OCS Study

BOEM 2014-608

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

Characterization and Potential Impacts of 

Noise Producing Construction and 

Operation Activities on the Outer 

Continental Shelf: Data Synthesis

OCS Study

BOEM 2014-608

Published by

U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

New Orleans, LA

June 2014

Characterization and Potential Impacts of 

Noise Producing Construction and 

Operation Activities on the Outer 

Continental Shelf: Data Synthesis

Authors

Bruce Martin

David Zeddies 

Jeff MacDonnell

Jonathan Vallarta

Julien Delarue

Prepared under BOEM Contract

M10PC000C55

by

JASCO Applied Sciences 

202 - 32 Troop Ave. 

Dartmouth, NS, B3B 1Z1 Canada 

iii

DISCLAIMER

This report was prepared under contract between the Bureau of Ocean Energy Management 

(BOEM) and JASCO Applied Sciences. This report has been technically reviewed by BOEM, 

and it has been approved for publication. Approval does not necessarily signify that the contents 

reflect the views and policies of BOEM, nor does mention of trade names or commercial 

products constitute endorsement or recommendation for use.

REPORT AVAILABILITY

To download a PDF file of this Gulf of Mexico OCS Region report, go to the U.S. 

Department of the Interior, Bureau of Ocean Energy Management, Environmental Studies 

Program Information System website and search on OCS Study BOEM 2014-608.

This report can be viewed at select Federal Depository Libraries. It can also be obtained from 

the National Technical Information Service; the contact information is below.

U.S. Department of Commerce

National Technical Information Service

5301 Shawnee Rd.

Springfield, Virginia 22312

Phone: (703) 605-6000, 1(800) 553-6847

Fax: (703) 605-6900

Website: http://www.ntis.gov/

CITATION

Martin, B, .D. Zeddies, J. MacDonnell, J. Vallarta, and J. Delarue. 2014. Characterization and 

potential impacts of noise producing construction and operation activities on the Outer 

Continental Shelf: data synthesis. U.S. Dept. of the Interior, Bureau of Ocean Energy 

Management, Gulf of Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2014-

608. 84 p.

v

ACKNOWLEDGEMENTS

JASCO thanks Rob Reynolds (Zephyr Marine) and Rob Morris (Edgetech) for assistance 

locating the AMARs at Nantucket Sound after Deployment 1. Thanks also to Joe Pritchard, 

Captain of Big Game, and Jim Tigit, Captain of Minute Man, for assistance with deployments, 

retrievals, and shipping. The deployments and retrievals were performed by Eric Lumsden, Jeff 

MacDonnell, Christopher Whitt, David Zeddies, Scott Trivers, and Nicole Chorney. The manual 

analysis was performed by Eric Lumsden, Craig Evans, Frederic Paquet, and Julien Delarue.

vii

CONTENTS

List of Figures..............................................................................................................................................ix

List of Tables.............................................................................................................................................xiii

1. Introduction.............................................................................................................................................1

1. Background.................................................................................................................................1

2. Summary of Results....................................................................................................................3

2. Methods ..................................................................................................................................................5

1. Acoustic Data Collection ............................................................................................................5

2. Non-Acoustic Data Collection ....................................................................................................7

3. Acoustic Data Analysis...............................................................................................................7

2.3.1. Ambient Sound Levels.................................................................................................7

2.3.2. Automated Shipping Detector....................................................................................10

2.3.3. Marine Life Call Detection.........................................................................................11

3. Results...................................................................................................................................................15

1. Offshore Delaware Bay.............................................................................................................15

3.1.1. Deployment 1, June–October 2010............................................................................15

3.1.2. Deployment 2, October 2010 to January 2011...........................................................25

3.1.3. Deployment 3, January–April 2011 ...........................................................................25

3.1.4. Deployment 4, May–August 2011 .............................................................................34

2. Nantucket Sound.......................................................................................................................39

3.2.1. Deployment 1, June–October 2010............................................................................39

3.2.2. Deployment 2, October 2010 to January 2011...........................................................39

3.2.3. Deployment 3, January–April 2011 ...........................................................................43

3.2.4. Deployment 4, April–August 2011 ............................................................................46

4. Discussion.............................................................................................................................................51

1. Biological Activity....................................................................................................................51

2. Ambient and Anthropogenic Sound Levels..............................................................................53

4.2.1. Variations over Time..................................................................................................53

4.2.2. Variations between Sites............................................................................................55

5. Conclusions and Recommendations .....................................................................................................57

6. Literature Cited .....................................................................................................................................59

Appendix A STFT Analysis ..................................................................................................................61

Appendix B Hydrophone Calibrations..................................................................................................65

ix

LIST OF FIGURES

Figure 1-1. Installed onshore wind power capacity........................................................................ 1

Figure 1-2. United States offshore wind resource .......................................................................... 2

Figure 2-1. Recorder deployment ................................................................................................... 5

Figure 2-2. Autonomous Multi-channel Acoustic Recorder........................................................... 6

Figure 2-3. Mooring design for Autonomous Multi-channel Acoustic Recorder (AMAR) 

deployment with ground line for grapple retrieval. .................................................... 7

Figure 2-4. The Wenz curves describing pressure spectral density levels of marine ambient 

noise............................................................................................................................ 9

Figure 2-5. Spectrogram showing tonals from heavy shipping activity ....................................... 10

Figure 2-6. The contour-follower mask. ....................................................................................... 13

Figure 2-7. Event detection process.............................................................................................. 14

Figure 3-1. Weather data during Deployment 1 in offshore Delaware Bay. ................................ 15

Figure 3-2. Track of Hurricane Earl ............................................................................................. 16

Figure 3-3. Track of Hurricane Igor ............................................................................................. 16

Figure 3-4. Spectral data for Deployment 1 in offshore Delaware Bay. ...................................... 17

Figure 3-5. Percentiles of power spectral density levels of the ambient noise during 

Deployment 1 in offshore Delaware Bay ................................................................. 18

Figure 3-6. Spectrogram of noise from a ship passing near the offshore Delaware Bay 

recorder..................................................................................................................... 19

Figure 3-7. Shipping detections per 30 min file during Deployment 1 in offshore Delaware 

Bay............................................................................................................................ 19

Figure 3-8. Half-hourly occurrence of unknown delphinid calls.................................................. 20

Figure 3-9. Dolphin calls .............................................................................................................. 21

Figure 3-10. Half-hourly occurrence of fin whale calls................................................................ 21

Figure 3-11. Fish sounds recorded on 20 Aug at the offshore Delaware Bay site ....................... 22

Figure 3-12. Fish sounds recorded 15 Sep at the offshore Delaware Bay site ............................. 23

Figure 3-13. Half-hourly occurrence of striped cusk-eel “chatter” sounds.................................. 23

Figure 3-14. Average broadband (100–1000 Hz), SPL every 30 min .......................................... 24

Figure 3-15: Sound pressure levels (SPLs) versus time for week of 28 Aug–04 Sep 2010. The 

data shows a strong peak at dusk and a weaker peak at dawn each day due to 

fish-chorus noise....................................................................................................... 24

Figure 3-16. Weather data during Deployment 3 in offshore Delaware Bay. .............................. 25
x

Figure 3-17. Spectral data from Deployment 3 in offshore Delaware Bay. (32 000-point FFT, 

Hamming window, 50% overlap.) Fin whale calls caused the slight increase in 

sound at 20 Hz in Jan and Feb. The horizontal lines in the range of 40–1000 Hz 

in Jan–Mar are from shipping................................................................................... 26

Figure 3-18. Percentiles of power spectral density levels during Deployment 3 in offshore 

Delaware Bay............................................................................................................ 27

Figure 3-19. Shipping detections during Deployment 3 in offshore Delaware Bay..................... 27

Figure 3-20. Spectrogram of the continuous source near the offshore Delaware Bay recorder... 28

Figure 3-21. Half-hourly occurrence of fin whale calls................................................................ 29

Figure 3-22. Fin whale song notes................................................................................................ 30

Figure 3-23. North Atlantic right whale upcall............................................................................. 30

Figure 3-24. Half-hourly occurrence of North Atlantic right whale calls .................................... 31

Figure 3-25. Humpback whale moans.......................................................................................... 31

Figure 3-26. Half-hourly occurrence of humpback whale calls ................................................... 32

Figure 3-27. Half-hourly occurrence of unknown delphinid calls................................................ 33

Figure 3-28. Weather data during Deployment 4 in offshore Delaware Bay. .............................. 34

Figure 3-29. Spectral data from Deployment 4 in offshore Delaware Bay .................................. 35

Figure 3-30. Percentiles of power spectral density levels of the ambient noise during 

Deployment 4 in offshore Delaware Bay ................................................................. 36

Figure 3-31. Shipping detections during Deployment 4 in offshore Delaware Bay..................... 36

Figure 3-32. Half-hourly occurrence of unknown delphinid calls................................................ 37

Figure 3-33. Half-hourly occurrence of fin whale calls................................................................ 38

Figure 3-34. Weather data for Deployment 2 in Nantucket Sound. ............................................. 39

Figure 3-35. Spectral data for Deployment 2 in Nantucket Sound............................................... 40

Figure 3-36. Percentiles of power spectral density levels of the ambient noise during 

Deployment 2 in Nantucket Sound........................................................................... 41

Figure 3-37. Shipping detections per 30 min file during Deployment 2 in Nantucket Sound. .... 41

Figure 3-38. Unknown fish sounds............................................................................................... 42

Figure 3-39. Half-hourly occurrence of unknown fish sounds..................................................... 42

Figure 3-40. Weather data for Deployment 3 in Nantucket Sound .............................................. 43

Figure 3-41. Spectral data for Deployment 3 in Nantucket Sound............................................... 44

Figure 3-42. Percentiles of power spectral density levels of the ambient noise during 

Deployment 3 in Nantucket Sound........................................................................... 44

Figure 3-43. Shipping detections during Deployment 3 in Nantucket Sound. ............................. 45

Figure 3-44. Half-hourly occurrence of unknown fish sounds..................................................... 45
xi

Figure 3-45. Weather data for Deployment 4 in Nantucket Sound. ............................................. 46

Figure 3-46. Spectral data for Deployment 4 in Nantucket Sound............................................... 47

Figure 3-47. Percentiles of power spectral density levels of the ambient noise during 

Deployment 4 in Nantucket Sound........................................................................... 48

Figure 3-48. Shipping detections during Deployment 4 in Nantucket Sound. ............................. 48

