Long-Term Ambient NoiseStatistics

in theGulf of Mexico

Mark A. Snyder & Peter A. Orlin

Naval Oceanographic Office

Stennis Space Center, MS

Anthony I. Eller

Science Applications International Corporation

EARS* Data

AcousticRelease

Floats

EARSData

Logger

• Bottom-moored omni-directional hydrophone• Bandwidth of 10 Hz - 1000 Hz• 14 months of data (Apr 2004 - May 2005)• Water depth ~ 3200 meters• Hydrophone depth ~ 2935 meters• Vicinity 27.5 N, 86.1 W (about 159 nm south of Panama City, FL and 196 nm west of Tampa, FL)

* Environmental Acoustic Recording System

Location of EARS and NDBC* Weather Buoys

NDBC 42003

EARS

103 nm

89 nm

3200 m

3200 m

55 m

NDBC 42036

* National Data Buoy Center

Monthly

Trends

Monthly Statistics*

• Mean

• Median

• Standard deviation

• Skewness

• Kurtosis

• Coherence time**

* For 8 third-octave bands.

** Time for autocorrelation to decay to e-1 of its zero-lag value.

1 year cycle

Hurricanes

Hurricanes

14-Month

Statistics

Low frequency band

Positive skewness

Chi – Square PDF

Apr04 May05

Apr04 May05

High frequency bandNegative skewness

Hurricanes Winter Storms

1st order Gauss-Markov process is characterized by an exponentially-decaying autocorrelation.

Coherence time = 2.97 hours

400 Hz

Variability

Time

Scales

• Power spectrum of 14-month time series shows how the energy associated with variability is spread over long and short time scales.

• Each vertical bar = variance in each 1/10-decade* freq band.

• Sum of all vertical bars = total variance.

• Low frequency band

• Most of the variability is in time scales near 10 hours

• Red curve is plot of 1st order Gauss-Markov process

4 days 6 weeks 1 year* 1/10-decade ≈ 1/3-octave

4 days 6 weeks 1 year

• High frequency band• Most of the variability is in time scales near 100 hours

Frequency Coherence

2 octaves to left and right of center frequency have correlation coefficient ≥ 0.5

Spatial Coherence

A1 A3A6

2.29 km2.56 km

Water depth = 3200 m at all 3 sites

Hydrophone depth = 2935 m at all 3 sites

10 month comparison

• 100 Hz - more affected by local noise sources

• 1000 Hz – wind is correlated over large distances

• 100 Hz - more affected by local noise sources

• 1000 Hz – wind is correlated over large distances

Comparison to NDBC

Weather Data

• 14-month avg wind speed = 11.3 knots

• Avg significant wave height = 1.06 m

• Avg Beaufort Wind Force = 3.5

• Moderate to heavy shipping

• Shipping level 6-7 on scale of 1-9

• 14-month avg wind speed = 11.3 knots• Avg significant wave height = 1.06 m• Avg Beaufort Wind Force = 3.5• Moderate to heavy shipping• (Shipping level = 6-7 on scale of 1-9, with 1 = light, 9 = very heavy)

Best-Fit Density Functions (14 Months)

Fc (Hz)

Best Fit PDF (3 Moments)

Comments

25 Rayleigh σR = 6.06 50 Chi-Square n = 7 100 Chi-Square n = 6 200 Rayleigh σR = 5.60

σR = Rayleigh parameter.

n = degrees of freedom.

14-Month Summary• Ambient noise at low frequencies (25 – 400 Hz)

Mean > median > mode (2 – 3 dB spread)

All 3 values close and predicted by moderate to heavy shipping. Location of all 3 caused positive skewness (skewed towards peaks).

• Ambient noise at high frequencies (630 – 950 Hz)

Mode > median > mean (2 – 3 dB spread)

All 3 values close and predicted by avg BWF = 3.5 (11.3 knots avg wind). Location of all 3 caused negative skewness (skewed towards troughs).

14-Month Summary

• Coherence time was low (2 – 4 hours) in shipping bands (25 – 400 Hz)

• Coherence time was high (14 – 21 hours) in weather bands (630 – 950 Hz)

• Monthly coherence time was highest during extreme wind conditions

14-Month Summary• Temporal variability occurred over 3 time scales:

7 - 22 hours (shipping-related) 56 - 282 hours (2 - 12 days, weather-related) 8 - 12 months (1 year cycle)

• The 25 Hz time series had a strong 8-hour component (sinusoidal autocorrelation; not shipping or weather)

• The 50, 100 and 200 Hz frequency bands were fit by a 1st order Gauss-Markov process (well characterized by 3 parameters: mean, variance and coherence time)

• More complicated structure in other bands

Avg BWF = 2.5

Mean = 56.26 dB

σ = 5.78 dBRange = 38.27 dB

Skewness = 0.45

C.T. = 1.74 hours

Avg BWF = 4

Mean = 62.73 dB

σ = 4.67 dBRange = 31.81 dB

Skewness = -0.51

C.T. = 10.31 hours

Data Processing

2048 Point FFT

10 Minute Avg

Power Spectra

Separate Data

Into

14 Months

Bandpass Each Month’s

Data Over

Eight 1/3-Octave Bands

Compute Monthly

Statistics Over Each

Frequency Band

Raw Acoustic

Time Series Data

Average 732 (0.82 seconds each) periodograms.

Sampled at 2.5 kHz.

Remove disk spin and clips.

Compute the average power in each band every 10 minutes.

Δf = 1.22 Hz.

FC = 25, 50, 100, 200,

400, 630, 800, 950 Hz

Frances Ivan I JeanneIvan II