Ocean acoustic hurricane classification

Wilson, Joshua D.; Makris, Nicholas C.

doi:10.1121/1.2130961

Cited by 37 publications

(20 citation statements)

References 51 publications

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“…The far more accurate method for quantifying hurricane destructive power achieved in situ through the direct wind speed measurements of specialized hurricane‐hunting aircraft is prohibitively expensive for routine use outside of the North Atlantic and the Gulf of Mexico [ Holland , 1993; Federal Coordinator for Meteorological Services and Supporting Research (FCMSSR) , 2003; Wilson and Makris , 2006].…”

Section: Introductionmentioning

confidence: 99%

Quantifying hurricane destructive power, wind speed, and air‐sea material exchange with natural undersea sound

Wilson

Makris

2008

Geophysical Research Letters

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Passive ocean acoustic measurements may provide a safe and inexpensive means of accurately quantifying the destructive power of a hurricane. This is demonstrated by correlating the underwater sound intensity of Hurricane Gert with meteorological data acquired by aircraft transects and satellite surveillance. The intensity of low frequency underwater sound measured directly below the hurricane is found to be approximately proportional to the cube of the local wind speed, or the wind power. It is shown that passive underwater acoustic intensity measurements may be used to estimate wind speed and quantify the destructive power of a hurricane with an accuracy similar to that of aircraft measurements. The empirical relationship between wind speed and noise intensity may also be used to quantify sea‐salt and gas exchange rates between the ocean and atmosphere, and the impact of underwater ambient noise on marine life and sonar system performance.

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Section: Introductionmentioning

confidence: 99%

Quantifying hurricane destructive power, wind speed, and air‐sea material exchange with natural undersea sound

Wilson

Makris

2008

Geophysical Research Letters

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“…A detailed overview of the stateof-art and a desirability of additional measurements of strong winds may be found in Ref. 7, which also contains extensive references to previous studies exploring the relation between ambient underwater acoustic noise and wind strength. In that article, Wilson and Makris 7 investigated the possibility of measuring by acoustic means hurricane location and corresponding wind speed.…”

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confidence: 99%

Mapping of the ocean surface wind by ocean acoustic interferometers

Voronovich

Penland

2011

The Journal of the Acoustical Society of America

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Measurements of marine surface winds are crucial to understanding mechanical and thermodynamic forces on the ocean. Satellite measurements of surface winds provide global coverage but are problematic at high wind speeds. Acoustic techniques of wind speed retrieval, and even for tracking hurricanes, have been suggested as an alternative since wind is a strong source of ambient noise in the ocean. Such approaches involve near-local measurements with bottom-mounted hydrophones located close to the area of interest. This paper suggests a complementary approach: measuring directivity of low-frequency ambient noise in the horizontal plane. These measurements would employ long vertical line arrays (VLAs) spanning a significant portion of the ocean waveguide. Two VLAs separated by a distance of some tens of kilometers and coherently measuring acoustic pressure form a single ocean interferometer. By sampling the area of interest from different perspectives with at least two interferometers, marine surface winds might be mapped over horizontal scales of the order of 1000 km with about 10 km resolution (more specifically, the 10 km resolution here means that contribution from the basis functions representing surface wind field with the scale of spatial variations of the order of 10 km can be resolved; independent retrieval of the wind within 10(4) cells of a corresponding grid is hardly possible). An averaging time required to overcome statistical variability in the noise field is estimated to be about 3 h. Numerical simulations of propagation conditions typical for the North Atlantic Ocean are presented.

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“…Each Monte-Carlo realization employs a different sound speed profile measured during the OAWRS 2006 experiment [24] every 500 m [33,34] along the propagation path. SL is the whale call source level [1], T is the time duration,f is the center frequency of baleen whale vocalizations relevant for target detection, BW 1/3 is the one-third octave bandwidth centered at frequencyf , DT is the detection threshold, AG is the array gain given whale acoustic parameters, L is the spatial distance between the two omni-directional receiver with spatial coherence, α is the waveguide propagation factor [35], β is the constant baseline ambient noise intensity, and n is the power law coefficient of wind-speed-dependent ambient noise. The parameter values for SL are given in the form of mean ± standard deviation.…”

Section: Detection Of Scattered Returns From Herring Shoals and The Smentioning

confidence: 99%

“…where Φ re f = 1 µPa is the reference acoustic pressure in water, v is the wind speed, n is the power law coefficient of wind-speed-dependent ambient noise, α is the waveguide propagation factor [35], and β is the constant baseline ambient noise intensity. The coefficients n, α, and β given in Table 1 are empirically determined [2] by least-square fitting between the measured and the modeled ambient noise levels as a function of measured wind speed during the OAWRS 2006 experiment [22] ( Figure A1).…”

Section: Detection Of Scattered Returns From Herring Shoals and The Smentioning

confidence: 99%

Feasibility of Acoustic Remote Sensing of Large Herring Shoals and Seafloor by Baleen Whales

Makris

2016

Remote Sensing

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Recent research has found a high spatial and temporal correlation between certain baleen whale vocalizations and peak herring spawning processes in the Gulf of Maine. These vocalizations are apparently related to feeding activities with suggested functions that include communication, prey manipulation, and echolocation. Here, the feasibility of the echolocation function is investigated. Physical limitations on the ability to detect large herring shoals and the seafloor by acoustic remote sensing are determined with ocean acoustic propagation, scattering, and statistical theories given baleen whale auditory parameters. Detection is found to be highly dependent on ambient noise conditions, herring shoal distributions, baleen whale time-frequency vocalization spectra, and geophysical parameters of the ocean waveguide. Detections of large herring shoals are found to be physically feasible in common Gulf of Maine herring spawning scenarios at up to 10 ± 6 km in range for humpback parameters and 1 ± 1 km for minke parameters but not for blue and fin parameters even at zero horizontal range. Detections of the seafloor are found to be feasible up to 2 ± 1 km for blue and humpback parameters and roughly 1 km for fin and minke parameters, suggesting that the whales share a common acoustic sensation of rudimentary features of the geophysical environment.

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Ocean acoustic hurricane classification

Cited by 37 publications

References 51 publications

Quantifying hurricane destructive power, wind speed, and air‐sea material exchange with natural undersea sound

Quantifying hurricane destructive power, wind speed, and air‐sea material exchange with natural undersea sound

Mapping of the ocean surface wind by ocean acoustic interferometers

Feasibility of Acoustic Remote Sensing of Large Herring Shoals and Seafloor by Baleen Whales

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