Rainfall Map from Attenuation Data Fusion of Satellite Broadcast and Commercial Microwave Links

The demand for accurate rainfall rate maps is growing ever more. This paper proposes a novel algorithm to estimate the rainfall rate map from the attenuation measurements coming from both broadcast satellite links (BSLs) and commercial microwave links (CMLs). The approach we pursue is based on an iterative procedure which extends the well-known GMZ algorithm to fuse the attenuation data coming from different links in a three-dimensional scenario, while also accounting for the virga phenomenon as a rain vertical attenuation model. We experimentally prove the convergence of the procedures, showing how the estimation error decreases for every iteration. The numerical results show that adding the BSL links to a pre-existent CML network boosts the accuracy performance of the estimated rainfall map, improving up to 50% the correlation metrics. Moreover, our algorithm is shown to be robust to errors concerning the virga parametrization, proving the possibility of obtaining good estimation performance without the need for precise and real-time estimation of the virga parameters

Sensing the dynamics of severe weather using 4D GPS tomography in the Australian region

The dynamics of water vapour (WV) have a strong influence on weather and climate due to the large energy transfers in the hydrological processes. This particularly correlates to WV dynamics during the formation and lifecycle of severe mesoscale convective storm and precipitation systems. Contrary to its importance, WV remains poorly understood and inadequately measured both spatially and temporally, especially in Australia and the southern hemisphere where meteorological data are sparse. Ground-based and space-borne GPS (global positioning system) meteorology are currently regarded as leading atmospheric remote sensing instruments for numerical weather prediction (NWP) and climatology due to their high spatio-temporal resolutions, multiple observing platforms and continuous operability. The GPS signals are delayed and bent due to the refractive index of the ionosphere and troposphere. This tropospheric path delay can be separated into dry and wet integral components, with the latter proportional, using a scale factor, to the integrated precipitable water vapour (PWV) in the vertical column above the GPS stations. These wet delay measurements can also be combined using a network of GPS stations to resolve the spatial distribution of WV. This method is called GPS tomography, which is a promising and developing method of reconstructing dynamically changing four dimensional (4D) wet refractivity fields. This takes advantage of the high density and homogeneity of ground-based GPS Continuously Operating Reference Station (CORS) networks to provide accurately resolved WV profiles in space and time. A distinct trend between the 4D reconstructed wet refractivity fields using GPS tomography and the formation and lifecycle of severe storm and precipitation systems was found. Sharp gradients are evident up the vertical layers The dynamics of water vapour (WV) have a strong influence on weather and climate due to the large energy transfers in the hydrological processes. This particularly correlates to WV dynamics during the formation and lifecycle of severe mesoscale convective storm and precipitation systems. Contrary to its importance, WV remains poorly understood and inadequately measured both spatially and temporally, especially in Australia and the southern hemisphere where meteorological data are sparse. Ground-based and space-borne GPS (global positioning system) meteorology are currently regarded as leading atmospheric remote sensing instruments for numerical weather prediction (NWP) and climatology due to their high spatio-temporal resolutions, multiple observing platforms and continuous operability. The GPS signals are delayed and bent due to the refractive index of the ionosphere and troposphere. This tropospheric path delay can be separated into dry and wet integral components, with the latter proportional, using a scale factor, to the integrated precipitable water vapour (PWV) in the vertical column above the GPS stations. These wet delay measurements can also be combined using a network of GPS stations to resolve the spatial distribution of WV. This method is called GPS tomography, which is a promising and developing method of reconstructing dynamically changing four dimensional (4D) wet refractivity fields. This takes advantage of the high density and homogeneity of ground-based GPS Continuously Operating Reference Station (CORS) networks to provide accurately resolved WV profiles in space and time. A distinct trend between the 4D reconstructed wet refractivity fields using GPS tomography and the formation and lifecycle of severe storm and precipitation systems was found. Sharp gradients are evident up the vertical layers providing the wet refractivity trend of convection, with high gradient falls through the vertical layers after the storm system passed. Radiosonde is used as a reference to validate the GPS tomographic model with final accuracies of the March 2010 and January 2011 case studies presenting 8.58 and 9.36 ppm RMS errors, respectively. A wet refractivity index adopted for the GPS tomographic wet refractivity profiles showed an excessive increase above the planetary boundary layer as a response to the formation of a supercell thunderstorm. Finally, horizontal and vertical 2D cross sections, investigating the evolution of the March 2010 severe weather event concludes a high correlation between the highly dynamic spatial and temporal changes of wet refractivity, modelled using 4D GPS tomography with precipitation intensities measured using weather radars images. These gradient solutions from GPS tomography are able to identify the spatial and temporal structure of the mesoscale convective and stratiform processes during severe weather. Final investigations analyse the influence of additional observational methods introduced into the observation model of the GPS tomographic processing. This analysis is conducted during the formation and lifecycle of severe weather of the January 2011 case study. A statistical analysis compares additional observational methods including: radiosonde, synoptic weather station networks and GPS radio occultation and then the influence of all observation methods combined. The results are compared against radiosonde-derived wet refractivity estimates as the reference data to conclude RMS errors of 9.36, 8.03, 8.14, 8.56 and 7.57 ppm, respectively. These results have shown that the introduction of accurate additional information into the tomographic solution lead to a significant increase in accuracy and more robust results than the original method containing no additional data. These improvements are in the order of 14.29%, 13.09%, 8.57% and 19.15%, respectively. The major objectives of this research are satisfied by developing ground-based GPS meteorological platforms in the Australian region including the introduction of 4D tomographic reconstruction methods to the GPSnet. These developments are in view of assimilation methods for nowcasting and NWP to provide a more robust platform for early detection and prediction of severe weather and precipitation extremes