Figure 3-49. Half-hourly occurrence knock trains (30 Apr to 7 Jun) and striped cusk-eel 

chatter sounds (1 Jun until the end).......................................................................... 49

Figure 3-50. Broadband sound pressure level (SPL; 100–1000 Hz) during Deployment 4 in 

Nantucket Sound....................................................................................................... 50

Figure 4-1. The 5th, 50th, and 95th percentiles of sound pressure levels..................................... 54

Figure 4-2. The 5th, 50th, and 95th percentiles of the sound pressure levels............................... 54

Figure 4-3. Deployment 3 sound pressure level difference .......................................................... 56

Figure 4-4. Deployment 4 sound pressure level difference .......................................................... 56

Figure B-1. Example of a GRAS pistonphone calibrator on a hydrophone. Each hydrophone 

type has a customized adapter whose volume was measured with a NIST verified 

Larson-Davis Sound Level Meter............................................................................. 67

Figure B-2. M8E Nominal Calibration Curve .............................................................................. 68

Figure B-3. Nominal Calibration curves for M15B hydrophones. ............................................... 68

xiii

LIST OF TABLES

Table 1. Details of the offshore Delaware Bay Deployments. ....................................................... 5

Table 2. Details of the Nantucket Sound Deployments.................................................................. 6

Table A-1. Short-term Fourier transform (STFT) analysis parameters. ....................................... 63

Table B-1. Hydrophone IDs and single frequency calibration values.......................................... 69

1

1. INTRODUCTION

1. BACKGROUND

The integration of wind energy generation into existing power grids is accelerating around 

the globe and in the United States. The onshore wind power base in the U.S. has grown almost

1500% in just over a decade; from 2.5 GW in 1999 to 37 GW in 2010 (Figure 1-1). The 

American Wind Energy Association (2010) points out that sound economics are driving this 

trend, including: price stability; price hedging to offset volatility of fossil fuel sources; rapid 

construction opportunities compared to nuclear, hydro, and coal-fired power generation systems;

and the benefits of much reduced environmental risks.

Figure 1-1. Installed onshore wind power capacity (30 Sep 2010).

Many densely populated states of the eastern seaboard have little installed onshore wind 

power. There are many contributing factors, such as the lack of available land and the relatively 

poor value of the onshore wind resource. There is, however, great potential for offshore wind 

energy generation in this region. The relatively shallow coastal waters of the U.S. Atlantic 

seaboard from Massachusetts to South Carolina are an excellent wind resource (Figure 1-2) 

within reach of the populated centers. An Oceana study (Mahan et al. 2010) estimates that 127 

GW of energy are economically recoverable from this offshore wind resource. This 127 GW is 

approximately half of the current energy demand of the region, and many of the States could 

supply all of their power with offshore wind alone. In anticipation of increased offshore power 
2

generation applications, the Bureau of Ocean Energy Management, Regulation and Enforcement 

(BOEMRE, now the Bureau of Ocean Energy Management [BOEM]) created the Final Rule for 

Renewable Energy (Department of the Interior 2009), which sets out guidelines for granting 

leases on the Outer Continental Shelf (OCS) for wind, solar, current, and wave energy projects.

Figure 1-2. United States offshore wind resource at 90 m above the surface (average annual wind 

speeds).

Environmental impact during construction, operation, and removal is a key concern for 

permitting under BOEMRE’s Final Rule. To facilitate its permitting process, BOEMRE issued a 

call for proposals to obtain baseline data of natural and anthropogenic underwater noise and 

marine mammal distributions at up to six selected sites within the Atlantic OCS Planning Areas. 

JASCO Applied Sciences (JASCO) was selected to conduct this study. Additional acoustic data 

might be collected when an offshore renewable energy project is built. JASCO staff could then 

compare construction noise with baseline noise, and investigate changes in marine mammal 

detections at the sites.

JASCO was contracted to record and analyze acoustic data near the Cape Wind site in

Nantucket Sound, and at a lease site under consideration by Bluewater Wind in offshore 

Delaware Bay. This report describes the recording and analysis program, and provides results, 

discussion, and recommendations.
3

2. SUMMARY OF RESULTS

The project’s goal was to provide a statistical description of ambient sound levels for one 

year at two locations likely to be developed for offshore wind-energy production. The chosen 

sites were offshore Delaware Bay and Nantucket Sound. The preconstruction description of 

ambient sound levels provides a baseline that can later be used for comparisons, such as during 

construction, operation, and maintenance of the wind farms. These baseline descriptions can also 

be used for comparison with other sites. The statistical description of ambient sounds levels was 

presented as percentile spectral-level histograms of the spectral density values. As a measure of 

relative overall sound levels and as an indication of possible sources of sound, the percentile 

levels were compared with the envelope values of the Wenz curves (Wenz 1962). In general, the 

Wenz curves are reasonable predictors of the ambient noise levels at the two locations; however, 

there are frequency bands and seasons when sound levels are greater than those predicted by the 

Wenz curves.

Both manual and automated detection and classification were performed on the recordings to 

identify prominent sources of sound. Anthropogenic sources, such as heavy shipping, were found 

at each site throughout the year and could exceed the maximal predictions of the Wenz curves. 

Large storms, including hurricanes and Nor’easters, produce rain and wind with high waves and 

are natural sources of sound.

Biological sound activity included marine mammal and fish sounds. Delphinids (likely 

bottlenose dolphins (Tursiops truncatus) and some unidentified species) and fin whales 

(Balaenoptera physalus) were the most commonly detected marine mammals at offshore 

Delaware Bay. North Atlantic right whale (Eubalaena glacialis) calls were detected on a few 

occasions at both sites. Humpback whale (Megaptera novaeangliae) call detections occurred 

only at the offshore Delaware Bay site. Fish choruses were heard in late summer and fall at 

offshore Delaware Bay and in winter and summer at Nantucket Sound. These events 

occasionally exceeded the Wenz curves.

Ambient sound levels differ throughout the year at each site and between each site, but the 

differences are largely attributable to identifiable events and sources. 

5

2. METHODS

1. ACOUSTIC DATA COLLECTION

Underwater acoustic recording was performed for a period of one year at two sites. The sites, 

chosen by BOEMRE, were near the future Cape Wind installation in Nantucket Sound and the 

proposed Bluewater Wind project in offshore Delaware Bay (Figure 2-1). Four offshore 

Delaware Bay deployments and retrievals were carried out aboard charter vessel Big Game from 

Cape May, New Jersey, starting in June 2010 (Table 1). Similarly, four Nantucket Sound 

deployments and retrievals were carried out aboard charter vessel Minute Man from Falmouth, 

Massachusetts, also starting in June 2010 (Table 2). 

Figure 2-1. Recorder deployment and weather buoy locations in Nantucket Sound and 

offshore Delaware Bay.

Table 1.

Details of the Offshore Delaware Bay Deployments

Latitude Longitude Depth (ft) Deployment, 

Record start Record end Recording days Retrieval

38°42.314′ N 74°42.196′ W 69 2010 Jun 29 2010 Oct 4 97 2010 Oct 19

38°42.141′ N 74°42.447′ W 61 2010 Oct 19 * * *

38°42.078′ N’ 74°42.475′ W 61 2011 Jan 22 2011 May 1 99 2011 Jun 6

38°42.433′ N 74°42.052′ W 70 2011 May 3 2011 Aug 4 93 2011 Aug 4

* Recorder was lost.
6

Table 2.

Details of the Nantucket Sound Deployments

Latitude Longitude Depth (ft) Deployment, 

Record start Record end Recording days Retrieval

41°30.087′ N 70°17.901′ W 55 2010 Jun 27 * * 2011 Jan 11

41°30.212′ N 70°17.796′ W 55 2010 Oct 21 2011 Jan 11 82 2011 Jan 11

41°30.119′ N 70°17.913′ W 54 2010 Jan 11 2011 Apr 14 93 2011 Apr 14

41°29.870′ N 70°18.526′ W 50 2011 Apr 14 2011 Aug 2 108 2011 Aug 2

* Did not record.

Underwater sound was recorded with Autonomous Multichannel Acoustic Recorders 

(AMARs, JASCO Applied Sciences; Figure 2-2). Acoustic data were recorded continuously on 

one channel at 24-bits per sample and a sample rate of 32 kHz. Electronic attenuation occurs 

below 16 Hz, so the useful frequency range of these recordings was considered to be 16 Hz to 

16 kHz, with a dynamic range of 100 dB. Each recorder was fitted with an M15C (−160 ± 1 dB 

re 1 V/μPa sensitivity) or an M8 (−165 ± 3 dB re 1 V/μPa sensitivity) omnidirectional 

hydrophone (Geospectrum Technologies Inc.). The in-water, recording noise floor was 37 dB re 

1 μPa/√Hz with the M15 hydrophone and 42 dB re 1 μPa/√Hz with the M8 hydrophone (both at 

2 kHz). Data were stored in 30 min files on 768 GB internal solid-state flash memory.

Hydrophone calibration results are provided in Appendix B.

Each AMAR was deployed with a float collar fastened to a 55 kg anchor weight and attached 

with a line so that the hydrophone would be approximately 2 m above the seafloor (Figure 2-3). 

A shroud (flow shield) was used to cover the cage surrounding the hydrophone in order to reduce 

flow noise, and tubing was added around the anchor line to prevent chafing. A sinking ground 

line, longer than 2.5 times the water depth, was attached from the recorder anchor weight to a 

secondary anchor for retrieval by grappling.

Figure 2-2. Autonomous Multi-channel Acoustic Recorder

(AMAR, JASCO Applied Sciences).
7

Figure 2-3. Mooring design for Autonomous Multi-channel Acoustic Recorder (AMAR)

deployment with ground line for grapple retrieval.

2. NON-ACOUSTIC DATA COLLECTION

Wind speed, wave height, and sea-surface temperature during the deployments were obtained

from the National Buoy Data Center (Meindl and Hamilton 1992): Buoy 44020 for the

Nantucket Sound site and Buoy 44009 for the offshore Delaware Bay site (the locations of the 

buoys are shown in Figure 2-1). The buoy data were obtained at 10-minute temporal resolution 

for the duration of the deployments. Occasional missing data were supplied by averaging 

adjacent points when a single data point was missing, or replicating the closest valid data point 

when more than one data point were missing. 

3. ACOUSTIC DATA ANALYSIS 

Automated processing of the entire dataset was performed with JASCO’s Acoustic Analysis 

software suite to: (1) compute ambient sound levels, (2) detect shipping vessel noise and 

anthropogenic events, and (3) detect marine mammal and fish calls.

