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.