Study of real-time estimation of the power attenuation due to rainfall along microwave link

The problem of rainfall monitoring is a topic task in areas where precipitations are characterized by high intensity and very fast development. Tuscany is a region interested by flood and logistic problems due to strong intensity storms. The topic task is to find a rainfall method that can permit to monitor in real time risk areas so that, in case of hazard, citizens can be alerted earlier. Nowadays rain gauges, weather radar, microwave networks and satellite sensing are the most employed approaches to the task of rainfall monitoring. Unfortunately, all of these methods show substantial weakness that, in different ways, limit their employment in any scenario. Although the attenuation of a microwave link is not entirely due to rain, and generally the precipitation events are characterized by a simultaneous multiple status of water, from the point of view of both the probability of occurrence and the severity of effect, the rain scattering is however the most important of the hydrometeor phenomena, especially for operative frequencies above 10 GHz. In this thesis a novel method for rainfall monitoring has been proposed: it is based on the employment of an opportunistic commercial kit for satellite internet services, operating in KA-band. Since the signals within this band are particularly affected by hydrometeors fading, in order to guarantee a continuity of the service in all-weather conditions, the employed device needs to carry out a continuous adjustment of the uplink transmitted power in function of the intensity of the signal received from the satellite. This mechanism, that gives to the service a certain weather independency, is the basic principle of the proposed low-cost digital rain gauge. This power-control technique, essential for KA-band satellite internet applications, can be exploited to measure in real time the signal fading induced by hydrometeors along the Tropospheric segment of the Earth-space link. The proposed algorithm is named Rainfall rate EsTimation - Attenuation Based (RET-AB): it consists on collecting data with the KA-band system and then it processes them in order to retrieve the cumulated rainfall rate along the microwave link. Two measurement campaign have been held in order to validate the results obtained by the whole system

Interpretation of the tropospheric gradients estimated with GPS during the hurricane Harvey

During the last decade Global Positioning System (GPS) Continuous Operating Reference Stations networks have become a new important data source for meteorology. This has dramatically improved the ability to remotely sense the atmosphere under the influence of severe mesoscale and synoptic systems. The zenith tropospheric delay (ZTD) is one of the atmospheric variables continuously observed, and its horizontal variations, the horizontal tropospheric gradients, are routinely computed nowadays within the dual-frequency GPS processing, but their interpretation and relationship with the weather is still an open question. The purpose of this paper is to contribute in this direction by studying the effect that Hurricane Harvey had on the spatial and temporal behavior of the ZTDs and gradients, when it reached Texas coast, during 18–31 August 2017. The results show that ZTD time series present a clear and rapid increase larger than 10 cm in a few hours when the hurricane reached the area. Gradients behaviors show that the hurricane also produced significant changes on them, since the magnitude and predominant directions before and after the hurricane arrived are completely different. Noticeably, the gradient vectors before the landing are consistently related to the horizontal winds and pressure fields. In this manuscript we demonstrate that the ZTD gradients can show a consistent signature under severe weather events, strongly suggesting their potential application for short-term weather forecasting.Fil: Graffigna, Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; ArgentinaFil: Hernández Pajares, Manuel. Universidad Politécnica de Catalunya; EspañaFil: Gende, Mauricio Alfredo. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Azpilicueta, Francisco Javier. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Antico, Pablo Luis. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentin

