The Temporal Morphology of Infrasound Propagation Douglas P. Drob 1 , Milton Garces 2 , Michael Hedlin 3 , and Nicolas Brachet 4 1)Space Science Division, Naval Research Laboratory, Washington, DC 2)Infrasound Laboratory, University of Hawaii, Kona 3)Laboratory for Atmospheric Acoustics, University of California, San Diego 4)International Data Center, Provisional Technical Secretariat, CTBTO, Vienna Austria
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The Temporal Morphology of Infrasound Propagation Douglas P. Drob 1, Milton Garces 2, Michael Hedlin 3, and Nicolas Brachet 4 1)Space Science Division,
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The Temporal Morphology of Infrasound Propagation
Douglas P. Drob1, Milton Garces2, Michael Hedlin3, and Nicolas Brachet4
1)Space Science Division, Naval Research Laboratory, Washington, DC2)Infrasound Laboratory, University of Hawaii, Kona3)Laboratory for Atmospheric Acoustics, University of California, San Diego4)International Data Center, Provisional Technical Secretariat, CTBTO, Vienna Austria
Why are precomputed monthly average travel time tables poor for operational infrasound source location calculations?
Expert knowledge suggests that the performance of automated infrasound event association and source location algorithms will be greatly improved by the ability to continual update station travel time curves to properly account for the seasonal/daily/hourly changes of the atmospheric state.
- thus -
Advocate for, develop, and integrate this capability into automated source location operations to reduced false alarm rates and improved network detection capability.
Requirements• Knowledge of the atmospheric state.• Procedures for calculating infrasound
propagation characteristics.• Procedures for utilization of travel time curves
in automated event association and location algorithms.
• Validation.• Systems integration.
Knowledge of the Atmospheric State
• HWM-93– empirical climatology– data sparse– low resolution– global– time dependent– 0 to 500 km
• Numerical weather prediction– operational– data rich– high-resolution– global/regional– 4x daily– 0 to 55/85 kmNOAA-GSF, ECMWF, NASA-GEOS5,
NOGAPS.
• Hybrid Ground-to-Space Model
• Seamless global specification - U, V, T, and P.
• Operational prototype, 4x daily from September 2002 to current, plus specific events to 1990.
Meridional Wind(N-S)
Zonal Wind (E-W)
Static Sound Speed
Methodology• 4x daily empirical climatologic and G2S
atmospheric specifications from September 13, 2002 to April 31, 2007.
• Tau-P infrasound propagation characteristics (Garces et al., 1998).
• Calculate celerity, azimuth deviation, and turning height for all azimuths up to 35° elevation.
• Calculated from the network receiver perspective.
Conclusions• Over the past 5 years we have developed and compiled
reasonably good knowledge of the atmospheric state for infrasound propagation calculations.
• We have also developed and exercised robust procedures for calculating local infrasound propagation characteristics.
• Precomputed monthly average travel time tables and climatology are poor for operational infrasound source location calculations - performance of automated infrasound event association and source location algorithms will be greatly improved by the ability to continual update station travel time curves to properly account for the seasonal/daily/hourly changes of the atmospheric state
Challenges• Integration of propagation code/travel times
results into automated event association algorithms.
• Data volume and computational resource.• Validation, Validation, Validation