Loading…

Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment

The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine t...

Full description

Saved in:
Bibliographic Details
Published in:Energies (Basel) 2023-04, Vol.16 (9), p.3819
Main Authors: Badger, Merete, Fujita, Aito, Orzel, Krzysztof, Hatfield, Daniel, Kelly, Mark
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13
cites cdi_FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13
container_end_page
container_issue 9
container_start_page 3819
container_title Energies (Basel)
container_volume 16
creator Badger, Merete
Fujita, Aito
Orzel, Krzysztof
Hatfield, Daniel
Kelly, Mark
description The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine the spatial variability of the wind resource. Synthetic Aperture Radar (SAR) observations from satellites can be used for retrieval of wind fields over the ocean at a high spatial resolution. The recent launch of constellations of small SAR satellites by private companies will improve the sampling of SAR scenes significantly over the coming years compared with the current sampling rates offered by multi-purpose SAR missions operated by public space agencies. For the first time, wind fields are retrieved from a series of StriX SAR scenes delivered by Synspective (Japan) and also from Sentinel-1 scenes delivered by the European Space Agency. The satellite winds are compared with wind speed observations from the FINO3 mast in the North Sea. This leads to root-mean-square errors of 1.4–1.8 m s−1 and negative biases of −0.4 m s−1 and −1.0 m s−1, respectively. Although the Geophysical Model Functions (GMF) applied for wind retrievals have not yet been tuned for StriX SAR observations, the wind speed accuracy is satisfactory. Through conditional sampling, we estimate the wind resource from current and future SAR sampling scenarios where the number of SAR satellites in orbit is increasing over time. We find that hourly samples are needed to fully capture the diurnal wind speed variability at the site investigated. A combination of SAR samples from current missions with samples from clusters of small SAR satellites can yield the necessary number of wind speed samples for accurate wind resource estimation. This is particularly important for sites with pronounced diurnal wind speed variability. An additional benefit of small SAR satellites is that wind speed variability can be mapped at the sub-km scale. The very high spatial resolution is valuable for characterizing the wind conditions in the vicinity of existing offshore wind farms.
doi_str_mv 10.3390/en16093819
format article
fullrecord <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_0f59387f40944764a33de74fe9eb5ae7</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A749097165</galeid><doaj_id>oai_doaj_org_article_0f59387f40944764a33de74fe9eb5ae7</doaj_id><sourcerecordid>A749097165</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13</originalsourceid><addsrcrecordid>eNpNkU1PAyEQhjdGE4168ReQeDOpwsIui7em8aNJk5pW45FQGCp1d6lATfz3UtuocGAyvO8zA1MUFwRfUyrwDfSkxoI2RBwUJ0SIekAwp4f_4uPiPMYVzotSQik9Kd5fXW_QDFJw8KlaZIPv0Mj3MUHbquRyhLxF8061LZoPZ2iutjcuQbxFTz5Bn9zW5gOaWhvffAC0R0a_CRrQMEaIscvCs-LIqjbC-f48LV7u755Hj4PJ9GE8Gk4GmmGcBlVJRNVobCsNxjJSiYobQalZmFqAUbi2Fa8bxjQjHFNgRFjMLBDTNGWpCD0txjuu8Wol18F1KnxJr5z8SfiwlCokp1uQuUj-MG4ZFozxmqlcBniGCVhUCnhmXe5Y6-A_NhCTXOVn9bl9WTakZNmMm6y63qmWKkNdb30KSudtoHPa92Bdzg85E1hwUlfZcLUz6OBjDGB_2yRYbocp_4ZJvwH5SJAm</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2812438708</pqid></control><display><type>article</type><title>Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment</title><source>Publicly Available Content (ProQuest)</source><creator>Badger, Merete ; Fujita, Aito ; Orzel, Krzysztof ; Hatfield, Daniel ; Kelly, Mark</creator><creatorcontrib>Badger, Merete ; Fujita, Aito ; Orzel, Krzysztof ; Hatfield, Daniel ; Kelly, Mark</creatorcontrib><description>The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine the spatial variability of the wind resource. Synthetic Aperture Radar (SAR) observations from satellites can be used for retrieval of wind fields over the ocean at a high spatial resolution. The recent launch of constellations