Doctor of Philosophy

dissertationLow-cost wireless embedded systems can make radio channel measurements for the purposes of radio localization, synchronization, and breathing monitoring. Most of those systems measure the radio channel via the received signal strength indicator (RSSI), which is widely available on inexpensive radio transceivers. However, the use of standard RSSI imposes multiple limitations on the accuracy and reliability of such systems; moreover, higher accuracy is only accessible with very high-cost systems, both in bandwidth and device costs. On the other hand, wireless devices also rely on synchronized notion of time to coordinate tasks (transmit, receive, sleep, etc.), especially in time-based localization systems. Existing solutions use multiple message exchanges to estimate time offset and clock skew, which further increases channel utilization. In this dissertation, the design of the systems that use RSSI for device-free localization, device-based localization, and breathing monitoring applications are evaluated. Next, the design and evaluation of novel wireless embedded systems are introduced to enable more fine-grained radio signal measurements to the application. I design and study the effect of increasing the resolution of RSSI beyond the typical 1 dB step size, which is the current standard, with a couple of example applications: breathing monitoring and gesture recognition. Lastly, the Stitch architecture is then proposed to allow the frequency and time synchronization of multiple nodes' clocks. The prototype platform, Chronos, implements radio frequency synchronization (RFS), which accesses complex baseband samples from a low-power low-cost narrowband radio, estimates the carrier frequency offset, and iteratively drives the difference between two nodes' main local oscillators (LO) to less than 3 parts per billion (ppb). An optimized time synchronization and ranging protocols (EffToF) is designed and implemented to achieve the same timing accuracy as the state-of-the-art but with 59% less utilization of the UWB channel. Based on this dissertation, I could foresee Stitch and RFS further improving the robustness of communications infrastructure to GPS jamming, allow exploration of applications such as distributed beamforming and MIMO, and enable new highly-synchronous wireless sensing and actuation systems

Doctor of Philosophy

dissertationDevice-free localization (DFL) and tracking services are important components in security, emergency response, home and building automation, and assisted living applications where an action is taken based on a person's location. In this dissertation, we develop new methods and models to enable and improve DFL in a variety of radio frequency sensor network configurations. In the first contribution of this work, we develop a linear regression and line stabbing method which use a history of line crossing measurements to estimate the track of a person walking through a wireless network. Our methods provide an alternative approach to DFL in wireless networks where the number of nodes that can communicate with each other in a wireless network is limited and traditional DFL methods are ill-suited. We then present new methods that enable through-wall DFL when nodes in the network are in motion. We demonstrate that we can detect when a person crosses between ultra-wideband radios in motion based on changes in the energy contained in the first few nanoseconds of a measured channel impulse response. Through experimental testing, we show how our methods can localize a person through walls with transceivers in motion. Next, we develop new algorithms to localize boundary crossings when a person crosses between multiple nodes simultaneously. We experimentally evaluate our algorithms with received signal strength (RSS) measurements collected from a row of radio frequency (RF) nodes placed along a boundary and show that our algorithms achieve orders of magnitude better localization classification than baseline DFL methods. We then present a way to improve the models used in through-wall radio tomographic imaging with E-shaped patch antennas we develop and fabricate which remain tuned even when placed against a dielectric. Through experimentation, we demonstrate the E-shaped patch antennas lower localization error by 44% compared with omnidirectional and microstrip patch antennas. In our final contribution, we develop a new mixture model that relates a link's RSS as a function of a person's location in a wireless network. We develop new localization methods that compute the probabilities of a person occupying a location based on our mixture model. Our methods continuously recalibrate the model to achieve a low localization error even in changing environments

Interpretation of the Tropospheric Gradients Estimated With GPS During Hurricane Harvey

During the last decade Global Positioning System (GPS) Continuous Operating Reference Stations networks have become a new important data source for meteorology. This has dramatically improved the ability to remotely sense the atmosphere under the influence of severe mesoscale and synoptic systems. The zenith tropospheric delay (ZTD) is one of the atmospheric variables continuously observed, and its horizontal variations, the horizontal tropospheric gradients, are routinely computed nowadays within the dual-frequency GPS processing, but their interpretation and relationship with the weather is still an open question. The purpose of this paper is to contribute in this direction by studying the effect that Hurricane Harvey had on the spatial and temporal behavior of the ZTDs and gradients, when it reached Texas coast, during 18–31 August 2017. The results show that ZTD time series present a clear and rapid increase larger than 10 cm in a few hours when the hurricane reached the area. Gradients behaviors show that the hurricane also produced significant changes on them, since the magnitude and predominant directions before and after the hurricane arrived are completely different. Noticeably, the gradient vectors before the landing are consistently related to the horizontal winds and pressure fields. In this manuscript we demonstrate that the ZTD gradients can show a consistent signature under severe weather events, strongly suggesting their potential application for short-term weather forecasting.Facultad de Ciencias Astronómicas y Geofísica