT REMOTE SENSING

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    Global warming, climate changes mostly associates with solar-renewable energy; however wind-energy potential has no detail reports in Indonesia. This study aims to mapping of characteristics and potential of wind as renewable-energy from long-term (1997-2009) satellite remote-sensing. Wind direction (WD), speed (WS) derives from microwave/ scatterometer sensor on satellite operational years as follows: ADEOS (1997), DMSP (1998-1999), AMI (1997-1999), QuikSCAT (1999- 2009). Data processed into 0.25o grid, monthly temporal resolution. The regional characteristics of WD/WS, seasonal and zonal-longitudinal reveals by statistic. Electrical energy derives from kinetic energy of turbine-blades per-unit time. Energy conversion uses power-curves and technical parameters of 1.50 and 3.40 MW (GE 1.5s, 3.4-137 models) onshore installations with 25km2 per point, 15% availability area. Result shows WS has low characteristics in Indonesian-waters (5deg), wind curve follows north-south hemisphere characteristics and crosses in April, October. The north-west, south-east monsoon shows clearly only on north-western of Java-Sumatra waters. WS has range of 0-25.20ms-1, average 6.64ms-1 with Std. 1.64ms-1. With these WS, generation of electrical energy has range from 104.0 to 2230.5 kWh per-point installation grid

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

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    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

     Ocean Remote Sensing with Synthetic Aperture Radar

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    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

    Global observations of aerosol-cloud-precipitation-climate interactions: Global observations of aerosol-cloud-precipitation-climateinteractions

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    Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects ofmeteorology fromthose of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing.Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing

    Earth Resources: A continuing bibliography with indexes, issue 33

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    This bibliography list 436 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System. 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, hydrology and water management, data processing and distribution sytems, instrumentation and sensors, and economic analysis

    Using ground-based fixed and mobile weather radars and numerical modeling to evaluate hurricane structure and dynamics at landfall

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    Hurricane observations during landfall in the United States have received relatively little attention in the research community compared to hurricanes observed over the open ocean. Aircraft-based observations using in situ and remotely sensed data have elucidated much about the structure and evolution of hurricanes. However, gathering high temporal (3-5 minutes) and high spatial (500-1000 m) resolution observations over contiguous spatial domains (e.g., 10,000 km2) is not possible with aircraft due to instrumentation limitations, operational missions, and required flight paths in hurricanes. Using ground-based fixed and mobile Doppler weather radars afford continuous observations of processes that not only affect landfall, but also offer comparison to aircraft observations of processes that occur over the open ocean. In addition, hurricane landfalls have generally been under sampled due to aircraft observations being relegated to the open ocean for crew and aircraft safety. The Shared Mobile Atmospheric Research and Teaching (SMART) Radars (SRs) are a pair of mobile Doppler, dual-polarization radars operated by the University of Oklahoma. Having sampled 14 landfalling tropical storms and hurricanes, datasets collected by the SRs likely provide key insight into hurricane dynamics and is the primary data source of this work. SR data, along with other fixed ground-based radars, in situ platforms, and satellite remote sensing, are combined to provide a comprehensive view of hurricane structure using dual-Doppler analysis, single Doppler observations, microphysical retrievals, and surface station network wind mapping. The primary datasets for this analysis includes Hurricanes Isabel (2003), Irene (2011), Matthew (2016), and Harvey (2017). This dissertation presents a detailed analysis of asymmetric dynamic processes in the form of the excitation of vortex Rossby waves from asymmetric convection in the eye in landfalling hurricanes and their impacts on the surface winds and rainfall experienced at landfall. Specifically, the verification of vortex Rossby wave theory is addressed by examining the propagation of rainbands radially outward of the hurricane eyewall. The impact of vortex Rossby waves on the symmetrization and intensity change in hurricanes is also assessed for the first time in high temporal and spatial resolution. The microphysical structure of vortex Rossby wave-induced rainbands through remotely sensed and in situ observations is also detailed. As vortex Rossby wave-driven processes are currently not well understood, this work concludes by examining a numerical simulation of Hurricane Harvey (2017) to compare observed vortex Rossby waves to those in this simulation. Additionally, little is known regarding the evolution of the hurricane boundary layer at landfall. In order to assess the impacts of structures in the wind field arising from asymmetric dynamics, the hurricane boundary layer response to a step-function change in aerodynamic surface roughness inland must be understood. Using aircraft observations offshore and ground-based mobile and fixed radars onshore, the hurricane boundary layer is quantitatively examined, for the first time, from over the open ocean through the coastal transition. The verification of boundary layer models, which can be used to estimate surface winds from winds observed aloft, is vital the estimation of standardized surface winds. The transfer of momentum by turbulence on a variety of spatial scales can be examined to understand the evolution of the hurricane wind field aloft and relate it to surface winds observed in situ
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