of small SAR satellites by private companies will improve the sampling of SAR scenes significantly over the coming years compared with the current sampling rates offered by multi-purpose SAR missions operated by public space agencies. For the first time, wind fields are retrieved from a series of StriX SAR scenes delivered by Synspective (Japan) and also from Sentinel-1 scenes delivered by the European Space Agency. The satellite winds are compared with wind speed observations from the FINO3 mast in the North Sea. This leads to root-mean-square errors of 1.4–1.8 m s−1 and negative biases of −0.4 m s−1 and −1.0 m s−1, respectively. Although the Geophysical Model Functions (GMF) applied for wind retrievals have not yet been tuned for StriX SAR observations, the wind speed accuracy is satisfactory. Through conditional sampling, we estimate the wind resource from current and future SAR sampling scenarios where the number of SAR satellites in orbit is increasing over time. We find that hourly samples are needed to fully capture the diurnal wind speed variability at the site investigated. A combination of SAR samples from current missions with samples from clusters of small SAR satellites can yield the necessary number of wind speed samples for accurate wind resource estimation. This is particularly important for sites with pronounced diurnal wind speed variability. An additional benefit of small SAR satellites is that wind speed variability can be mapped at the sub-km scale. The very high spatial resolution is valuable for characterizing the wind conditions in the vicinity of existing offshore wind farms.</description><identifier>ISSN: 1996-1073</identifier><identifier>EISSN: 1996-1073</identifier><identifier>DOI: 10.3390/en16093819</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Alternative energy sources ; Artificial satellites ; Coasts ; Diurnal ; Marine environment ; Numerical models ; Offshore ; Offshore energy sources ; resource assessment ; Sampling ; satellite ; Satellite constellations ; Satellites ; Sensors ; Spatial discrimination ; Spatial resolution ; Synthetic aperture radar ; Synthetic Aperture Radar (SAR) ; Time series ; Variability ; wind energy ; Wind farms ; Wind power ; wind retrieval ; Wind speed</subject><ispartof>Energies (Basel), 2023-04, Vol.16 (9), p.3819</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13</citedby><cites>FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13</cites><orcidid>0000-0002-2072-8619 ; 0000-0001-5576-6669 ; 0000-0003-2882-4450 ; 0000-0002-5118-9988</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2812438708/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2812438708?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Badger, Merete</creatorcontrib><creatorcontrib>Fujita, Aito</creatorcontrib><creatorcontrib>Orzel, Krzysztof</creatorcontrib><creatorcontrib>Hatfield, Daniel</creatorcontrib><creatorcontrib>Kelly, Mark</creatorcontrib><title>Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment</title><title>Energies (Basel)</title><description>The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine the spatial variability of the wind resource. Synthetic Aperture Radar (SAR) observations from satellites can be used for retrieval of wind fields over the ocean at a high spatial resolution. The recent launch of constellations of small SAR satellites by private companies will improve the sampling of SAR scenes significantly over the coming years compared with the current sampling rates offered by multi-purpose SAR missions operated by public space agencies. For the first time, wind fields are retrieved from a series of StriX SAR scenes delivered by Synspective (Japan) and also from Sentinel-1 scenes delivered by the European Space Agency. The satellite winds are compared with wind speed observations from the FINO3 mast in the North Sea. This leads to root-mean-square errors of 1.4–1.8 m s−1 and negative biases of −0.4 m s−1 and −1.0 m s−1, respectively. Although the Geophysical Model Functions (GMF) applied for wind retrievals have not yet been tuned for StriX SAR observations, the wind speed accuracy is satisfactory. Through conditional sampling, we estimate