Long Term Variability of Windspeed.

Underwater acoustic sensors are subject to interfering ambient noise generated by the action of wind on the sea surface. Noise at frequencies above a few hundred Hz generally shows strong correlation with wind speed. A knowledge of the statistical variability of wind-speed is useful for predicting t...

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Bibliographic Details
Main Authors: Eller,A I, Blodgett,M L
Other Authors: NAVAL RESEARCH LAB WASHINGTON DC
Format: Text
Language:English
Published: 1980
Subjects:
Online Access:http://www.dtic.mil/docs/citations/ADA091802
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA091802
id ftdtic:ADA091802
record_format openpolar
spelling ftdtic:ADA091802 2023-05-15T15:05:14+02:00 Long Term Variability of Windspeed. Eller,A I Blodgett,M L NAVAL RESEARCH LAB WASHINGTON DC 1980-11-03 text/html http://www.dtic.mil/docs/citations/ADA091802 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA091802 en eng http://www.dtic.mil/docs/citations/ADA091802 APPROVED FOR PUBLIC RELEASE DTIC AND NTIS Meteorology *WIND VELOCITY *BAROMETRIC PRESSURE VARIATIONS SPECTRA STATISTICAL ANALYSIS FOURIER ANALYSIS ARCTIC OCEAN ISLANDS Bear Island(Norway) Van Mayen PE63795N WU03530 Text 1980 ftdtic 2016-02-20T18:55:06Z Underwater acoustic sensors are subject to interfering ambient noise generated by the action of wind on the sea surface. Noise at frequencies above a few hundred Hz generally shows strong correlation with wind speed. A knowledge of the statistical variability of wind-speed is useful for predicting the properties of ambient noise. Values of surface wind speed and atmospheric pressure reported from weather stations at Jan Mayen in the Norwegian Sea and Bear Island in the Barents Sea over a two-year period were examined. It was found that the statistical distribution of wind speeds can be represented approximately as a Rayleigh distribution. Spectral analysis of the time series records of wind speed and pressure shows that most of the variability of these parameters is contributed by synoptic scale variations having periods of from a few days to a few weeks. The annual or seasonal variations has the largest signle Fourier coefficient but represents only a relatively small part of the total variance. (Author) Text Arctic Arctic Ocean Barents Sea Bear Island Jan Mayen Norwegian Sea Defense Technical Information Center: DTIC Technical Reports database Arctic Arctic Ocean Barents Sea Bear Island ENVELOPE(-67.250,-67.250,-68.151,-68.151) Jan Mayen Norway Norwegian Sea
institution Open Polar
collection Defense Technical Information Center: DTIC Technical Reports database
op_collection_id ftdtic
language English
topic Meteorology
*WIND VELOCITY
*BAROMETRIC PRESSURE
VARIATIONS
SPECTRA
STATISTICAL ANALYSIS
FOURIER ANALYSIS
ARCTIC OCEAN ISLANDS
Bear Island(Norway)
Van Mayen
PE63795N
WU03530
spellingShingle Meteorology
*WIND VELOCITY
*BAROMETRIC PRESSURE
VARIATIONS
SPECTRA
STATISTICAL ANALYSIS
FOURIER ANALYSIS
ARCTIC OCEAN ISLANDS
Bear Island(Norway)
Van Mayen
PE63795N
WU03530
Eller,A I
Blodgett,M L
Long Term Variability of Windspeed.
topic_facet Meteorology
*WIND VELOCITY
*BAROMETRIC PRESSURE
VARIATIONS
SPECTRA
STATISTICAL ANALYSIS
FOURIER ANALYSIS
ARCTIC OCEAN ISLANDS
Bear Island(Norway)
Van Mayen
PE63795N
WU03530
description Underwater acoustic sensors are subject to interfering ambient noise generated by the action of wind on the sea surface. Noise at frequencies above a few hundred Hz generally shows strong correlation with wind speed. A knowledge of the statistical variability of wind-speed is useful for predicting the properties of ambient noise. Values of surface wind speed and atmospheric pressure reported from weather stations at Jan Mayen in the Norwegian Sea and Bear Island in the Barents Sea over a two-year period were examined. It was found that the statistical distribution of wind speeds can be represented approximately as a Rayleigh distribution. Spectral analysis of the time series records of wind speed and pressure shows that most of the variability of these parameters is contributed by synoptic scale variations having periods of from a few days to a few weeks. The annual or seasonal variations has the largest signle Fourier coefficient but represents only a relatively small part of the total variance. (Author)
author2 NAVAL RESEARCH LAB WASHINGTON DC
format Text
author Eller,A I
Blodgett,M L
author_facet Eller,A I
Blodgett,M L
author_sort Eller,A I
title Long Term Variability of Windspeed.
title_short Long Term Variability of Windspeed.
title_full Long Term Variability of Windspeed.
title_fullStr Long Term Variability of Windspeed.
title_full_unstemmed Long Term Variability of Windspeed.
title_sort long term variability of windspeed.
publishDate 1980
url http://www.dtic.mil/docs/citations/ADA091802
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA091802
long_lat ENVELOPE(-67.250,-67.250,-68.151,-68.151)
geographic Arctic
Arctic Ocean
Barents Sea
Bear Island
Jan Mayen
Norway
Norwegian Sea
geographic_facet Arctic
Arctic Ocean
Barents Sea
Bear Island
Jan Mayen
Norway
Norwegian Sea
genre Arctic
Arctic Ocean
Barents Sea
Bear Island
Jan Mayen
Norwegian Sea
genre_facet Arctic
Arctic Ocean
Barents Sea
Bear Island
Jan Mayen
Norwegian Sea
op_source DTIC AND NTIS
op_relation http://www.dtic.mil/docs/citations/ADA091802
op_rights APPROVED FOR PUBLIC RELEASE
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