Reverse Satellite Transionospheric Sounding: Advantages and Prospects

This chapter includes four sections. The first introduction section provides a brief review of the existing methods of transionospheric sounding and the results obtained, and the shortcomings of each are noted. The second section describes the proposed principle based on the installation of a receiver on the GLONASS platform. The advantages and technical characteristics of the proposed system are justified. The main area of use is the polar region. The third section presents the most modern modeling methods and models used. To calculate the propagation of radio waves, this is a method of ray tracing taking into account the large- and small-scale inhomogeneities of the ionosphere. To describe the state of the ionosphere, it is proposed to use the IRI2016 model, which includes adaptation to the current diagnostic data provided by ground ionosondes, and the IRI-Plas model, which not only can be adapted to ground ionosonde data, but also to values of the total electronic content, the measurement of which is an additional advantage of the proposed system. The fourth sectionincludes areas of application, the main of which is the monitoring of the polar region, and the least provided with ionospheric information

Ionosphere Monitoring with Remote Sensing

This book focuses on the characterization of the physical properties of the Earth’s ionosphere, contributing to unveiling the nature of several processes responsible for a plethora of space weather-related phenomena taking place in a wide range of spatial and temporal scales. This is made possible by the exploitation of a huge amount of high-quality data derived from both remote sensing and in situ facilities such as ionosondes, radars, satellites and Global Navigation Satellite Systems receivers

Aerospace medicine and biology: A continuing bibliography with indexes, supplement 183

This bibliography lists 273 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1978

GNSS-RO Residual Ionospheric Error (RIE): A New Method and Assessment

GNSS radio occultation (RO) observations play an increasingly important role in monitoring climate changes and numerical weather forecasts in the upper troposphere and stratosphere. The magnitudes of the RO bending angle are small at these altitudes, and therefore residual ionospheric error (RIE) is critical to retrieve vertical profiles of atmospheric temperature and refractivity. The latter represent the state variables of the weather and climate models. RIEs remain poorly characterized in terms of the global geographical distribution and its variations with the local time and altitude influenced by the solar cycle and solar-geomagnetic disturbances. In this study we developed a new method to determine RIE from the RO excess phase measurement on a profile-by-profile basis. The method, called Φex-gradient method, is self-sufficient and based on the vertical derivative of the RO excess phase (Φex) profile, which can be applied to individual RO bending angle observations for RIE correction. In addition to the RIE in bending angle measurements, RIEs are found in the RO Φex measurements in the upper atmosphere where an exponential dependence is expected and in small-scale temperature variance of the RO retrieval. We found that the RIE values derived from the Φex-gradient method can be both positive and negative, which is fundamentally different from the k-method that produces only the positive RIE values. The new algorithm reveals a latitude-dependent diurnal variation with a larger daytime negative RIE (up to ~3 μrad) in the tropics and subtropics. Based on the observed RIE climatology, a local-time dependent RIE representation is used to evaluate its impacts on reanalysis data. We examined these impacts by comparing the data from the Goddard Earth Observing System (GEOS) data assimilation (DA) system with and without the RIE. The RIF impact on GEOS DA temperature is mainly confined to the polar regions of stratosphere. Between 10 hPa and 1 hPa the temperature differences are ~1 K and exceed ~3–4 K in some cases. These results further highlight the need for RO RIE correction in the modern DA systems

New applications and challenges of GNSS variometric approach

Global Navigation Satellite Systems (GNSS) are nowadays widely used in several technical and scientific activities. Since the early stages of development (mid 1980 s), given the high level of accuracy achieved in determining the coordinates of the receiver, it became clear that the extensive deployment of GPS stations all over the world would have improved many tasks in geodesy and geodynamics. The use of GNSS signals is now not only limited to the estimation of the receiver's position, but it has eventually become a key instrument for ionospheric and tropospheric remote sensing studies, and for soil features (GNSS reflectometry). In particular, GNSS can be used to monitor the ionosphere at different time and space scales. On a global scale, GNSS signals are used to generate Global Ionosphere Maps (GIM) by measuring the total electron content from stations located around the world. On a regional scale, the same signals can be used to detect fast ionospheric disturbances, including those generated by natural hazards, such as tsunami and earthquakes. %For these reasons, real-time GNSS applications became particularly relevant in a number of different scientific fields. The Variometric Approach is a processing algorithm for GNSS observations which allow a GNSS receiver to provide valuable real-time information in a stand-alone operative mode. This approach is based on single time differences of suitable linear combinations of GNSS carrier-phase measurements, using a stand-alone GNSS receiver and standard GNSS broadcast products (orbits and clocks corrections) that are available in real-time. This thesis investigates the possibility to apply the Variometric Approach to the monitoring of the ionosphere, in order to detect in real-time ionospheric disturbances generated by tsunami. The first chapter of this thesis will serve as a preface to define fundamental concepts that we will refer to throughout the rest of this work. The rest of this thesis is divided into two main parts. In the first part (chapter~\ref{sec:VADASE}), we present some advances and applications of the VADASE (Variometric Approach for Displacements Analysis Standalone Engine) algorithm to estimate in real time ground velocities and displacements using stand-alone GNSS receivers. This algorithm was eventually appointed as an effective strategy to contribute to GNSS seismology. In this section we used the 2016 Meinong earthquake occurred in Taiwan as a case study and we estimated coseismic displacements and propagation properties of the surface waves in a real-time scenario using low-cost GNSS receivers. The second part of this work (chapters \ref{sec:VARION}, \ref{sec:rtscenario}, and \ref{sec:VARIONimpementation}) is devoted to a new GNSS processing algorithm, VARION (Variometric Approach for Real-Time Ionosphere Observation), which is capable of estimating changes in the ionosphere's Total Electron Content (TEC) using stand-alone GNSS receivers in real time. In chapter~\ref{sec:rtscenario}, the effectiveness of VARION was proven on the following study cases: 2012 Haida Gwaii earthquake and tsunami event, 2015 Chile earthquake and tsunami event, 2013 U.S. East Coast meteotsunami event, and 2017 Mexico tsunami and geomagnetic storm events. Finally, some conclusions and relevant prospects for future VARION developments are outlined. VARION may represent a significant contribution to science because the ionosphere is strongly coupled to the dynamics of the Earth's surface, neutral atmosphere, and geomagnetic field. In particular, these ionospheric perturbations can be used to detect in real time detection atmospheric gravity waves due to tsunamis. During the NASA funded GNSS Tsunami Early Warning System 2017 workshop held in Sendai, Japan, July 25-27 2017, the VARION algorithm was appointed as the first real-time GNSS tsunami tracking and warning system based upon NASA's Global Differential GPS system

