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Anthony Finn and Kevin Rogers

Abstract

If the acoustic signature of an unmanned aerial vehicle (UAV) is observed as it overflies an array of ground microphones, then the projected and observed Doppler shifts in frequency of the narrowband tones generated by its engine may be compared and converted into effective sound speed values. This allows 2D and 3D spatially varying atmospheric temperature and wind velocity fields to be estimated using tomography. Errors in estimating sound speed values are inversely proportional to the rate of change in the narrowband tones received on the ground. As this rate of change typically approaches zero at least twice per microphone during the UAV’s overflight, errors in the time of flight estimates are typically too large to deliver useful precision to the tomographically derived temperature and wind fields. However, these errors may be reduced by one or two orders of magnitude by continuously varying the engine throttle rate, thereby making the tomographic technique potentially feasible. This is demonstrated through reconstruction of realistic simulated conditions for a weakly sheared daytime convective atmospheric boundary layer.

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Anthony Finn and Kevin Rogers

Abstract

The opacity of water to radio waves means there are few, if any, techniques for remotely sensing it and the atmosphere concurrently. However, both these media are transparent to low-frequency sound (<300 Hz), which makes it possible to contemplate systems that take advantage of the natural integration along acoustic paths of signals propagating through both media. This paper proposes—and examines with theoretical analysis—a method that exploits the harmonics generated by the natural signature of a propeller-driven aircraft as it overflies an array of surface and underwater sensors. Correspondence of the projected and observed narrowband acoustic signals, which are monitored synchronously on board the aircraft and by both sensor sets, allows the exact travel time of detected rays to be related to a linear model of the constituent terms of sound speed. These observations may then be inverted using tomography to determine the inhomogeneous structures of both regions. As the signature of the aircraft comprises a series of harmonics between 50 Hz and 1 kHz, the horizontal detection limits of such a system may be up to a few hundred meters, depending on the depth of the sensors, roughness of the water surface, errors due to refraction, and magnitude of the sound field generated by the source aircraft. The approach would permit temperature, wind, and current velocity profiles to be observed both above and below the water’s surface.

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Kevin Rogers and Anthony Finn

Abstract

This paper presents a method for tomographically reconstructing spatially varying three-dimensional atmospheric temperature profiles and wind velocity fields based on passive acoustic travel time measurements between a small unmanned aerial vehicle (UAV) and ground-based microphones. A series of simulations are presented to provide an indication of the performance of the technique. The parametric fields are modeled as the weighted sum of radial basis functions (RBFs) or Fourier series, which also allow local meteorological measurements made at the UAV and ground receivers to supplement any time delay observations. The technique has potential for practical applications such as boundary layer meteorology and theories of atmospheric turbulence and wave propagation through a turbulent atmosphere.

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Anthony Finn, Kevin Rogers, Feng Rice, Joshua Meade, Greg Holland, and Peter May

Abstract

The natural sound generated by an unmanned aerial vehicle is used in conjunction with tomography to remotely sense the virtual temperature and wind profiles of the atmosphere in a horizontal plane up to an altitude of 1200 m and over a baseline of 600 m. Sound fields recorded on board the aircraft and by an array of microphones on the ground are compared and converted to sound speed estimates for the ray paths intersecting the intervening medium. Tomographic inversion is then used to transform these sound speed values into two-dimensional profiles of virtual temperature and wind vector, which enables the atmosphere to be visualized and monitored over time. The wind vector and temperature estimates are compared to measurements taken by a collocated midrange Doppler sodar and sensors on board the aircraft. Large-eddy simulations of daytime atmospheric boundary layers and error models of the tomographic inversion and sodar are also used to assess the magnitude and nature of anticipated differences. Both the simulations and field trials data show similar levels of correspondence between the tomographically derived and independently observed measurements.

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James C. Liljegren, Stephen Tschopp, Kevin Rogers, Fred Wasmer, Lucia Liljegren, and Michael Myirski

Abstract

The Chemical Stockpile Emergency Preparedness Program Meteorological Support Project ensures the accuracy and reliability of data acquired by meteorological monitoring stations located at seven U.S. Army chemical weapons depots where storage and weapons destruction (demilitarization) activities are ongoing. The data are delivered in real time to U.S. Army plume dispersion models, which are used to plan for and respond to a potential accidental release of a chemical weapons agent. The project provides maintenance, calibration, and audit services for the instrumentation; collection, automated screening, visual inspection, and analysis of the data; and problem reporting and tracking to carefully control the data quality. The resulting high-quality meteorological data enhance emergency response modeling and public safety.

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Melvyn Shapiro, Jagadish Shukla, Gilbert Brunet, Carlos Nobre, Michel Béland, Randall Dole, Kevin Trenberth, Richard Anthes, Ghassem Asrar, Leonard Barrie, Philippe Bougeault, Guy Brasseur, David Burridge, Antonio Busalacchi, Jim Caughey, Deliang Chen, John Church, Takeshi Enomoto, Brian Hoskins, Øystein Hov, Arlene Laing, Hervé Le Treut, Jochem Marotzke, Gordon McBean, Gerald Meehl, Martin Miller, Brian Mills, John Mitchell, Mitchell Moncrieff, Tetsuo Nakazawa, Haraldur Olafsson, Tim Palmer, David Parsons, David Rogers, Adrian Simmons, Alberto Troccoli, Zoltan Toth, Louis Uccellini, Christopher Velden, and John M. Wallace

The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.

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