2.3.1. Ambient Sound Levels

Ambient sound levels from each recorder were examined to document the range of sound 

levels encountered and their rate of occurrence. Sound level as a function of time and frequency

is known as the spectral density over time and can be plotted as a spectrogram (see e.g., 

Figure 3-4). The spectral density is calculated using the fast Fourier transform (FFT; Oppenheim 

and Shafer 1999) and is the sound power in 1 Hz wide frequency bands. 

The range and occurrence rate of sound levels are presented as exceedance percentiles of the 

spectral density levels. These percentiles are histograms of the spectral density in each frequency 

bin per minute of data. The 5th, 25th, 50th, 75th, and 95th percentiles are plotted. The 5th 

percentile curve is the frequency dependent sound power level that was exceeded 5% of the time 

during the deployment. Equivalently, 95% of the time, the spectral levels were below the 5th 

AMAR

Float collar

1.5 m

55 kg

recorder 

anchor 

Ground line

(2.5 × water depth)

Hydrophone

10 kg ground 

line anchor
8

percentile curve. The 95th percentile represents the quietest noise state that is expected to occur, 

and the 5th percentile represents the loudest.

The 50th percentile is equal to the median of the spectral distribution (i.e., median of the 

1 min spectral density levels) and can be compared to the Wenz ambient noise curves 

(Figure 2-4). The Wenz curves show the range in ambient spectral density levels, as a function of 

frequency, measured off the U.S. Pacific coast over a range of weather, vessel traffic, and 

geologic conditions. The Wenz curve limits of prevailing noise (thick black lines in Figure 2-4) 

are plotted over the spectral distribution results as blue dashed lines; these curves are generalized 

and are provided for approximate comparison only.
9

Figure 2-4. The Wenz curves describing pressure spectral density levels of marine ambient 

noise from weather, wind, geologic activity, and commercial shipping (National 

Research Council 2003 adapted from Wenz 1962). The thick black lines indicate 

the limits of prevailing noise.
10

2.3.2. Automated Shipping Detector

Large shipping vessels generally travel at a constant speed. Their acoustic signature consists 

of a number of narrow, frequency-band peaks (tonals) generated by the vessel’s motors, 

propellers, pumps, and gearing (Arveson and Vendittis 2000) (Figure 2-5). An automated 

shipping detector was implemented to detect tonals in the recorded acoustic data.

To detect tonals, the acoustic data were divided into two-second intervals and their spectra 

calculated using the fast Fourier transform (FFT) with a Hamming window and 50% overlap. 

Sixty two-second samples were then averaged to obtain spectrograms representing one minute

intervals of recorded data. The spectra were normalized in the frequency band between 1 and 

1000 Hz using the split-window normalizing method (Crocker 1998) and searched for 

narrowband peaks. A positive detection was counted when a tonal was present in three of four 

adjacent one-minute intervals. Detection confidence was indicated by the number of peaks 

detected. Though this approach works well for heavy shipping traffic, it is not appropriate for 

detecting fishing vessels or pleasure craft that regularly change speed.

Figure 2-5. Spectrogram showing tonals from heavy shipping activity. 2 s FFT, 2 s time window, 

1.75 s overlap, Hamming window. This curved pattern in the center of the image is a 

typical bathtub pattern that occurs as a vessel approaches and then leaves a sensor 

(closest point of approach is at the inflection point). Note that many of the tonals from 

the shipping show rapid changes in frequency as the vessel speed or gearing is 

changed.
11

2.3.3. Marine Life Call Detection

2.3.3.1. Manual Analysis Protocol

Four trained analysts manually reviewed samples of the data by visually examining 

spectrograms and listening to the recordings. The objective of the manual analysis was to review 

a fraction of the data throughout the deployments to assess where and when marine mammals 

and fish were acoustically present in the area. 

Five percent of the data from each recorder were manually analyzed. The analysis focused on 

the first 90 s of every 30 min of continuously-recorded data, totaling 72 min of data per day per 

recorder. Within each 90 s data sample, the analysts annotated one call per species. JASCO has 

developed a custom software tool, SpectroPlotter, which provides standardized annotations and a 

consistent approach among analysts. SpectroPlotter was used by all analysts to review and 

annotate the data samples. 

In case of doubt regarding species identification within a sample, the data immediately before 

and after the sample were examined for the presence of more easily identifiable calls. 

Unidentified sounds believed to be biological in origin were tagged as “Unknown” and kept for 

subsequent review.

2.3.3.2. Analysis Validation

The lead analyst, Julien Delarue, helped the other analysts classify calls that were difficult to 

assign to a species. Delarue also reviewed a subset of annotations from all analysts to ensure 

accurate classification of calls by species and to provide feedback to the analysts, who fixed any 

incorrect classifications. The review focused on:

 Annotations assigned to baleen whales (particularly the endangered right whale as well as fin 

and humpback whales).

 Fish sounds (although many were not assigned to a species, the aim was to define the period 

of occurrence of the most common sounds).

 Unknown sounds (particularly those whose time and frequency parameters and associated 

comments pointed towards a possibly known source).

Delarue consulted with external researchers when new or unidentified call types were 

detected.

2.3.3.3. Result Compilation

The detections of each species or call types (when the calling species was unknown) were 

compiled and plotted to show their hourly and daily distribution throughout each deployment in 

relation to hours of darkness (from sunset to sunrise). The latter aimed at revealing potential 

diurnal patterns of sound production.

2.3.3.4. Automated Detections

The automated acoustic analysis suite includes a procedure designed to provide a high 

probability of detecting marine life calls in the acoustic recordings. The first step in call detection

is to determine the spectral density (sound level as a function of time and frequency). Biological 

signals are often of short duration, so the spectral density is calculated using a short-time
12

implementation of the fast Fourier transform (STFT) (Oppenheim and Schafer, 1999). There are 

several STFT parameters (sampling rate, window length, zero padding, and analysis window 

overlap) and the choice of values affects the overall performance of the detector. JASCO has 

gained much experience in optimizing the parameters for the best detections.

The contour data space is defined from the spectral density by normalizing the levels in each 

frequency bin at each time step by the median amplitude of the frequency bin for a processing 

block (i.e., STFT window length). The normalized values are then compared to an empirically 

chosen detection threshold (typically four times the median value). The bins above the threshold 

are set to 1 and the bins below the threshold are set to 0 (Figure 2-6) so that each cell of the 

spectrogram is either a 1 or a 0. From the contour data space, the contour of a biological call can 

be found using a simple, but robust, contour-following algorithm that has been described as a 

variation of the flood-fill algorithm (Nosal 2008). 

The contour-following algorithm begins at the first time point in the contour data space and 

considers each cell with a 1 as the potential start of a marine-life call. For each of these potential 

call starts, a joining algorithm searches adjacent cells for other cells that are also set to 1

(Figure 2-6). Merging cells set to 1 creates a contour of the marine life call (similar to how the 

human brain ‘joins the dots’ to ‘know’ that there are three calls in Figure 2-7c). Each cell with a 

1 is only added to one contour, and this algorithm is not concerned with distinguishing the 

boundaries between different calls.

Once a contour is complete, the signal parameters (start time, duration, and frequency 

components) are extracted and a contour is compared to minimum duration and bandwidth 

values before being stored in the output file. JASCO used these detection counts to indicate 

which files may contain biologic calls of interest. A sample of automated detections was 

reviewed by Delarue to verify validity of fin whale and right whale auto-detections. The 

validated detections were included in the plots described in Section 2.3.3.3.
13

Frequency 



Time 

Figure 2-6. The contour-follower mask.

The starting white cell for joining to 

the contour must be 1 to initiate 

contour following. All green and 

blue cells equal to 1 are added to 

the contour. The algorithm 

advances from left to right in time 

so gray cells left of the test cell 

need not be checked again; 

however, the far left cells are 

checked to join any broken 

contours. A contour can be broken 

because a green cell equal to 1 is 

added to the contour even if all 

blue cells are 0.
14

Figure 2-7. Event detection process: (a) Original spectrogram, (b) 

normalized spectrogram (the 4 s at the start and end (black 

bands) are set to 0 because of moving average border effects), 

and (c) detected contours. 

a

b

c
15

3. RESULTS

1. OFFSHORE DELAWARE BAY

3.1.1. Deployment 1, June–October 2010

3.1.1.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44009 in offshore Delaware Bay were obtained 

(Figure 3-1). During Deployment 1, the offshore Delaware Bay water temperature was near 

25 °C and then dropped toward 20 °C in September. Several major weather events occurred 

during this time period: Hurricane Earl passed through the region on 4 Sep (Figure 3-2) and 

Hurricane Igor on 20 Sep (Figure 3-3). More storms with high winds and wave heights occurred

on 23–24 August and in late September, and there was a notable Nor’easter on 10–11 October.

Figure 3-1. Weather data during Deployment 1 in offshore Delaware Bay. Water 

temperature, wind speed, and wave height from NOAA Buoy 44009, Jun–Oct 2010.

0

10

20

30

40

50

60

Water Temp (°C) Wind Speed (ft/s) Wave Height (ft)
16

Figure 3-2. Track of Hurricane Earl, as projected 14:00 EDT, 4 Sep 2010.

Figure 3-3. Track of Hurricane Igor, as projected 14:00 EDT, 20 Sep 2010.
17

The spectral composition over time of the acoustic recording is shown as a spectrogram in 

Figure 3-4. A diurnal pattern in sound levels is suggested by the vertical stripes in the 

spectrogram.

There are several events of increased sound level. The low-frequency (<100 Hz) sound 

events correlate with increased wave height during storms, including Hurricanes Earl and Igor, 

and the Nor’easter in October. The increased sound levels from 25 August to 4 October in the 

higher frequency bands (200–700 Hz and 1000–4000 Hz) were due to fish sounds (see Section

3.1.1.4).

The 5th percentile of the spectral density levels is at or above the Wenz curve limits of 

prevailing noise from 10 Hz to 10 kHz (Figure 3-5). Boating (pleasure craft and fishing boats) 

and biological activity (fish sounds in September) contributed to the high ambient sound levels at 

frequencies between 200 and 4000 Hz. In particular, the two peaks along the 5th percentile 

between 1000 and 3000 Hz can be assigned to striped cusk-eel (Ophidion marginatum) choruses 

(see section 3.1.1.4 and Figure 3-12). Shipping and frequent storms increased the ambient levels 

at frequencies below 100 Hz.

Figure 3-4. Spectral data for Deployment 1 in offshore Delaware Bay.

Spectrogram of acoustic recordings 27 Jun through 4 Oct 2010. This is 

a typical spectrogram showing measured sound levels as colors, with 

time on the horizontal axis and frequency on the vertical axis. This 

spectrogram was generated using the fast Fourier transform (FFT) 

method with 32 000 points, a Hamming window, and 50% overlap. 

These plots show how the sound energy is distributed in time and 

frequency.
18

Figure 3-5. Percentiles of power spectral density levels of the ambient noise 

during Deployment 1 in offshore Delaware Bay, 29 Jun to 4 Oct 

2010. The blue dashed lines indicate the limits of prevailing noise of 

the Wenz curves.

A sample spectrogram of a ship passing the offshore Delaware Bay recorder is shown in 

Figure 3-6. The automated detector was triggered regularly by heavy shipping (Figure 3-7) 

during Deployment 1, except on 23 Aug, and 4 and 20 Sep, which coincided with major storms 

(see Figure 3-1). Shipping traffic likely ceased during these storms, although increased ambient 

sound levels during the storms may have masked the shipping noise.
19

Figure 3-6. Spectrogram of noise from a ship passing near the offshore Delaware Bay

recorder, 17:00, 20 Aug 2010. The closest point of approach creates the 

characteristic bathtub pattern of tonals, which is a Lloyd’s mirror interference 

pattern. (8192 pt FFT, 2048 real data points, 1024 pt advance, Hamming 

window.)

Figure 3-7. Shipping detections per 30 min file during Deployment 1 in offshore Delaware Bay.

0

5

10

15

20

25

Occurrence
20

3.1.1.2. Delphinid Detections

Delphinids were the most commonly detected marine mammals during this deployment. 

Delphinid calls were detected on 86 of the 99 recording days. The occurrence of detections 

declined after 15 Aug 2010. Thereafter, detections occurred with a diurnal pattern with most 

calls recorded during hours of darkness, particularly after 15 Sep. This pattern does not occur 

before 15 Aug (Figure 3-8). The detections included whistles, buzzes, and clicks (Figure 3-9) as 

well as barking sounds thought to be subadult social calls (Laela Sayigh, pers. communication).

Figure 3-8. Half-hourly occurrence of unknown delphinid calls between 29 Jun and 4 Oct 

2010 based on the manual analysis of 5% of the data. Each black rectangle 

represents a 30-minute sound file. The red dashed lines show the recording start 

and end. The shading indicates hours of darkness from sunset to sunrise (Begler

2009).
21

Figure 3-9. Dolphin calls recorded 30 Jul 2010 at the offshore Delaware Bay site. The impulsive 

sounds below 3000 Hz are fish sounds (see Figure 3-11). (Frequency resolution: 

10 Hz; frame size: 0.02 s; time step: 0.01 s; Reisz window.)

3.1.1.3. Fin Whale Detections

Fin whale calls were detected on 11 days, mainly after 15 Sep 2010. Most detections 

consisted of songs (e.g., Watkins et al. 1987). Fin whale calls were detected mainly during 

daylight hours (Figure 3-10).

Figure 3-10. Half-hourly occurrence of fin whale calls between 29 Jun and 4 Oct 2010 based on 

the manual analysis of 5% of the data. Each black rectangle represents a 30-

minute sound file. The red dashed lines show the recording start and end. The 

shading indicates hours of darkness from sunset to sunrise (Begler 2009).
22

3.1.1.4. Fish Detections

Much biological activity related to soniferous fishes was detected at the offshore Delaware 

Bay site during the first deployment. Three dominant sound types were identified. The first 

sound type consisted of knock-like sounds produced in trains (Figure 3-11). These sounds were 

detected from the first day of deployment until 27 Aug. The repetition rate was initially slow but 

increased at the end of the detection period, which coincided with the appearance of the second 

sound type: a “jack-hammer” sound that has been assigned to striped cusk-eels (see the “chatter” 

sound of Sprague and Luczkovich 2001). These chatter sounds began on 25 Aug and lasted until 

the end of the deployment. The sounds were initially spaced out but eventually became so 

prominent as to form two energy bands visible in the spectrogram (Figure 3-5), even in the 

absence of clearly identifiable chatter sounds (Figure 3-12). 

Because of the narrow temporal overlap between the cessation of the knock-like sounds and 

the start of the chatter sounds along with the increase in repetition rate of the knock trains, which 

ultimately approached or matched the chatter sounds, both sounds may be produced by cuskeels, although this is unconfirmed. Figure 3-13, therefore, shows the occurrence of only 

confirmed cusk-eel calls. Masking by ship noise likely explains some of the episodic differences 

in diurnal sound production patterns visible in Figure 3-13. Sprague and Luczkovich (2001) 

recorded this sound type at various times of day in North Carolina and did not describe any 

diurnal patterns in sound production. The chatter sound appears to be linked to spawning in 

striped cusk-eels. The current data shows a clear diurnal pattern with peaks 15-35 dB above the 

normal sound levels occurring near dusk every day (Figure 3-14–Figure 3-15).

The third and last commonly occurring sound type was sequences of 2–4 low-frequency

knocks (Figure 3-11). These first appeared on 20 Aug and occurred until the end of the 

deployment. Other sounds (buzzes, grunts, thumps) likely produced by fish or invertebrates

occurred occasionally throughout the deployment.

Figure 3-11. Fish sounds recorded on 20 Aug at the offshore Delaware Bay site. Note the repeated 

pairs/triplets of knocking sounds between 200–600 Hz and the broadband knock train 

between 300–3000 Hz (frequency resolution: 10 Hz; frame size: 0.128 s; time step: 

0.032 s; Reisz window).
23

Figure 3-12. Fish sounds recorded 15 Sep at the offshore Delaware Bay site. These sounds have 

been assigned to striped cusk-eels. The figure shows a single sound and the two 

continuous energy bands associated with distant chorusing cusk-eels (frequency 

resolution: 5 Hz; frame size: 0.128 s; time step: 0.032 s.; Reisz window).

Figure 3-13. Half-hourly occurrence of striped cusk-eel chatter sounds between 29 Jun and 

4 Oct 2010 based on the manual analysis of 5% of the data. Each black rectangle 

represents a 30-minute sound file. The red dashed lines show the recording start 

and end. The shading indicates hours of darkness from sunset to sunrise (Begler

2009).
24

Figure 3-14. Average broadband (100–1000 Hz), SPL every 30 min, Jul–Oct 2010 in offshore 

Delaware Bay. Peaks occur once per day at 00:00–01:00 UTC (20:00–21:00 local

time). Manual review of the data shows the peaks from 26 Aug onwards to be fish 

choruses. The fish chorus was present throughout the day, with periods of 

particularly intense calling at dusk that increased the sound levels by 15–35 dB for 

a period of 1–2 hours (Figure 3-15). 

Figure 3-15. Sound pressure levels (SPLs) versus time for week of 28 Aug–

04 Sep 2010. The data show a strong peak at dusk and a weaker peak 

at dawn each day due to fish-chorus noise.
25

3.1.2. Deployment 2, October 2010 to January 2011

Unsuccessful attempts to retrieve the recorder were made in January and April 2011. More 

searches were conducted with a side-scan sonar in June and September 2011. The recorder is 

presumed lost. Possible explanations for the loss include flounder dragging that occurs in the 

area, an error in communicating location coordinates, or mooring breakage.

3.1.3. Deployment 3, January–April 2011 

3.1.3.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44009 in offshore Delaware Bay were obtained 

(Figure 3-16). During Deployment 3, the water temperature in offshore Delaware Bay steadily 

rose from about 3 °C in late January to about 10 °C in early May. There were several weather 

events during this time period, though not of the magnitude seen during the first deployment.

Figure 3-16. Weather data during Deployment 3 in offshore Delaware Bay.

The spectral composition over time of the acoustic recording is shown as a spectrogram in 

Figure 3-17. There were events of increased low-frequency sound. Some of the low-frequency 

(<20 Hz) sound energy is attributed to heavy weather, such as on 26 Jan and 16 Apr. Most of the 

sound energy at low frequencies (<100 Hz) is from anthropogenic sources such as shipping (see 

below), especially between 11 and 17 Mar when there was a particularly noisy ship with possible 

engine damage or perhaps a dredging operation.

Percentile spectral levels of recorded sound were calculated and compared to the Wenz 

curves of prevailing noise (Figure 3-18). During Deployment 3 the ambient sound levels were 

well predicted by the Wenz curves except below 100 Hz where there were obvious 

anthropogenic sounds from a damaged ship or other activities and events (including storms). 

0

10

20

30

40

50

60

Water Temp degC Wind Speed ft/s Wave Height ft
26

The percentiles show an unusual slope in the region of 300–5000 Hz, which implies that 

some type of source was present at all times. No biologic source was found to explain this 

energy. The continual presence of shipping near the recorder is likely the source of this noise.

The peak near 25 Hz in the 5th percentile is attributed to fin whale song notes (see Section 

3.1.3.2), which were prominent during the first month of recording.

Figure 3-17. Spectral data from Deployment 3 in offshore Delaware Bay (32 000-

point FFT, Hamming window, 50% overlap). Fin whale calls caused the 

slight increase in sound at 20 Hz in Jan and Feb. The horizontal lines 

in the range of 40–1000 Hz in Jan–Mar are from shipping.
27

Figure 3-18. Percentiles of power spectral density levels during Deployment 3 in offshore 

Delaware Bay, 22 Jan to 1 May 2011. The blue dashed lines indicate the 

limits of prevailing noise of the Wenz curves.

Tonal signals produced by heavy shipping were detected throughout the third deployment 

(Figure 3-19). During 11–17 Mar, sustained anthropogenic sound was detected. A sample 

spectrogram of this source is shown in Figure 3-20. Two broadband Lloyd’s mirror interference 

patterns are apparent in this figure, so two vessels were present.

Figure 3-19. Shipping detections during Deployment 3 in offshore Delaware Bay.

0

5

10

15

20

Occurrence
28

Figure 3-20. Spectrogram of the continuous source near the offshore Delaware Bay recorder, 

15 Mar 2011.
29

3.1.3.2. Fin Whales Detections

Fin whale songs (Figure 3-22) were detected continually from deployment until 20 Feb with 

a few sporadic detections in late February-early March, on 17 Mar, and on 7 Apr 2011. No 

obvious diurnal pattern was observed (Figure 3-21). 

Figure 3-21. Half-hourly occurrence of fin whale calls between 22 Jan and 1 May 2011 based on 

the manual analysis of 5% of the data. Each black rectangle represents a 30-

minute sound file. The red dashed lines show the recording start and end. The 

shading indicates hours of darkness from sunset to sunrise (Begler 2009).
30

Figure 3-22. Fin whale song notes recorded 26 Jan 2011 at the offshore Delaware Bay site 

(frequency resolution: 1 Hz; frame size: 0.1 s; time step: 0.025 s; Reisz window).

3.1.3.3. Right Whale Detections

Right whale upcalls (e.g., Parks and Tyack 2005; Figure 3-23) were detected on eight days 

during the deployment, with 69% of the detection occurring between 30 Jan and 1 Feb 2011 

(Figure 3-24). These calls were likely produced by individuals transiting between their breeding 

grounds off Florida and Georgia and their feeding areas off northeastern U.S. and Canada,

although the direction of travel is unclear.

Figure 3-23. North Atlantic right whale upcall recorded off offshore Delaware Bay on 31 Jan 2011 

(frequency resolution: 2 Hz; frame size: 0.1 s; time step: 0.025 s.; Reisz window). 
31

Figure 3-24. Half-hourly occurrence of North Atlantic right whale calls between 22 Jan and 1 May 

2011 based on the manual analysis of 5% of the data. Each black rectangle 

represents a 30-minute sound file. The red dashed lines show the recording start and 

end. The shading indicates hours of darkness from sunset to sunrise (Begler 2009).

3.1.3.4. Humpback Whale Detections

Humpback whale moans (Figure 3-25) were detected on eight days during Deployment 3. 

Detections were concentrated in early February, 18–19 Feb, and 8 Apr 2011 (Figure 3-26). As 

for right whales, these detections are likely attributable to individuals moving between their 

Caribbean breeding grounds and their North Atlantic feeding grounds.

Figure 3-25. Humpback whale moans recorded off offshore Delaware Bay on 5 Feb 2011 

(frequency resolution: 2 Hz; frame size: 0.1 s; time step: 0.025 s; Reisz window).
32

Figure 3-26. Half-hourly occurrence of humpback whale calls between 22 Jan and 1 May 2011 

based on the manual analysis of 5% of the data. Each black rectangle represents 

a 30-minute sound file. The red dashed lines show the recording start and end. 

The shading indicates hours of darkness from sunset to sunrise (Begler 2009).
33

3.1.3.5. Delphinid Detections

Calls of unidentified delphinid species were detected on 31 days during the third deployment. 

Most detections occurred from early February to early March and in the second half of April 

2011. There were no detections between 18 Mar and 20 Apr 2011.

Figure 3-27. Half-hourly occurrence of unknown delphinid calls between 22 Jan and 1 May 2011 

based on the manual analysis of 5% of the data. Each black rectangle represents a 

30-minute sound file. The red dashed lines show the recording start and end. The 

shading indicates hours of darkness from sunset to sunrise (Begler 2009).
34

3.1.3.6. Fish Detections

No prominent fish sound sounds were detected during the third deployment although buzzes, 

grunts, and thumps, presumably produced by fish or invertebrates, occurred occasionally. 

3.1.4. Deployment 4, May–August 2011 

3.1.4.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44009 in offshore Delaware Bay were obtained 

(Figure 3-28). During Deployment 4, the offshore Delaware Bay water temperature rose from 

approximately 12 °C in early May to about 26 °C in June through August. Although wind speed 

remained low compared to the other deployments, wave heights were higher in May.

Figure 3-28. Weather data during Deployment 4 in offshore Delaware Bay.

The spectral composition over time of the acoustic recording is shown as a spectrogram in 

Figure 3-29. Diurnal variations in sound level are evident as vertical stripes in the spectrogram

from mid-June to the end of the recordings. Low frequency (<100 Hz) tonal signals from heavy

shipping or similar anthropogenic activity is evident during Deployment 4. Throughout May 

large wave heights also contributed to the low frequency sound levels.

Percentile spectral levels of recorded sound were calculated and compared to the Wenz 

curves limits of prevailing noise (Figure 3-30). During Deployment 4, the ambient sound levels 

were well predicted by the Wenz curves except below 100 Hz where the 5th percentile exceeded 

the maximal Wenz curve prediction. Heavy shipping (and possibly wave activity) appears to 

account for these increased sound levels below 100 Hz.

0

10

20

30

40

50

Wind Speed ft/s Wave Height ft Water Temp degC
35

Tonal signals produced by heavy shipping were detectable throughout Deployment 4, 

(Figure 3-19). A heavy shipping event was detected from 10 to 15 July as a ship was making a 

slow transit or was possibly at anchor with active generators.

Figure 3-29. Spectral data from Deployment 4 in offshore Delaware Bay (32 000-

point FFT, Hamming window, 50% overlap). Increased wave heights 

and wind speeds caused higher sound levels in May. A prominent 

shipping event can be seen in early to mid-July.
36

Figure 3-30. Percentiles of power spectral density levels of the ambient noise 

during Deployment 4 in offshore Delaware Bay, 3 May to 4 Aug 

2011. The blue dashed lines indicate the limits of prevailing noise 

of the Wenz curves.

Figure 3-31. Shipping detections during Deployment 4 in offshore Delaware Bay.

0

5

10

15

20

25

30
37

3.1.4.2. Delphinid Detections

Delphinids were by far the most commonly detected species during this deployment. Calls 

were detected on each day of the deployment. No obvious diurnal calling pattern was noted

although more calls were detected during hours of darkness from the second half of June onward

(Figure 3-32). As for previous deployments, the calling species remain unidentified. 

Figure 3-32. Half-hourly occurrence of unknown delphinid calls between 3 May and 3 Aug 

2011 based on the manual analysis of 5% of the data. Each black rectangle 

represents a 30-minute sound file. The red dashed lines show the recording start 

and end. The shading indicates hours of darkness from sunset to sunrise (Begler 

2009).
38

3.1.4.3. Fin Whale Detections

Fin whale calls were detected on seven days between 2 and 20 Jun 2011. Detections 

consisted exclusively of higher-frequency calls (Watkins 1981), and no songs were detected. 

Figure 3-33. Half-hourly occurrence of fin whale calls between 3 May and 3 Aug 2011 based 

on the manual analysis of 5% of the data. Each black rectangle represents a 30-

minute sound file. The red dashed lines show the recording start and end. The 

shading indicates hours of darkness from sunset to sunrise (Begler 2009). 
39

3.1.4.4. Humpback Whale Detections

Humpback whale calls were detected once, on 2 Jun 2011.

3.1.4.5. Fish Detections

Similarly to Deployment 3, no prominent fish sounds were detected during Deployment 4

although buzzes, grunts, and thumps, presumably produced by fish or invertebrates, occurred 

occasionally.

2. NANTUCKET SOUND

3.2.1. Deployment 1, June–October 2010

No data were acquired in Nantucket Sound due to power failure during the deployment. 

3.2.2. Deployment 2, October 2010 to January 2011

3.2.2.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44020 in Nantucket Sound were obtained (Figure 3-1). 

During Deployment 2, the Nantucket Sound water temperature decreased continuously from 

15 °C to about 5 °C. A series of weather events occurred that produced increased wave height, 

notably a major Nor’easter (the North America blizzard of 26–27 Dec).

Figure 3-34. Weather data for Deployment 2 in Nantucket Sound. Water temperature, wind 

speed, and wave height from NOAA Buoy 44020.

0

10

20

30

40

50

60

70

Water Temp degC Wind Speed ft/s Wave Height ft
40

The spectral composition over time of the acoustic recording is shown as a spectrogram in

Figure 3-35. There are regular increases in noise from 100–1000 Hz that appear to relate to 

periods of higher wind speed. Overall, the spectrogram indicates that this period was relatively 

quiet, despite notable weather events. The percentile spectral levels (Figure 3-36) are well within 

the Wenz curve limits of prevailing noise. The 5th percentile shows several tonals in the 40–

200 Hz range, which are likely attributed to the numerous, stereotyped fish sounds recorded from 

mid-December onward (see section 3.2.2.2; Figure 3-38). Tonal signals produced by heavy 

shipping were detected during Deployment 2 (Figure 3-19).

Figure 3-35. Spectral data for Deployment 2 in Nantucket Sound. Spectrogram of 

acoustic recording, 4 Oct 2010 to 10 Jan 2011 (32 000-point FFT, 

Hamming window, 50% overlap).
41

Figure 3-36. Percentiles of power spectral density levels of the ambient noise 

during Deployment 2 in Nantucket Sound. The blue dashed lines 

indicate the limits of prevailing noise of the Wenz curves.

Figure 3-37. Shipping detections per 30 min file during Deployment 2 in Nantucket Sound.

0

2

4

6

8

10

12

14

16

18

Occurrence
42

3.2.2.2. Fish Detections

Stereotyped fish sounds (Figure 3-38) were detected from 12 Dec 2010 until the end of the 

deployment. Detections continued into the next deployment (see section 3.2.3.2). Although the 

first five days of detections showed evidence of a diurnal sound production pattern, sounds were 

detected almost continually thereafter (Figure 3-39). The source of these sounds is unknown.

Figure 3-38. Unknown fish sounds recorded at the Nantucket site on 25 Dec 2011 (frequency 

resolution: 5 Hz; frame size: 0.128 s; time step: 0.032 s; Reisz window).

Figure 3-39. Half-hourly occurrence of unknown fish sounds (as in Figure 3-38) between 21 

Oct 2010 and 11 Jan 2011 based on the manual analysis of 5% of the data. Each 

black rectangle represents a 30-minute sound file. The red dashed lines show the 

recording start and end. The shading indicates hours of darkness from sunset to 

sunrise (Begler 2009).
43

3.2.3. Deployment 3, January–April 2011 

3.2.3.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44020 in Nantucket Sound were obtained (Figure 3-1). 

During Deployment 3, the Nantucket Sound water temperature rose from 4 °C to about 10 °C.

Wind and wave heights were high during some periods, but they were less pronounced than 

during Deployment 2.

Figure 3-40. Weather data for Deployment 3 in Nantucket Sound. Water temperature, wind speed, 

and wave height from NOAA Buoy 44020.

The spectral composition over time of the acoustic recording is shown as a spectrogram in 

Figure 3-41. Overall, the spectrogram indicates this period was relatively quiet. Periods of 

elevated noise in the 100–1000 Hz band relate to extended periods of high wind speeds. The 

percentile spectral levels (Figure 3-42) are within the Wenz curve limits of prevailing noise. 

