Data · collection · 2016
Construction of long-term data set of sea surface wind speed/stress vectors by continuous satellite observations
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Using scatterometer data from three sources (QSCAT/SeaWinds, MetOp-A/ASCAT, and ERS-1,2), we construct a gridded data set of wind/wind-stress vectors with continuous time series for investigation of long-term variation in ocean surface wind.
Description
The present study investigates differences in wind fields between two products in the overlapping periods 2008 (for QSCAT and ASCAT products) and 2000 (for QSCAT and ERS products).
Systematic differences are found in the meridional components, showing that anomalies in the ASCAT and ERS products from that in QSCAT’s are positive (northward) in the northern hemisphere and negative (southward) in the southern hemisphere, corresponding to poleward anomalies. These poleward anomalies are also found in the monthly mean fields, and less clearly in the daily mean ones, in which there are meridionally striped patterns in the mid-latitude areas, suggesting that they are due to differences in satellite orbits and measurement timings.
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Similar comparisons are also made in the wind-stress curl field, which is a driving force of oceanic currents. The poleward anomalies are not so marked in the annual mean field of the wind-stress curl field, but there are meridionally striped features in the mid-latitude areas. Time series of the wind-stress curl are made in the subtropical and subarctic circulation regions of the North Pacific for investigation of long-term variation over several years using corrected times series.
The results reveals that the magnitude of wind-stress curl in both regions has been weakening since the beginning of this century, indicating that they would be a result of weakening of the westerlies.
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- Repository landing page figshare.com/collections/Construction_of_long_term_data_set_of_sea_surface_… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.2182170.v1 ↗
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Documentation and papers
- CC-BY creativecommons.org/licenses/by/3.0/us ↗
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- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.2182170.v1 ↗
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- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.2182170.v1 ↗
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Topics
- Stated by source
- Biological sciences · Chemical sciences · Earth and related environmental sciences · Physical sciences
- From keywords
- Ecology · Inorganic chemistry
- Inferred from text
- Satellite remote sensing 65%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.2182170.v1 | 11 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].fos:chemical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:earth-and-related-environmental-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:physical-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[modality].local:modality:remote-sensing | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (65%) |
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