Alec Duncan – firstname.lastname@example.org
Centre for Marine Science and Technology, Curtin University, Bentley, WA, 6102, Australia
Applied Physics Laboratory
University of Washington
Popular version of 1pAO2 – Long-range underwater acoustic detection of aircraft surface impacts – the influence of acoustic propagation conditions and impact parameters
Presented at the 185th ASA Meeting
Read the abstract at https://doi.org/10.1121/10.0022761
Please keep in mind that the research described in this Lay Language Paper may not have yet been peer reviewed.
In the right circumstances, sound can travel thousands of kilometres through water, so when Malaysian Airlines flight MH370 went missing in the Indian Ocean in 2014 we searched recordings from underwater microphones called hydrophones for any signal that could be connected to that tragic event. One signal of interest was found, but when we looked at it more carefully it seemed unlikely to be related to the loss of the aircraft.
Fast-forward five years and in 2019 the fatal crash of an F35 fighter aircraft in the Sea of Japan was detected by the Comprehensive Nuclear-Test-Ban Treaty Organisation (CTBTO) using hydrophones near Wake Island, in the north-western Pacific, some 3000 km from the crash site1.
Fig. 1. Locations of the F35 crash and the CTBTO HA11N hydroacoustic station near Wake Island that detected it.
With the whereabouts of MH370 still unknown, we decided to compare the circumstances of the F35 crash with those of the loss of MH370 to see whether we should change our original conclusions about the signal of interest.
Fig. 2. Location of the CTBTO HA01 hydroacoustic station off the southwest corner of Australia. The two light blue lines are the measured bearing of the signal of interest with an uncertainty of +/- 0.75 degrees.
We found that long range hydrophone detection of the crash of MH370 is much less likely than that of the F35, so our conclusions still stand, however there is some fascinating science behind the differences.
Fig. 3. Top: comparison of modelled received signal strengths versus distance from the hydrophones for the MH370 and F35 cases. Bottom: water depth and deep sound channel (DSC) axis depth along each path.
Aircraft impacts generate lots of underwater sound, but most of this travels steeply downward then bounces up and down between the seafloor and sea surface, losing energy each time, and dying out before it has a chance to get very far sideways. For long range detection to be possible the sound must be trapped in the deep sound channel (DSC), a depth region where the water properties stop the sound hitting the seabed or sea surface. There are two ways to get the sound from a surface impact into the DSC. The first is by reflections from a downward sloping seabed, and the second is if the impact occurs somewhere the deep sound channel comes close to the sea surface. Both these mechanisms occurred for the F35 case, leading to very favourable conditions for coupling the sound into the deep sound channel.
Fig. 4. Sound speed and water depth along the track from CTBTO’s HA11N hydroacoustic station (magenta circle) to the estimated F35 crash location (magenta triangle). The broken white line is the deep sound channel axis.
We don’t know where MH370 crashed, but the signal of interest came from somewhere along a bearing that extended northwest into the Indian Ocean from the southwest corner of Australia, which rules out the second mechanism, and there are very few locations along this bearing where the first mechanism would come into play.
Fig. 5. Sound speed and water depth in the direction of interest from CTBTO’s HA01 hydroacoustic station off Cape Leeuwin, Western Australia (magenta circle). The broken white line is the deep sound channel axis.
This analysis doesn’t completely rule out the signal of interest being related to MH370, but it still seems less likely than it being due to low-level seismic activity, something that results in signals at HA01 from similar directions about once per day.
 Metz D, Obana K, Fukao Y, “Remote Hydroacoustic Detection of an Airplane Crash”, Pure and Applied Geophysics, 180 (2023), 1343-1351. https://doi.org/10.1007/s00024-022-03117-6