NOAA-Navy Sanctuary Soundscape Monitoring Project, Mid Frequency Active Sonar, Channel Islands, SanctSound_CI01_07_sonar

NOAA and the U.S. Navy are working to better understand underwater sound within the U.S. National Marine Sanctuary System. From 2018 to 2021, these agencies will work with numerous scientific partners to study sound within seven national marine sanctuaries and one marine national monument, which includes waters off Hawai'i and the east and west coasts. Standardized measurements will assess sounds produced by marine animals, physical processes (e.g., wind and waves), and human activities. Collectively, this information will help NOAA and the Navy measure sound levels and baseline acoustic conditions in sanctuaries. This work is a continuation of ongoing Navy and NOAA research, including efforts by NOAA's Office of National Marine Sanctuaries This dataset represents the derived products from the raw acoustic data that are archived at NOAA National Centers for Environmental Information.
abstract=This record represents encounters of active sonar. Encounters of low and mid-frequency active sonar were logged manually from Long-term Spectral Averages using the Logger remora in Triton and user-defined settings. All detected signals with the same characteristics detected within 1 hour of each other were considered one encounter.These data were recorded at SanctSound Site CI01_07 between March 05, 2021 and July 01, 2021.
acknowledgement=This project received funding from the U.S. Navy.
cdm_data_type=TimeSeries
citation=Cite as: NOAA Office of National Marine Sanctuaries and U.S Navy. 2021. Active Sonar Recorded at SanctSound Site CI01_07, SanctSound Data Products. NOAA National Centers for Environmental Information. Accessed [date]. DOI: https://doi.org/http://doi.org/10.25921/5w0q-v678
comment=Data quality: Increased backround level and increased amplitudes, which may or may not be connected to the system performance from 2021-05-29 00:00 to 2021-07-01 15:00 UTC.
contributor_name=Simone Baumann-Pickering, Scripps Institution of Oceanography; Leila Hatch, NOAA Stellwagen Bank National Marine Sanctuary; John Joseph, U.S. Naval Postgraduate School; Anke Kuegler, Hawai'i Institute of Marine Biology, University of Hawai'i at Manoa; Marc Lammers, NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary; Tetyana Margolina, U.S. Naval Postgraduate School; Karlina Merkens, NOAA Pacific Islands Fisheries Science Center; Lindsey Peavey Reeves, NOAA Channel Islands National Marine Sanctuary; Timothy Rowell, NOAA Northeast Fisheries Science Center; Jenni Stanley, Woods Hole Oceanographic Institution; Alison Stimpert, Moss Landing Marine Laboratories; Sofie Van Parijs, NOAA Northeast Fisheries Science Center; Eden Zang,NOAA Hawaiian Islands Humpback Whale National Marine Sanctuary
contributor_role=Principal Investigator
Conventions=COARDS, CF-1.6, ACDD-1.3
featureType=TimeSeries
geospatial_bounds=POINT (34.04358 -120.06702)
history=Encounters of active sonar were logged manually from Long-term Spectral Averages (LTSA), using the Logger remora in Triton (Scripps Whale Acoustics Lab, La Jolla, USA), with the following settings: Window length = 1 h, Frequency range = 0-6000 Hz, Brightness = 40 dB, Contrast = 100%. All detected signals with the same characteristics detected within 1 hour of each other were considered one encounter. Data were processed with Triton - (1.93.20160524/Github version d81e5fa) and Matlab (2016b and newer; statistics toolbox).
id=http://doi.org/10.25921/5w0q-v678
infoUrl=https://ncei.noaa.gov
institution=NOAA
instrument=SoundTrap ST500
keywords_vocabulary=GCMD Science Keywords
naming_authority=NOAA-Navy
project=NOAA-Navy Sanctuary Soundscape Monitoring Project
sourceUrl=(local files)
standard_name_vocabulary=CF Standard Name Table v55

国家海洋和大气管理局（NOAA）及美国海军正致力于深化对美国国家海洋保护区系统内水下声音的理解。自2018年至2021年，这些机构将与众多科学合作伙伴携手研究七个国家级海洋保护区及一个海洋国家纪念地内的声音，包括夏威夷岛及美国东西海岸附近海域。标准化测量将评估海洋动物、物理过程（例如风浪）以及人类活动产生的声音。这些信息的综合将有助于NOAA和海军评估保护区内的声音水平和声学基线条件。此项工作是对海军和NOAA持续研究工作的延续，包括国家海洋保护区办公室的努力。该数据集代表了存储在国家海洋和大气管理局环境信息国家中心的原始声学数据的派生产品。