Shipping was detected regularly at levels comparable to the previous deployments (Figure 3-43). 

0

10

20

30

40

50

60

Water Temp degC Wind Speed ft/s Wave Height ft
44

Figure 3-41. Spectral data for Deployment 3 in Nantucket Sound. Spectrogram of 

acoustic recording (32 000-point FFT, Hamming window, 50% overlap).

Figure 3-42. Percentiles of power spectral density levels of the ambient noise 

during Deployment 3 in Nantucket Sound. The blue dashed lines 

indicate the limits of prevailing noise of the Wenz curves.
45

Figure 3-43. Shipping detections during Deployment 3 in Nantucket Sound. Detections per 30 min file.

3.2.3.2. Fish Detections

The fish sounds (see Figure 3-38) first detected during Deployment 2 continued until 3 Feb 

2011 when they stopped abruptly. A few sporadic detections occurred on 5 and 9 Feb, 15 Mar,

and 14 Apr 2011. The abrupt end of the detections may be due to movement of the fish out of the 

recorder’s detection range or the soniferous behavior of that species may be seasonal.

Figure 3-44. Half-hourly occurrence of unknown fish sounds (as in Figure 3-38) between 11 

Jan and 14 Apr 2011 based on the manual analysis of 5% of the data. Each black 

rectangle represents a 30-minute sound file. The red dashed lines show the 

recording start and end. The shading indicates hours of darkness from sunset to 

sunrise (Begler 2009).

0

2

4

6

8

10

12

14

16

18

Occurrence
46

3.2.4. Deployment 4, April–August 2011 

3.2.4.1. Weather and Ambient Noise

Weather data from NOAA Buoy 44020 in Nantucket Sound were obtained (Figure 3-45). 

During Deployment 4, the Nantucket Sound water temperature rose from approximately 5 °C in 

early April to about 21 °C in late August. Large weather events occurred in April and mid-May 

and became less intense through the summer.

Figure 3-45. Weather data for Deployment 4 in Nantucket Sound. Water temperature, wind speed, 

and wave height from NOAA Buoy 44020.

The spectral composition over time of the acoustic recording is shown as a spectrogram 

(Figure 3-46). Some data from early May were lost due to a faulty memory chip. Diurnal 

variations are evident as vertical stripes throughout the rest of the spectrogram. Low-frequency 

noise events associated with weather occurred in April and May and to a lesser extent in June 

and July. Beginning in late June, sound energy between 800 and 3000 Hz increased. This was 

linked to the onset of striped cusk-eel choruses, whose energy is concentrated in two main bands 

centered near 1.4 and 2.2 kHz (see section 3.2.4.3 and Figure 3-12). Percentile spectral levels 

(Figure 3-47) exceeded the Wenz curve predictions in the frequency range of 800–3000 Hz. The 

percentile spectral levels (Figure 3-47) also show increased noise above 10 kHz, but this is an 

artifact associated with the faulty memory chip. Shipping was detected regularly at levels similar 

to the previous deployments (Figure 3-48). 

0

10

20

30

40

50

60

Wind Speed ft/s Wave Height ft Water Temp degC
47

Figure 3-46. Spectral data for Deployment 4 in Nantucket Sound. Spectrogram of 

acoustic recording (32 000-point FFT, Hamming window, 50% overlap.).

Data from early May were lost due to a faulty memory chip.
48

Figure 3-47. Percentiles of power spectral density levels of the ambient noise 

during Deployment 4 in Nantucket Sound. The blue dashed lines 

indicate the limits of prevailing noise of the Wenz curves.

Figure 3-48. Shipping detections during Deployment 4 in Nantucket Sound. Detections per 30 min 

file. Data from early May were lost due to a faulty memory chip.

0

2

4

6

8

10

12

14

Occurrence
49

3.2.4.2. Right Whale Detections

Right whale upcalls were detected over a five-hour period on 27 Apr 2011.

3.2.4.3. Fish Detections

Striped cusk-eel chatter sounds (Figure 3-12) were the most conspicuous biological noise. As 

in the offshore Delaware Bay Deployment 1, they were preceded by knock trains (Figure 3-11). 

The first knock trains were detected on 30 Apr 2011. Although no data were recorded during the 

first two weeks of May, knocks were still present in low numbers by mid-May. Their occurrence 

increased progressively in the second half of May. The first cusk-eel chatter sounds were on 

1 Jun. The knock sounds disappeared by the second week of June. Cusk-eel sounds were 

detected continuously thereafter until the end of the recordings (Figure 3-49). Sprague and 

Luczkovich (2001) noted an increase in the dominant frequency of chatter sounds with 

increasing water temperature. This may explain a similar increase in frequency visible in 

Figure 3-46 because the water temperature increased progressively during the recording period 

(Figure 3-45). The cusk-eel chatter sounds showed clear diurnal pattern where the sound level 

increased dramatically at dusk for a period of about 30 min (Figure 3-50).

Figure 3-49. Half-hourly occurrence knock trains (30 Apr to 7 Jun) and striped cusk-eel chatter 

sounds (1 Jun until the end) between 14 Apr and 3 Aug 2011 based on the 

manual analysis of 5% of the data. Each black rectangle represents a 30-minute 

sound file. The red dashed lines show the recording start and end. The shading

indicates hours of darkness from sunset to sunrise (Begler 2009). 
50

Figure 3-50. Broadband sound pressure level (SPL; 100–1000 Hz) during Deployment 4 in Nantucket 

Sound. A diurnal pattern appears in mid-June associated with fish choruses at dusk.

80

85

90

95

100

105

110

115

120

SPL (dB re 1 

mPa)
51

4. DISCUSSION

The objective of this project was to provide a statistical description of sound levels and 

sources at two locations likely to be developed for wind energy capture. This preconstruction 

description of sound levels and sources provides a baseline that can later be used for 

comparisons, such as during construction, operation, and maintenance of the wind farms. These 

baseline descriptions can also be compared to other sites. The ambient noise was recorded over 

one year, with the year divided into four deployments. 

Analysis of ambient sound begins with spectrograms of the recordings. Diel (usually diurnal) 

fluctuation can be seen in the spectrograms of some deployments. This daily pattern is likely due 

to fish choruses.

The statistical distribution of ambient sounds levels was presented as percentile histograms of 

the spectral density values. Percentile levels for the 5th, 25th, 50th, 75th, and 95th percentiles are 

given, where the 50th percentile is equal to the median of the spectral distribution and the 95th

percentile is the level exceeded by 95% of the data (see Section 2.3.1). The 95th percentile 

represents the quietest noise state that is expected to occur. The 5th percentile represents the 

loudest state expected to occur and is typically due to occasional events such as nearby shipping,

extreme weather, or intense biological activity. As a measure of relative overall sound levels and 

as an indication of possible sources of sound, the percentile spectral levels were compared with 

the Wenz curve limits of prevailing noise (see Figure 2-4), which represent the contributions of 

various sound sources to ambient sound levels in the oceans. In general, the Wenz curves are 

reasonable predictors of the ambient noise levels at the two locations; however, there are 

frequency bands and seasons when sound levels are greater than predicted by the Wenz curves. 

Both manual and automated detection of some sources was performed on the recordings in an 

effort to identify prominent sources of sound. Heavy shipping noise was found at each site 

throughout the year and contributed to the ambient sound levels at lower frequencies (10–

1000 Hz). This anthropogenic sound, either from shipping or a related activity, such as fishing, 

could exceed the maximal predictions of the Wenz curves (e.g., offshore Delaware Bay

Deployment 3). Boating, such as pleasure or fishing vessels, was also routinely detected and

contributed the overall ambient noise levels. Natural sources contributed to the ambient sound 

levels and also exceeded the predictions of the Wenz curves. Large storms, such as Hurricanes 

Earl and Igor during Deployment 1 in offshore Delaware Bay, produced rain and wind with high 

waves that increased the sound levels. Storms were common in spring and fall, but less frequent 

in winter and summer. 

1. BIOLOGICAL ACTIVITY

Biological activity was found in all deployments. Delphinids were detected only in offshore 

Delaware Bay and were most common from early May until mid-August. Occurrence was low in 

winter and no calls were detected from mid-March to mid-April 2011. The species producing the 

detected whistles and clicks remain unidentified, primarily because of a lack of published call 

descriptions for several species that may occur in this area. Shipboard and aerial surveys 

conducted by NOAA’s Northeast Fisheries Science Center and Southeast Fisheries Science 

Center during the summers of 1998, 1999, 2002, 2004, 2006, and 2007 indicate several delphinid 

species that could have produced the detected calls (whistles and clicks) occur along the eastern 

seaboard at or near the latitude of Delaware. These include bottlenose (Tursiops truncatus), 
52

Risso’s (Grampus griseus), short-beaked common (Delphinus delphis delphis), Atlantic spotted 

(Stenella frontalis), striped (Stenella coeruleoalba), and rough-toothed (Steno bredanensis) 

dolphins and short-finned (Globicephala macrorynchus) and/or long-finned (Globicephala melas 

melas) pilot whales (Waring et al. 2011). Except for bottlenose dolphins, all species were sighted 

exclusively near or beyond the shelf break, i.e., far from the inshore, shallow deployment 

location. The distribution of these species during fall through spring is unknown, but they are all 

known to be associated with the shelf break. Although one cannot rule out some occasional 

intrusions on the continental shelf closer to shore, this leaves bottlenose dolphins as the most 

likely source of most of the detections. 

The stock structure of bottlenose dolphins along the eastern seaboard is complex and 

distinguishes offshore, coastal, and estuarine stocks of bottlenose dolphins. Coastal bottlenose 

dolphins are further distinguished among northern migratory and southern migratory coastal 

stocks. In summer, northern migratory coastal bottlenose dolphins range from New Jersey south 

to the mouth of Chesapeake Bay inshore of the 25 m isobaths (the offshore Delaware Bay

recorder was deployed in 18 m of water). In winter, they migrate south and occupy coastal 

waters from Cape Lookout, North Carolina, to the North Carolina-Virginia border (Waring et al.

2011). This is consistent with the observed patterns of acoustic occurrence, with maximum 

detections in the summer, decreasing detections in the fall and few to no detections in winter and 

early spring (Waring et al. 2011). The northern extent of the southern migratory coastal stock is 

between Cape Lookout, North Carolina and east Virginia; therefore, they are not expected to 

have come within range of the offshore Delaware Bay recorders. Northern migratory coastal 

bottlenose dolphins are likely responsible for a large portion of the detections.