the wind resource from current and future SAR sampling scenarios where the number of SAR satellites in orbit is increasing over time. We find that hourly samples are needed to fully capture the diurnal wind speed variability at the site investigated. A combination of SAR samples from current missions with samples from clusters of small SAR satellites can yield the necessary number of wind speed samples for accurate wind resource estimation. This is particularly important for sites with pronounced diurnal wind speed variability. An additional benefit of small SAR satellites is that wind speed variability can be mapped at the sub-km scale. The very high spatial resolution is valuable for characterizing the wind conditions in the vicinity of existing offshore wind farms.</description><subject>Alternative energy sources</subject><subject>Artificial satellites</subject><subject>Coasts</subject><subject>Diurnal</subject><subject>Marine environment</subject><subject>Numerical models</subject><subject>Offshore</subject><subject>Offshore energy sources</subject><subject>resource assessment</subject><subject>Sampling</subject><subject>satellite</subject><subject>Satellite constellations</subject><subject>Satellites</subject><subject>Sensors</subject><subject>Spatial discrimination</subject><subject>Spatial resolution</subject><subject>Synthetic aperture radar</subject><subject>Synthetic Aperture Radar (SAR)</subject><subject>Time series</subject><subject>Variability</subject><subject>wind energy</subject><subject>Wind farms</subject><subject>Wind power</subject><subject>wind retrieval</subject><subject>Wind speed</subject><issn>1996-1073</issn><issn>1996-1073</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkU1PAyEQhjdGE4168ReQeDOpwsIui7em8aNJk5pW45FQGCp1d6lATfz3UtuocGAyvO8zA1MUFwRfUyrwDfSkxoI2RBwUJ0SIekAwp4f_4uPiPMYVzotSQik9Kd5fXW_QDFJw8KlaZIPv0Mj3MUHbquRyhLxF8061LZoPZ2iutjcuQbxFTz5Bn9zW5gOaWhvffAC0R0a_CRrQMEaIscvCs-LIqjbC-f48LV7u755Hj4PJ9GE8Gk4GmmGcBlVJRNVobCsNxjJSiYobQalZmFqAUbi2Fa8bxjQjHFNgRFjMLBDTNGWpCD0txjuu8Wol18F1KnxJr5z8SfiwlCokp1uQuUj-MG4ZFozxmqlcBniGCVhUCnhmXe5Y6-A_NhCTXOVn9bl9WTakZNmMm6y63qmWKkNdb30KSudtoHPa92Bdzg85E1hwUlfZcLUz6OBjDGB_2yRYbocp_4ZJvwH5SJAm</recordid><startdate>20230429</startdate><enddate>20230429</enddate><creator>Badger, Merete</creator><creator>Fujita, Aito</creator><creator>Orzel, Krzysztof</creator><creator>Hatfield, Daniel</creator><creator>Kelly, Mark</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-2072-8619</orcidid><orcidid>https://orcid.org/0000-0001-5576-6669</orcidid><orcidid>https://orcid.org/0000-0003-2882-4450</orcidid><orcidid>https://orcid.org/0000-0002-5118-9988</orcidid></search><sort><creationdate>20230429</creationdate><title>Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment</title><author>Badger, Merete ; Fujita, Aito ; Orzel, Krzysztof ; Hatfield, Daniel ; Kelly, Mark</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Alternative energy sources</topic><topic>Artificial satellites</topic><topic>Coasts</topic><topic>Diurnal</topic><topic>Marine environment</topic><topic>Numerical models</topic><topic>Offshore</topic><topic>Offshore energy sources</topic><topic>resource assessment</topic><topic>Sampling</topic><topic>satellite</topic><topic>Satellite constellations</topic><topic>Satellites</topic><topic>Sensors</topic><topic>Spatial discrimination</topic><topic>Spatial resolution</topic><topic>Synthetic aperture radar</topic><topic>Synthetic Aperture Radar (SAR)</topic><topic>Time series</topic><topic>Variability</topic><topic>wind energy</topic><topic>Wind farms</topic><topic>Wind power</topic><topic>wind retrieval</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Badger, Merete</creatorcontrib><creatorcontrib>Fujita, Aito</creatorcontrib><creatorcontrib>Orzel, Krzysztof</creatorcontrib><creatorcontrib>Hatfield, Daniel</creatorcontrib><creatorcontrib>Kelly, Mark</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Directory of Open Access Journals</collection><jtitle>Energies (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Badger, Merete</au><au>Fujita, Aito</au><au>Orzel, Krzysztof</au><au>Hatfield, Daniel</au><au>Kelly, Mark</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment</atitle><jtitle>Energies (Basel)</jtitle><date>2023-04-29</date><risdate>2023</risdate><volume>16</volume><issue>9</issue><spage>3819</spage><pages>3819-</pages><issn>1996-1073</issn><eissn>1996-1073</eissn><abstract>The planning of offshore wind energy projects requires wind observations over long periods for the establishment of wind speed distributions. In the marine environment, high-quality in situ observations are sparse and restricted to point locations. Numerical modeling is typically used to determine the spatial variability of the wind resource. Synthetic Aperture Radar (SAR) observations from satellites can be used for retrieval of wind fields over the ocean at a high spatial resolution. The recent launch of constellations of small SAR satellites by private companies will improve the sampling of SAR scenes significantly over the coming years compared with the current sampling rates offered by multi-purpose SAR missions operated by public space agencies. For the first time, wind fields are retrieved from a series of StriX SAR scenes delivered by Synspective (Japan) and also from Sentinel-1 scenes delivered by the European Space Agency. The satellite winds are compared with wind speed observations from the FINO3 mast in the North Sea. This leads to root-mean-square errors of 1.4–1.8 m s−1 and negative biases of −0.4 m s−1 and −1.0 m s−1, respectively. Although the Geophysical Model Functions (GMF) applied for wind retrievals have not yet been tuned for StriX SAR observations, the wind speed accuracy is satisfactory. Through conditional sampling, we estimate the wind resource from current and future SAR sampling scenarios where the number of SAR satellites in orbit is increasing over time. We find that hourly samples are needed to fully capture the diurnal wind speed variability at the site investigated. A combination of SAR samples from current missions with samples from clusters of small SAR satellites can yield the necessary number of wind speed samples for accurate wind resource estimation. This is particularly important for sites with pronounced diurnal wind speed variability. An additional benefit of small SAR satellites is that wind speed variability can be mapped at the sub-km scale. The very high spatial resolution is valuable for characterizing the wind conditions in the vicinity of existing offshore wind farms.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/en16093819</doi><orcidid>https://orcid.org/0000-0002-2072-8619</orcidid><orcidid>https://orcid.org/0000-0001-5576-6669</orcidid><orcidid>https://orcid.org/0000-0003-2882-4450</orcidid><orcidid>https://orcid.org/0000-0002-5118-9988</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1996-1073
ispartof Energies (Basel), 2023-04, Vol.16 (9), p.3819
issn 1996-1073
1996-1073
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_0f59387f40944764a33de74fe9eb5ae7
source Publicly Available Content (ProQuest)
subjects Alternative energy sources
Artificial satellites
Coasts
Diurnal
Marine environment
Numerical models
Offshore
Offshore energy sources
resource assessment
Sampling
satellite
Satellite constellations
Satellites
Sensors
Spatial discrimination
Spatial resolution
Synthetic aperture radar
Synthetic Aperture Radar (SAR)
Time series
Variability
wind energy
Wind farms
Wind power
wind retrieval
Wind speed
title Wind Retrieval from Constellations of Small SAR Satellites: Potential for Offshore Wind Resource Assessment
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T02%3A26%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Wind%20Retrieval%20from%20Constellations%20of%20Small%20SAR%20Satellites:%20Potential%20for%20Offshore%20Wind%20Resource%20Assessment&rft.jtitle=Energies%20(Basel)&rft.au=Badger,%20Merete&rft.date=2023-04-29&rft.volume=16&rft.issue=9&rft.spage=3819&rft.pages=3819-&rft.issn=1996-1073&rft.eissn=1996-1073&rft_id=info:doi/10.3390/en16093819&rft_dat=%3Cgale_doaj_%3EA749097165%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c400t-521958c0f5cedf415957d933dbd69eda06f576844c41703e419f04fe1d8822a13%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2812438708&rft_id=info:pmid/&rft_galeid=A749097165&rfr_iscdi=true