The Global Wind Resource Observed by Scatterometer
A 27-year-long calibrated multi-mission scatterometer data set is used to determine the global basin-scale and near-coastal wind resource. In addition to mean and percentile values, the analysis also determines the global values of both 50- and 100-year return period wind speeds. The analysis clearl...
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Online Access: | https://doi.org/10.3390/rs12182920 https://doaj.org/article/a5c2c8dc578b452c893dc8a8c212b357 |
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ftdoajarticles:oai:doaj.org/article:a5c2c8dc578b452c893dc8a8c212b357 2023-05-15T17:29:54+02:00 The Global Wind Resource Observed by Scatterometer Ian R. Young Ebru Kirezci Agustinus Ribal 2020-09-01T00:00:00Z https://doi.org/10.3390/rs12182920 https://doaj.org/article/a5c2c8dc578b452c893dc8a8c212b357 EN eng MDPI AG https://www.mdpi.com/2072-4292/12/18/2920 https://doaj.org/toc/2072-4292 doi:10.3390/rs12182920 2072-4292 https://doaj.org/article/a5c2c8dc578b452c893dc8a8c212b357 Remote Sensing, Vol 12, Iss 2920, p 2920 (2020) wind speed extreme value analysis scatterometer Science Q article 2020 ftdoajarticles https://doi.org/10.3390/rs12182920 2022-12-31T15:06:24Z A 27-year-long calibrated multi-mission scatterometer data set is used to determine the global basin-scale and near-coastal wind resource. In addition to mean and percentile values, the analysis also determines the global values of both 50- and 100-year return period wind speeds. The analysis clearly shows the seasonal variability of wind speeds and the differing response of the two hemispheres. The maximum wind speeds in each hemisphere are comparable but there is a much larger seasonal cycle in the northern hemisphere. As a result, the southern hemisphere has a more consistent year-round wind climate. Hence, coastal regions of southern Africa, southern Australia, New Zealand and southern South America appear particularly suited to coastal and offshore wind energy projects. The extreme value analysis shows that the highest extreme wind speeds occur in the North Atlantic Ocean with extreme wind regions concentrated along the western boundaries of the North Atlantic and North Pacific Oceans and the Indian Ocean sector of the Southern Ocean. The signature of tropical cyclones is clearly observed in each of the well-known tropical cyclone basins. Article in Journal/Newspaper North Atlantic Southern Ocean Directory of Open Access Journals: DOAJ Articles Southern Ocean Pacific Indian New Zealand Remote Sensing 12 18 2920 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
wind speed extreme value analysis scatterometer Science Q |
spellingShingle |
wind speed extreme value analysis scatterometer Science Q Ian R. Young Ebru Kirezci Agustinus Ribal The Global Wind Resource Observed by Scatterometer |
topic_facet |
wind speed extreme value analysis scatterometer Science Q |
description |
A 27-year-long calibrated multi-mission scatterometer data set is used to determine the global basin-scale and near-coastal wind resource. In addition to mean and percentile values, the analysis also determines the global values of both 50- and 100-year return period wind speeds. The analysis clearly shows the seasonal variability of wind speeds and the differing response of the two hemispheres. The maximum wind speeds in each hemisphere are comparable but there is a much larger seasonal cycle in the northern hemisphere. As a result, the southern hemisphere has a more consistent year-round wind climate. Hence, coastal regions of southern Africa, southern Australia, New Zealand and southern South America appear particularly suited to coastal and offshore wind energy projects. The extreme value analysis shows that the highest extreme wind speeds occur in the North Atlantic Ocean with extreme wind regions concentrated along the western boundaries of the North Atlantic and North Pacific Oceans and the Indian Ocean sector of the Southern Ocean. The signature of tropical cyclones is clearly observed in each of the well-known tropical cyclone basins. |
format |
Article in Journal/Newspaper |
author |
Ian R. Young Ebru Kirezci Agustinus Ribal |
author_facet |
Ian R. Young Ebru Kirezci Agustinus Ribal |
author_sort |
Ian R. Young |
title |
The Global Wind Resource Observed by Scatterometer |
title_short |
The Global Wind Resource Observed by Scatterometer |
title_full |
The Global Wind Resource Observed by Scatterometer |
title_fullStr |
The Global Wind Resource Observed by Scatterometer |
title_full_unstemmed |
The Global Wind Resource Observed by Scatterometer |
title_sort |
global wind resource observed by scatterometer |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/rs12182920 https://doaj.org/article/a5c2c8dc578b452c893dc8a8c212b357 |
geographic |
Southern Ocean Pacific Indian New Zealand |
geographic_facet |
Southern Ocean Pacific Indian New Zealand |
genre |
North Atlantic Southern Ocean |
genre_facet |
North Atlantic Southern Ocean |
op_source |
Remote Sensing, Vol 12, Iss 2920, p 2920 (2020) |
op_relation |
https://www.mdpi.com/2072-4292/12/18/2920 https://doaj.org/toc/2072-4292 doi:10.3390/rs12182920 2072-4292 https://doaj.org/article/a5c2c8dc578b452c893dc8a8c212b357 |
op_doi |
https://doi.org/10.3390/rs12182920 |
container_title |
Remote Sensing |
container_volume |
12 |
container_issue |
18 |
container_start_page |
2920 |
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1766125139113541632 |