Offshore bottlenose dolphins occur mainly along the outer continental shelf and continental 

slope of the western Atlantic Ocean. In winter, the offshore morphotype has occurred close to 

shore south of Cape Hatteras, North Carolina (Waring et al. 2011). A similar shift in distribution 

may occur off Delaware, possibly explaining some of the winter acoustic detections.

Fin whales were the dominant cetacean species detected in winter. Most fall and all winter 

detections consisted of songs (see e.g., Watkins et al. 1987). Song structure has been shown to 

vary geographically and may be used as an index of stock structure (Hatch and Clark 2004, 

Delarue et al. 2009, Castellote et al. 2011). The detected songs matched those recorded in the 

Gulf of Maine and off New York (Morano et al. 2012), suggesting that fin whales from these 

areas and off Delaware are affiliated. The end of detections in the second half of February 

presumably coincides with a northern movement of fin whales toward their summer feeding 

grounds off the northeastern U.S. Indeed, calling rates are high during the main period when fin 

whales display songs (August–April in the North Atlantic; Neukirk et al. 2012) so it is unlikely 

that fin whales were present and not calling during that period. Additionally, high calling rates 

yield a good detection probability with the 5% analysis protocol that was used. In summer, sound 

production is less regular (Watkins 1981) so the 5% analysis protocol may underestimate fin 

whale occurrence.

Right whales were detected on a few occasions at the offshore Delaware Bay site and once at 

Nantucket Sound. These low numbers of detections may be surprising, considering that the 

offshore Delaware Bay recorder lay within the migration corridor of that species, which migrates 

annually between breeding grounds off Georgia and Florida and feeding grounds off the New 

England and Maritime Canada coast (Firestone et al. 2008). Indeed, the offshore Delaware Bay

recorder was about 16 nautical miles (nmi) from the coast and 94.1% of all sightings recorded in 
53

the Mid-Atlantic region (between 31°15′ and 41°20′ N and west of 69°45′ N) occurred within 30 

nmi from shore; however, 64% of all sightings were within 10 nmi from shore (77% within 

15 nmi; Knowlton et al. 2002). At the latitude of the Delaware recorder, few right whale 

sightings have been recorded, and most of them were within 5 nmi from shore (Knowlton et al.

2002), which could explain the low number of detections. The migration corridor appears to 

extend much farther offshore south of Long Island and farther north, which likely explains why 

right whales were detected at the Nantucket site for only a few hours on a single day. A study 

that modeled the timing of right whale migration found that the average period of transit off 

Delaware is in the first week of April ± 15 days (Firestone et al. 2008). No detections occurred 

during this period. 

Another factor that may have affected right whale detection is their calling rate in 

conjunction with the chosen analysis protocol (5% manual review). Parks et al. (2011) have 

found right whales to be relatively quiet when traveling, as would be expected near the Delaware 

recorder. A low-coverage analysis protocol may, therefore, miss calls produced sporadically; 

however, most of the detected calls were upcalls and these are produced by all age and sex 

classes (Parks et al. 2011). The verification of upcall automated detections yielded a single 

detection that was not previously found by manual analysts, suggesting that the 5% manual 

review provides a reliable view of right whales’ acoustic occurrence. 

Fish proved to be a substantial source of noise in both deployment areas. Notable loud events 

of prolonged duration occurred that often exceeded the Wenz curves, such as the striped cusk-eel

chatter sounds in offshore Delaware Bay and Nantucket Sound between June and October and 

the unidentified calls recorded in Nantucket Sound between mid-December and early February.

More work is needed to assign most of the recorded sounds to species. The delay in the onset of 

the chatter sounds between Nantucket (early June) and Delaware (late August) could be due to a 

southern shift in distribution of striped cusk-eels during the summer, or the environmental

conditions required for spawning may have developed at different times in the two areas.

2. AMBIENT AND ANTHROPOGENIC SOUND LEVELS

4.2.1. Variations over Time

To determine how ambient sound levels in offshore Delaware Bay change throughout the 

year, the 95th, 50th, and 5th percentile values are compared for Deployments 1, 3, and 4 

(Figure 4-1). The sound levels are, in general, comparable between the deployments except for 

the sound levels between 200 and 4000 Hz, where the 5th percentile for Deployment 1 is 

considerably higher than for Deployments 3 and 4. The increased energy in this frequency band 

was attributed to striped cusk-eel sounds; therefore, the primary cause of seasonal variation in 

sound levels at the offshore Delaware Bay site was biological activity. Contributions from 

weather and anthropogenic sources were relatively constant. 

The same 95th, 50th, and 5th percentile values were compared for the year at the Nantucket 

Sound site (Figure 4-2). Again, the sound levels are, in general, comparable between the 

deployments. And again, a notable exception was found between about 200 and 4000 Hz where 

the sound energy in this band is considerably higher at the 5th percentile during Deployment 4

than during Deployments 2 and 3. The increased energy in this frequency band was also cusk-eel

chatter sounds, indicating that the primary driver of seasonal variation in sound levels at the 

Nantucket site was also biological activity.
54

Figure 4-1. The 5th, 50th, and 95th percentiles of sound pressure levels during 

Deployments 1, 3, and 4 in offshore Delaware Bay. 

Figure 4-2. The 5th, 50th, and 95th percentiles of the sound pressure levels

during Deployments 2, 3, and 4 in Nantucket Sound. 
55

4.2.2. Variations between Sites

By subtracting the ambient sound levels measured at the Nantucket Sound site from those at 

the offshore Delaware Bay site, a direct comparison between the two test sites can be made for

Deployments 3 and 4 (Figure 4-3). Figure 4-3 shows that for frequencies between 40 and 100 Hz 

the ambient noise at the offshore Delaware Bay site is consistently louder than at the Nantucket 

Sound site. During Deployment 3 in offshore Delaware Bay, heavy shipping and anthropogenic 

sounds were pronounced and likely account for the higher ambient levels at these frequencies. At 

higher frequencies (100–6000 Hz) the difference between the offshore Delaware Bay and the 

Nantucket Sound sites is consistently positive for the 95th percentile, which indicates that the 

quietest times in offshore Delaware Bay were louder than the quietest times in Nantucket Sound. 

Shipping and possibly other anthropogenic activity likely account for the elevated sound levels

during the quietest times in offshore Delaware Bay relative to Nantucket Sound. Deployment 3 

was during colder months (January to April), so shipping, boating, and other human activities 

may have decreased or stopped periodically in the colder climate of Nantucket Sound, more so

than in offshore Delaware Bay. The small difference between sites in the 5th and 50th percentiles 

indicates that the overall ambient sound levels and the sources of sound are similar at the two 

sites.

Subtracting the sound levels at the Nantucket Sound site from those at the offshore Delaware 

Bay site for Deployment 4 (Figure 4-4) shows that identifiable sources and events determined the 

relative levels at each site. Figure 4-4 shows that in the low-frequency band (40–100 Hz) the 

sound levels in offshore Delaware Bay are greater than in Nantucket Sound. During 

Deployment 4 in offshore Delaware Bay, shipping noise was prevalent, exceeding the Wenz 

curve predictions, and accounting for the difference in sound levels at low frequencies between 

the sites. At higher frequencies (800–1300 Hz) the sound levels in Nantucket Sound were greater 

than in offshore Delaware Bay (negative values in Figure 4-4). The high sound levels in this 

frequency range in Nantucket Sound were due to soniferous fish.
56

Figure 4-3. Deployment 3 sound pressure level difference (offshore 

Delaware Bay minus Nantucket Sound). 

Figure 4-4. Deployment 4 sound pressure level difference (offshore 

Delaware Bay minus Nantucket Sound). 
57

5. CONCLUSIONS AND RECOMMENDATIONS

Percentile-level descriptions of the ambient sound levels over one year at offshore Delaware 

Bay and Nantucket Sound were determined and compared with the envelope values of the Wenz 

curves. The Wenz curves were reasonable predictors of the ambient noise levels at the two 

locations, but there were frequency bands and seasons when sound levels exceeded the maximal 

values predicted by the Wenz curves. Both natural and anthropogenic sound sources exceeded

the Wenz curves: heavy shipping and large storms at lower frequencies (<100 Hz) and biological 

sources (fish) at higher frequencies (200–4000 Hz). The ambient sound levels differed between 

the deployments at each site and between sites, but the differences are largely attributed to 

identifiable events and sources. 

Future developments at the offshore Delaware Bay site should consider the presence of 

endangered right, fin, and humpback whales mainly from January to March. Delphinid 

occurrence, on the other hand, was lowest in winter and spring. Further work is needed to 

identify the fish species whose calls were detected at the Nantucket site in winter. Avoiding the 

two-month detection period, if it happens to be a species of commercial value to local fisheries,

should be considered when planning future work. Although right whale calls were detected at the 

Nantucket site for a few hours in April 2011, marine mammals were essentially absent from this 

site.

The acoustic recordings provide an accurate acoustic baseline that may be used for 

comparisons to ambient levels during wind turbine construction. These baseline descriptions can 

also be used for comparison with other sites.

59

6. LITERATURE CITED

American Wind Energy Association. 2010. Electric Utilities and Wind Power—A Good Mix 

(pamphlet). Available at 

http://www.awea.org/_cs_upload/learnabout/publications/4142_2.pdf

Arveson, P.T. and D.J. Vendittis. 2000. Radiated noise characteristics of a modern cargo ship. 

Journal of the Acoustical Society of America 107:118-129. 

Begler, C. 2009. The Matlab Toolbox of Ch. Begler. Matlab toolbox available at 

http://mooring.ucsd.edu/software/matlab/matlab_intro.html

Castellote, M., C.W. Clark, and M.O. Lammers. 2011. Fin whale (Balaenoptera physalus)

population identity in the western Mediterranean Sea. Marine Mammal Science 28:325–344.

Delarue, J., S.K. Todd, S.M. Van Parijs, and L. Di Iorio. 2009. Geographic variation in 

Northwest Atlantic fin whale (Balaenoptera physalus) song: Implications for stock structure 

assessment. Journal of the Acoustical Society of America 125:1774–1782.

