INFRASOUND Scientific and Civilian Applications

INVERSION OF INFRASOUND SIGNALS FOR PASSIVE ATMOSPHERIC

REMOTE SENSINGDouglas Drob1, Robert Meier2, Michael Picone3, and Milton Garcés4

Space Science Division, U.S. Naval Research Laboratory, 4555 Overlook Ave, Washington, DC, 20375

Department of Physics and Astronomy, George Mason University, MS 3F3, Fairfax VA, 22030

Infrasound Research Laboratory, HIGP, SOEST, University of Hawaii, Manoa, 73-4460 Queen Kaahumanu Hwy., #119, Kailua-Kona, HI 96740-26

PASSIVE ACOUSTIC REMOTE SENSING CONCEPT

Figure 1. A schematic of the infrasound inversion procedure formalism.

INVERSION RESULTS

Figure 6. Converged synthetic inversion results for a time of

01/01/2005 at 12:00 UTC generated by the HWM/MSIS climatology

only. The top row shows the inversion results for an iteration early in

the process. The second row shows the results for a intermediate

stage in the process. The bottom row shows the optimal estimate of

the atmospheric profile. The left hand column shows the x-y

difference between the back-propagated and actual source location.

The middle column show the x-z plane of the residual. The right

hand column shows the actual (solid) versus estimated (dashed) wind

profiles. The zonal wind component (black) exhibits the largest

amplitude at the Stratopause (50-70 km).

Figure 7. Same as Fig. 6 for an atmospheric profile for 01/25/2005 at

18:00 UTC generated by the G2S model.

SYNTHETIC DATA FOR INVERSION EXPERIMENTS

Figure 3. Example environmental profiles of the static sound speed (solid

line), zonal (dashed line), and meridional (dotted line) wind velocity

components at 33° N, 106°W on 01/25/ 2005 at 18:00 UT.

Acknowledgements The authors would like to thank the NASA GSFC for making the GEOS-4 analysis fields for

use in the G2S model for this scientific research. This work was supported by the Office of Naval Research.

HISTORY/BACKGROUND

Infrasound was first used by Whipple (1926) to postulate the existence of the stratosphere. Independent confirmation

was obtained with the first peace-time use of V-2 rockets (Best et al., 1947; Gutenberg, 1946). Physical understanding

was then advanced with the demolition of fortifications on the Island of Helgoland on April 18, 1947 with the

detonation of five thousand tons of high explosive (Cox, 1948). The resulting pressure perturbations were recorded on

microbarographs strategically placed 66 to 1000 km to the south-south-east (Cox, 1949; Cox et al., 1949). The use of

sound waves to probe the structure of the atmosphere continued through the mid-1950s with grenades ejected from

rockets (Groves, 1956).

Infrasound research on this topic was revitalized by Donn and Rind, (1972, 1971), Rind (1978), Rind and Donn (1975)

and Rind et al. (1973). For a single station in Palisades, New York they were able to relate the temporal variability of

the amplitude of infrasound signals generated by ocean wave sources (known as microbaroms) in the North Atlantic to

the seasonal and diurnal patterns of the stratosphere and lower thermosphere.

More recently papers by Garcés et al. (2004) and Le Pichon et al. (2005a; 2005b; 2006) showed renewed promise for

this concept using infrasound generated by volcanoes and ocean waves. Like the previous studies, these efforts

demonstrate that there are obvious seasonal and local time variations in infrasound propagation characteristics; in

particular they show that variations in the observed signal back azimuths and trace velocities can be directly correlated

with changes in the atmospheric state. Le Pichon et al. (2005a, 2005b) went one step further and derived corrections to

the ground-to-space atmospheric profiles needed to bring measured infrasound azimuth deviations in line with theory.

THESIS

At a minimum infrasound observations can provide a diagnostic technique for validating existing atmospheric

specifications from numerical weather prediction systems and empirical models. More ambitiously, infrasound signals

from known sources may be directly inverted to independently provide a measure of the atmosphere.

