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Location and Characterization of Infrasonic Events

Location and Characterization of Infrasonic Events. Roger Bowman 1 , Greg Beall 1 , Doug Drob 2 , Milton Garces 3 , Claus Hetzer 3 , Michael O’Brien 1 , Gordon Shields 1 1. Science Applications International Corporation 2. Naval Research Laboratory 3. University of Hawaii

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Location and Characterization of Infrasonic Events

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  1. Location and Characterization of Infrasonic Events Roger Bowman1, Greg Beall1, Doug Drob2, Milton Garces3, Claus Hetzer3, Michael O’Brien1, Gordon Shields1 1.Science Applications International Corporation 2.Naval Research Laboratory 3.University of Hawaii Infrasound Technology Workshop University of California, San Diego October 27-30, 2003

  2. Outline • Challenges • Approach • Data sets • Atmospheric models • Travel-time tables • Characterization and visualization • Ongoing work • Summary

  3. Challenges in Infrasound Monitoring Propagation Source Receiver

  4. Location Approach Stations Signal observations HWM/ MSISE models Ray tracing (tau-p) Travel-time tables Location algorithm Event locations Uncertainty estimation NRL G2S models Ray tracing (tau-p) Travel-time tables Arrival times Azimuths Canonical location data set Event times Location evaluation

  5. Project Network • All stations available in June 2003

  6. Canonical Location Data Set • Focuses on signals with ground truth locations • Waveforms and arrivals • Multiple station detections • For assessing location, azimuth, and travel-time estimates • Chemical explosions: GT1-101 (3 events) • Moving sources: GT100 (3 events) • Single station detection • For assessing azimuth and travel-time estimates • Mining explosions GT10-15 (5 events) • Chemical explosions: GT1-20 (5 events) • Gas pipe explosion: GS1 (1 events) • Earthquakes: GT5-10 (2 events) 1. Ground Truth with accuracy of 1 km – 10 km

  7. Atmospheric Models

  8. Atmospheric Models (2) • Meridional winds for a location in the southwest United States • 0000 UT for January 1-25, 2003

  9. Travel-Time Tables: PIDC • Prototype International Data Center (PIDC) ca. 2001 • Use HWM and MSISE climatological models • Horizontal Wind Model (HWM) • Mass Spectrometer, Incoherent Scatter – Extended (MSISE) • Use David Brown’s ray tracing program • Include travel times for “I” phase only • Depend on azimuth and season • 1o azimuthal resolution; 1.8o radial resolution • Use uncertainties based on possible phase misidentification

  10. Travel-Time Tables: Automatic Processing • Use HWM/MSISE climatological models • Use Milton Garces’ tau-p ray tracing program • Include travel times for stratospheric (Is), thermospheric (It) and undetermined (I) phases • Depend on azimuth, month and time of day • 19 stations x 4 times of day x 12 months x 3 phases =2,736 tables! • 1o azimuthal resolution; 1.5o radial resolution • 0o-120o range • Use uncertainties based on variability of G2S models for each month

  11. HWM/MSISE Travel-Time Table: DLIAR • January • 0000 UT • Back-azimuth: 200o • 2 out of 33,840 curves

  12. HWM/MSISE Travel-Time Table: DLIAR • 0000 UT • Is phases do not exist for some azimuths • Longer travel times westbound from source to receiver

  13. HWM Travel-Time Uncertainties • Non-Gaussian distribution of predicted travel times • Scatter in modeled travel times increases monotonically with range • Characterize uncertainty by standard deviation at two ranges • Interpolate for other ranges

  14. Accounting for Range Dependence • Accounts for variation of atmospheric model along range • Use 1-D ray tracing for four models along profile • Final curve is 4th degree polynomial

  15. Travel-Time Tables: Interactive Analysis • Use Naval Research Laboratory’s Ground-to-Space (G2S) models • Dependent on azimuth, date and time of day • Tables calculated for stations as needed • Include travel times for stratospheric (Is), thermospheric (It) and undetermined (I) phases • Use uncertainties based on variability of travel-time with take off angle for G2S models for each month

  16. G2S Travel-Time Table: DLIAR • 1000 km range • January 23, 2003 • 2000 UT • Similar to HWM travel times

  17. HWM and G2S Travel Time Tables • 2000 km range • January 23, 2003 2000 UT. • January, 1800 UT • Azimuth range for existence of Is phases differs • All G2S travel times are larger than HWM in this example

  18. Source-Size Estimation • Implemented Brown (1999) formula in libmagnitude • M = log10P + 1.36log10R – 0.019v • Where • P is pressure • R is range • v is wind velocity • Preliminary version uses wind at infrasound stations from G2S model

  19. Visualization Tools for Characterization • libinfra • libPMCC • Spectrograms Feature Plotting Analyst Review Station Infra Event Mapping Array Tool Feature Animation • Seismic • Hydroacoustic • Infrasound • Frequency • Apparent velocity • Azimuth

  20. Infra Mapping Tool • Supports “tip-and-queue” processing • Integrated with Analyst Review Station (ARS) • Arrival information sent back and forth • Zoom capability • Topography resolution varies with map scale

  21. Array Tool - Features • Watusi explosion at NTS • “libPMC” features • “libinfra” features • Waveforms

  22. Array Tool - Spectrograms • Watusi explosion at NTS • Standard spectrogram • Coherence spectrogram separates coherent signal from incoherent noise • Waveforms Array Tool

  23. Feature Animation Tool • Maps features to: • x-axes • y-axes • Color • Saturation • Animation sequence • Supports 3-D animations

  24. Feature Animation Tool (2) …can animate over any variable 0.8 Hz 4.8 Hz

  25. Ongoing Work • Location • Test location algorithm using new travel time curves • Complete travel-time tables for location event data set • Quantify changes in capability to estimate location and azimuth • Characterization • Validate feature measurements • Complete prototype analysis tool

  26. Summary • Data sets • Assembled a database of ground-truth events for use in evaluating infrasound source location estimates • Location • Defined a framework for using climatological and meteorological atmospheric models for location estimation • Calculated travel-time tables based on HWM/MSISE for each station, month and 4 times/day • Calculated travel-time tables based on G2S for each event/station in the location data set • Enhanced location programs to accept station/date/time dependent travel times 26

  27. Summary (2) • Characterization and Visualization • Implemented source-size estimation (strongly dependent on wind) • Developed prototype visualization tools for infrasound data feature analysis 27

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