Department of the Interior. 2009. 30 CFR Parts 250, 285, and 290 Renewable Energy and 

Alternate Uses of Existing Facilities on the Outer Continental Shelf; Final Rule. Federal 

Register 74(81):19638-19871. Available at http://www.boem.gov/Renewable-EnergyProgram/FinalRenewableEnergyRule-pdf.aspx

Firestone, J., S.B. Lyons, C. Wang, and J.J. Corbett. 2008. Statistical modeling of North Atlantic 

right whale migration along the mid-Atlantic region of the eastern seaboard of the United 

States. Biological Conservation 141:221-232. 

Hatch, L.T. and C.W. Clark. 2004. Acoustic differentiation between fin whales in both the North 

Atlantic and North Pacific Oceans, and integration with genetic estimates of divergence. 

Paper SC/56/SD6 presented to the IWC Scientific Committee, Sorrento, Italy. pp. 1–37.

Knowlton, A.R., J.B. Ring, and B. Russell. 2002. Right whale sightings and survey effort in the 

mid-Atlantic region: Migratory corridor, time frame, and proximity to port entrances. A 

report submitted to the NMFS ship strike working group.

Mahan, S., I. Pearlman, and J. Savitz. 2010. Untapped Wealth: Offshore Wind Can Deliver 

Cleaner, More Affordable Energy and More Jobs than Offshore Oil. Oceana, Washington, 

DC. 45 p.

Meindl, E.A. and G.D. Hamilton. 1992. Programs of the National Data Buoy Center. Bulletin of 

the American Meteorological Society 73:985-993. Data available at: 

http://www.ndbc.noaa.gov/

Morano, J.L., D.P. Salisbury, A.N. Rice, K.L. Conklin, K.L. Falk, and C.W. Clark. 2012. 

Seasonal and geographical patterns of fin whale song in the western North Atlantic Ocean. 

Journal of the Acoustical Society of America 132(2):1207-1212.
60

National Research Council. 2003. Ocean Noise and Marine Mammals. National Research 

Council (US), Ocean Studies Board, Committee on Potential Impacts of Ambient Noise in 

the Ocean on Marine Mammals. National Academies Press, New York. 195 p.

Neukirk, S.L., D.K. Mellinger, S.E. Moore, K. Klinck, R.P. Dziack, and J. Goslin. 2012. Sounds 

from airguns and fin whales recorded in the mid-Atlantic Ocean, 1999–2009. Journal of the 

Acoustical Society of America 131(2):1102-1112.

Nosal, E.M. 2008. Flood-fill algorithms used for passive acoustic detection and tracking. 

Proceedings of New Trends for Environmental Monitoring Using Passive Systems, 2008. 14-

17 Oct 2008. IEEE. pp. 1-5.

Oppenheim, A.V. and R.W. Schafer. 1999. Discrete-Time Signal Processing. 2nd edition. 

Prentice-Hall. 870 p.

Parks, S.E. and P.L. Tyack. 2005. Sound production by North Atlantic right whales (Eubalaena 

glacialis) in surface active groups. Journal of the Acoustical Society of America 

117:3297−3306.

Parks, S.E., A. Searby, A. Célérier, M.P. Johnson, D.P. Nowacek, and P.L. Tyack. 2011. Sound 

production behavior of individual North Atlantic right whales: implications for passive 

acoustic monitoring. Endangered Species Research 15:63-76.

Sprague, M.W. and J. Luczkovich. 2001. Do striped cusk-eels Ophidion marginatum 

(Ophidiidae) produce the “chatter” sound attributed to weakfish Cynoscion regalis

(Sciaenidae)? Copeia 3:854–859.

Waring, G., E. Josephson, K. Maze-Foley, and P. Rosel (eds.). 2011. U.S. Atlantic and Gulf of 

Mexico Marine Mammal Stock Assessments-2010. NOAA Tech Memo NMFS NE 219. 598 

p. Available at http://www.nefsc.noaa.gov/publications/tm/tm219/

Watkins, W.A. 1981. Activities and underwater sounds of fin whales. Scientific Report of the 

Whale Research Institute 33:83-117.

Watkins, W.A., P. Tyack, K.E. Moore, and J. Bird. 1987. The 20-Hz signals of finback whales 

(Balaenoptera physalus). Journal of the Acoustical Society of America 82:1901-1912.

Wenz, G.M. 1962. Acoustic ambient noise in the ocean: Spectra and sources. Journal of the 

Acoustical Society of America 34(12):1936–1956. 

Appendix A

STFT Analysis

63

The choice of short-term Fourier transform (STFT) parameters affects the overall 

performance of the detector and classifier. The available parameters and their impact are 

described in A-1. The effects of different STFT parameter choices on two signal types are shown 

in Figure A-1.

Table A-1.

Short-term Fourier Transform (STFT) Analysis Parameters

Parameter Definition Effect of Increasing Effect of Decreasing

Fs, Sampling 

Rate 

(determined by 

data collection 

system)

Number of samples of 

the data acquired per 

second; Highest 

frequency that can be 

analyzed is one half the 

sampling rate. (Nyquist 

frequency limit).

Higher sampling rates result in 

more demanding signal 

processing.

Less information since 

there is less frequency 

range represented.

Faster to process.

Analysis 

Window 

Length 

Total number of data 

points in the FFT; For 

efficient FFT 

implementations this 

must be a power of 2.

Increases the frequency 

resolution, but decreases the 

time resolution. Frequency 

resolution is equal to 1/duration in 

time of the FFT (e.g., a 2 s long 

FFT has a resolution of 0.5 Hz). 

Longer is better for signals where 

the frequency changes slowly in 

time.

Short durations are 

better if the signal 

frequencies change 

rapidly in time.

Zero Padding The actual data samples 

that are in the FFT may 

be less than the FFT 

length if the remaining 

points are zero, which is 

known as zero padding.

Increasing the zero padding 

allows the analysis to keep a high 

frequency resolution, but have 

better time resolution. This 

technique provides a better 

resolution, but does not improve 

the ability to discriminate two 

closely spaced tonal 

frequencies–that requires more 

data and a longer FFT.

Some signals have 

constant frequencies for 

short durations, which 

are best represented by 

long FFTs with less 

actual data in the FFT.

Analysis 

Window 

Advance

The number of data 

points that the data flow 

advances with each 

FFT. For example, a 

2048 point FFT 

advances by 25% or 

512 data points.

Provides lower time resolution, 

speeds up the analysis, and 

makes each output more sharply 

defined. A ‘window’ function in 

time is normally applied before an 

FFT to reduce frequency 

sidelobes. As a result there 

should always be some overlap 

to ensure all data is represented 

in the analysis.

A smaller advance will 

provide more output 

points when a signal is 

present thereby 

improving detection and 

contour following; 

however, this increases 

processing time due to 

data redundancy.
64

Figure A-1. Effects of different Short-term Fourier transform (STFT) settings. Top panels–humpback 

moan recorded at a sampling rate of 32 kHz. Top left-hand panel was analyzed with a 

0.25 second analysis window, and an advance of 0.0625 s. Top right-hand panel was 

analyzed with a 0.0625 s analysis window and 0.016 s advance. Bottom panels–dolphin 

whistle processed with the same settings. The short settings are better suited to the rapidly 

changing dolphin whistle, while the longer settings are better suited to the slowly changing 

humpback moan.
Appendix B

Hydrophone Calibrations

67

A GRAS 42AC pistonphone calibrator, which is NIST traceable, was used to verify the 

sensitivity of the recording apparatus as a whole, i.e., the hydrophone, pre-amplifier, and 

AMARS for both lab and field calibrations. Single-frequency calibrations of each hydrophone 

channel were performed in the lab before mobilization and in the field before each deployment. 

The pistonphone produces a known pressure signal on the hydrophone element (a 250 Hz 

sinusoid) which verifies the pressure response of the recording system. Each hydrophone model 

has a custom-fit adapter that couples it to the pistonphone (Figure B-1). Ambient atmospheric 

pressure was measured with a Garmin GPSMap 76CX (at left of Figure B-1) to compensate for 

deviations in ambient pressure (from the nominal 1 atm) and increase the accuracy of the 

calibrations. The single-frequency measurements were used to correct the manufacturer’s 

nominal calibration curves for each hydrophone type for the actual sensitivity of the entire 

system.

Figure B-1. Example of a GRAS pistonphone calibrator on a 

hydrophone. Each hydrophone type has a 

customized adapter whose volume was 

measured with a NIST verified Larson-Davis 

Sound Level Meter.
68

Calibration Curves

M8E Hydrophones

Figure B-2. M8E Nominal Calibration Curve

M15B Hydrophones

Figure B-3. Nominal Calibration curves for M15B hydrophones. Note: "back" traces are further from 

the projector and have not been normalized. The "fwd" trace is slightly closer.

-195

-190

-185

-180

-175

-170

-165

-160

1 10 100 1000 10000 100000

Receive Sensitivity, dBV re 1 

mPa

Frequency, Hz

-175

-170

-165

-160

-155

-150

-145

-140

100 1000 10000 100000

Sensitivty (dB/uPA)

Frequency (Hz)

DUT Sensitivity

M15-1 30deg

back

M15-1

broadside
69

In Field Calibration Values

Table B-1

Hydrophone IDs and Single Frequency Calibration Values

Station & Deployment Hydrophone Type Hydrophone ID

In-Field Calibration Value

dB re 1 μPa @ 250 Hz

Nantucket–1 Did not record

Delaware Bay–1 M15B 173 -158.9

Nantucket–2 M8E 153 -161.3

Delaware Bay–2 Lost

Nantucket–3 M8E 155 -164.4

Delaware Bay–3 M8E 152 -162.7

Nantucket–4 M15B 87 -158.6

Delaware Bay–4 M15B 174 -158.1

The Department of the Interior Mission

As the Nation’s principal conservation agency, the Department of the Interior has 

responsibility for most of our nationally owned public lands and natural 

resources. This includes fostering the sound use of our land and water 

resources; protecting our fish, wildlife, and biological diversity; preserving the 

environmental and cultural values of our national parks and historical places; 

and providing for the enjoyment of life through outdoor recreation. The 

Department assesses our energy and mineral resources and works to ensure 

that their development is in the best interests of all our people by encouraging 

stewardship and citizen participation in their care. The Department also has a 

major responsibility for American Indian reservation communities and for people 

who live in island communities.

The Bureau of Ocean Energy Management Mission

The Bureau of Ocean Energy Management (BOEM) works to manage the 

exploration and development of the nation's offshore resources in a way that 

appropriately balances economic development, energy independence, and 

environmental protection through oil and gas leases, renewable energy 

development and environmental reviews and studies.