dc.contributor.author | Hoseini, Mostafa | |
dc.contributor.author | Nahavandchi, Hossein | |
dc.date.accessioned | 2023-02-21T15:28:47Z | |
dc.date.available | 2023-02-21T15:28:47Z | |
dc.date.created | 2022-11-09T10:55:01Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Remote Sensing of Environment. 2022, 282 . | en_US |
dc.identifier.issn | 0034-4257 | |
dc.identifier.uri | https://hdl.handle.net/11250/3052868 | |
dc.description.abstract | The detectability of ocean surface currents in global navigation satellite system reflectometry (GNSS-R) observations is analyzed. We use a large dataset of spaceborne GNSS-R measurements from NASA cyclone GNSS (CYGNSS) mission. The data is collocated with ocean wind and near-surface current measurements. Our analysis reveals clear responses of the GNSS-R to the presence of currents. The response depends on the wind conditions and is more prominent for wind speeds below 6 m/s. A current velocity of 0.5 m/s under an opposing wind can, on average, suppress the GNSS-R by 0.8 decibels for low incidence angles. The interaction of the same current with a codirectional wind can enhance by almost the same amount. This enhancement is most visible at high incidence angles. We develop a model that improves the prediction of the GNSS-R in the presence of surface currents. The detected signatures of wind–current interactions highlight the potential of GNSS-R sensors onboard small satellites for observing ocean surface currents. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier Science | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | The potential of spaceborne GNSS reflectometry for detecting ocean surface currents | en_US |
dc.title.alternative | The potential of spaceborne GNSS reflectometry for detecting ocean surface currents | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.pagenumber | 11 | en_US |
dc.source.volume | 282 | en_US |
dc.source.journal | Remote Sensing of Environment | en_US |
dc.identifier.doi | 10.1016/j.rse.2022.113256 | |
dc.identifier.cristin | 2071090 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |