1 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 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 Source Propagation Receiver

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

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: GT (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 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 –1 o azimuthal resolution; 1.8 o 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! –1 o azimuthal resolution; 1.5 o radial resolution –0 o -120 o range Use uncertainties based on variability of G2S models for each month

11 HWM/MSISE Travel-Time Table: DLIAR January 0000 UT Back-azimuth: 200 o 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 4 th 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, UT Similar to HWM travel times

17 HWM and G2S Travel Time Tables 2000 km range January 23, 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 = log 10 P log 10 R – 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 Infra Event Mapping Array Tool Feature Plotting Feature Animation Analyst Review Station Seismic Hydroacoustic Infrasound libinfra libPMCC Spectrograms 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 Array Tool Watusi explosion at NTS Standard spectrogram Coherence spectrogram separates coherent signal from incoherent noise Waveforms

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

24 Feature Animation Tool (2) 0.8 Hz4.8 Hz …can animate over any variable

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