The effect of environmental variables on amphibian breeding phenology

Amphibian breeding phenology has generally been associated with temperature and rainfall, but these variables are not able to explain all of the variation in the timing of amphibian migrations, mating and spawning. This thesis examines some additional, previously under-acknowledged geophysical variables that may affect amphibian breeding phenology: lunar phase and the K-index of geomagnetic activity. A serendipitous observation of a large earthquake during the amphibian breeding season enabled a rare record of animal behaviour prior to an earthquake and led to an investigation into the effect of seismicity on amphibians. Data were collected on breeding migrations at three sites in the UK and Italy for frogs (Rana temporaria) and toads (Bufo bufo). Additional data were collated from published literature. Data on the arrivals of two newt species (Triturus cristatus and Lissotriton helveticus) were also analysed. Lunar phase was found to be important in Rana temporaria and Bufo bufo, with more individuals migrating, in amplexus and spawning around the full moon. Newts' response to the full moon was less clear. A meta-analysis of published data revealed that the effect of the lunar cycle on amphibians may be more prevalent than previously supposed and is species-specific, depending on the unique ecology of each species. The effects of the K- index on amphibian reproduction are unclear because of the low number of days when geomagnetism was high. Five days before a large earthquake in L'Aquila, Italy the majority of toads left the breeding site, only re- appearing when the earthquake was over. Numbers of toads were significantly correlated with days since the earthquake but not with weather variables. Finally I attempted to use the variables of interest (two measures of moon phase, plus the K-index of magnetic activity), along with weather variables to construct statistical models of amphibian breeding phenology and to predict arrivals and spawning / amplexus in single years based on the models. This met with variable success; there was a high variability between years in the ability of the models to predict breeding phenology, which could be due to site-specific factors, unmeasured environmental variables, or an endogenous component to breeding phenology

Local Ensemble Transform Kalman Filter for Earth-System Models: An application to Extreme Events

abstract: Earth-system models describe the interacting components of the climate system and technological systems that affect society, such as communication infrastructures. Data assimilation addresses the challenge of state specification by incorporating system observations into the model estimates. In this research, a particular data assimilation technique called the Local Ensemble Transform Kalman Filter (LETKF) is applied to the ionosphere, which is a domain of practical interest due to its effects on infrastructures that depend on satellite communication and remote sensing. This dissertation consists of three main studies that propose strategies to improve space- weather specification during ionospheric extreme events, but are generally applicable to Earth-system models: Topic I applies the LETKF to estimate ion density with an idealized model of the ionosphere, given noisy synthetic observations of varying sparsity. Results show that the LETKF yields accurate estimates of the ion density field and unobserved components of neutral winds even when the observation density is spatially sparse (2% of grid points) and there is large levels (40%) of Gaussian observation noise. Topic II proposes a targeted observing strategy for data assimilation, which uses the influence matrix diagnostic to target errors in chosen state variables. This strategy is applied in observing system experiments, in which synthetic electron density observations are assimilated with the LETKF into the Thermosphere-Ionosphere- Electrodynamics Global Circulation Model (TIEGCM) during a geomagnetic storm. Results show that assimilating targeted electron density observations yields on average about 60%–80% reduction in electron density error within a 600 km radius of the observed location, compared to 15% reduction obtained with randomly placed vertical profiles. Topic III proposes a methodology to account for systematic model bias arising ifrom errors in parametrized solar and magnetospheric inputs. This strategy is ap- plied with the TIEGCM during a geomagnetic storm, and is used to estimate the spatiotemporal variations of bias in electron density predictions during the transitionary phases of the geomagnetic storm. Results show that this strategy reduces error in 1-hour predictions of electron density by about 35% and 30% in polar regions during the main and relaxation phases of the geomagnetic storm, respectively.Dissertation/ThesisDoctoral Dissertation Applied Mathematics 201