CONCLUSIONS

Acoustic tomography is the prime tool of the seismic and hydroacoustic communities to determine the properties of

the background medium. The technical literature spans more than thirty years (e.g. Aki et al., 1977; Munk, 1986;

Munk and Wunsch, 1979; Romanowicz, 2008). A number of academic textbooks have also been written on the

subject (e.g. Menke, 1989; Munk et al., 1995; Tarantola, 2005; Wunsch, 1996). In seismology the background

medium is basically static, i.e. the system effectively elicits the same response given the same inputs. In

hydroacoustics the problem is mildly time dependent where over few days a slightly different response can be

observed given the same source location. For passive atmospheric remote sensing, the background medium has an

appreciable time dependence on scales from minutes to months and includes the added complication of a dominant

asymmetric wind term which results in significant propagation anisotropy. One luxury that the atmospheric science

community has however, is that the properties of the medium can also be observed remotely from the ground and

space, as well as in-situ, by a number of different techniques.

Figure 2. Source and receiver configuration for the US Regional

Infrasound Network used in the synthetic inversion experiments

[see Herrin et al. (2008) for additional details].

Figure 4. Ray paths for the hypothetical detections by the US regional

infrasound network on January 25, 2005 at 12:00 UTC given the G2S

model atmospheric profiles.

ATMOSPHERIC SPECIFICATIONS

We use the local one dimensional atmospheric profiles from the global hybrid spectral Ground-to-Space (G2S) model of

Drob et al. (2003) to compute the synthetic infrasound data. This system provides a unified global specification of c(z)

and u(z) from the Earth’s surface to greater than 150 km by combining operational numerical weather prediction analysis

fields and upper atmospheric empirical models. In the present study, the observational data products which comprise the

G2S coefficient sets are the 4× daily NOAA operational global forecast system (GFS) analysis products from 0 to 35

km (10 hPa) (Kalnay et al., 1990), the 4× daily stratospheric analysis from 15 to 55 km (100 to 0.2 hPa) from the

NASA Goddard Space Flight Center, Goddard Earth Observing System GEOS-4 (Bloom et al., 1996), and above 45 km

the HWM93 and MSISE-00 empirical models (Hedin et al., 1996; Picone et al., 2002). The G2S system is also

independent of the input data sources and can incorporate analysis products with any resolution including those from the

European Centre for Medium Range Weather Forecasting (ECMWF) (Courtier et al., 1998; Simmons et al., 2005), the

United Kingdom Meteorology Office (UKMO) (Swinbank et al., 1998), and the Naval Operational Global Atmospheric

Prediction System (NOGAPS) (Hogan and Rosmond, 1991).

A number of research challenges are outstanding, among these are; a) inclusion of synthetic measurement noise and

biases within the synthetic observations and the investigation thereof, b) a rigorous statistical survey of the inversion

results from the batch processing of a synthetic database spanning several years, c) estimation of the minimum and

maximum number of stations needed to successful perform an inversion, and d) application of the inversion to an

actual set of observations.

Through these numerical experiments we conclude that given suitable measurements of infrasound signals from a

single impulsive event, passive infrasound remote sensing can in theory provide improved estimates of the state of

the middle- and upper atmosphere with existing infrasound networks and thus improve current understanding,

particularly in conjunction with other simultaneous atmospheric measurements.

Figure 8. Same as Fig. 6 for the G2S atmospheric profiles of 07/21/2005

at 18:00 UTC.

For the respective examples shown the original profiles

are recovered to a meaningful accuracy. In particular the

meridional wind component (shown in blue) is well

resolved, while between 70 and 100 km the zonal wind is

only in error by a few m/s. Estimated statistical

uncertainties from the retrieval process are on the order of

5 m/s though can approach 15 m/s in some instances.

It is much easier to successfully invert the synthetic

observations that were generated by the empirical models

as they contain less vertical structure than the G2S

profiles. As is know in seismology, the presence of

multiple ducts (i.e. low velocity zones) can hamper the

performance of the inversion.

The objective of these numerical experiments is to determine whether currently available measurements are

adequate to obtain meaningful information about the Earth’s upper atmosphere. Infrasound observables are

calculated for a series of fictitious point sources with a simple three dimensional Cartesian ray tracer and a set of

atmospheric profiles spanning a range of geophysical conditions. These synthetic measurements are then inverted

using optimal estimation theory in an attempt to estimate the original atmospheric background state. Calculation

over a range of possible atmospheric configurations is necessary to understand the statistical robustness of the

inversion procedure.