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.

I56US Mid-latitude

January 1, 2006 0:00 UT

260 280 300 320 340 3600

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-100 -50 0 50 1000

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Sound Velocity (m/s) Wind Velocity (m/s)

Altit

ude

(km

)Zonal Meridional

Phase Velocity (m/s)

Back Azimuth (from receiver)

Ele

vatio

n

-150 -100 -50 0 50 100 1500

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Effective Sound Velocity (m/s)

Back Azimuth (Deg)

Alti

tude

(km

)

-150 -100 -50 0 50 100 1500

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Turning Height (km)

Back Azimuth

Ele

vatio

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-150 -100 -50 0 50 100 1500

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0

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Celerity (m/s)

Back Azimuth

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-150 -100 -50 0 50 100 1500

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Range (km)

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-150 -100 -50 0 50 100 1500

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Back Azimuth

Dat

e

I56USa Turning Point (km) from 5 degree elevation

-150 -100 -50 0 50 100 150

Oct02

Jan03

Apr03

Jul03

Oct03

Jan04

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Jan05

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Jan06

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0

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Back Azimuth

Dat

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I56US Turning Point (km) from 5 degree elevation

-150 -100 -50 0 50 100 150

Oct02

Jan03

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Jul03

Oct03

Jan04

Apr04

Jul04

Oct04

Jan05

Apr05

Jul05

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Jan06

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Oct06

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0

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260 280 300 320 340 3600

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Sound Velocity (m/s) Wind Velocity (m/s)

Altit

ude

(km

)Zonal Meridional

Effective Sound Velocity (m/s)

Back Azimuth (Deg)

Alti

tude

(km

)

-150 -100 -50 0 50 100 1500

20

40

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400

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07220

240

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360

Date

Cel

erity

(m

/s)

I56US Eastward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07220

240

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360

Date

Cel

erity

(m

/s)

I56US Southward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07220

240

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360

Date

Cel

erity

(m

/s)

I56US Westward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07-5

-4

-3

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-1

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5

Date

azde

verit

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/s)

I56US Westward arrivals, 5 degree elevation

Azim

uth

Dev

iatio

n (d

egre

es)

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07-5

0

5

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15

Date

azde

verit

y (m

/s)

I56US Southward arrivals, 5 degree elevation

Azim

uth

Dev

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egre

es)

I55US Polar Latitude

Back Azimuth

Dat

e

I55USa Turning Point (km) from 5 degree elevation

-150 -100 -50 0 50 100 150

Oct02

Jan03

Apr03

Jul03

Oct03

Jan04

Apr04

Jul04

Oct04

Jan05

Apr05

Jul05

Oct05

Jan06

Apr06

Jul06

Oct06

Jan07

Apr07

0

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100

120

200 250 300 3500

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40

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-50 0 500

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40

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120

Sound Velocity (m/s) Wind Velocity (m/s)

Altit

ude

(km

)Zonal

Meridional

Back Azimuth

Dat

e

I55US Turning Point (km) from 5 degree elevation

-150 -100 -50 0 50 100 150

Oct02

Jan03

Apr03

Jul03

Oct03

Jan04

Apr04

Jul04

Oct04

Jan05

Apr05

Jul05

Oct05

Jan06

Apr06

Jul06

Oct06

Jan07

Apr07

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Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07240

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Date

Cel

erity

(m

/s)

I55US Southward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07240

250

260

270

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330

340

Date

Cel

erity

(m

/s)

I55US Eastward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07220

240

260

280

300

320

340

Date

Cel

erity

(m

/s)

I55US Westward arrivals, 5 degree elevation

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07-5

0

5

10

15

Date

azde

verit

y (m

/s)

I55US Southward arrivals, 5 degree elevation

Azim

uth

Dev

iatio

n (d

egre

es)

Jan03 Jul03 Jan04 Jul04 Jan05 Jul05 Jan06 Jul06 Jan07-5

-4

-3

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-1

0

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Date

azde

verit

y (m

/s)

I55US Westward arrivals, 5 degree elevation

Azim

uth

Dev

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n (d

egre

es)

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