Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models
The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehi...
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ftdoajarticles:oai:doaj.org/article:f74c71ee7e004c90940793cb0e16f5ce 2024-01-14T10:04:07+01:00 Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models Jorge Vazquez-Cuervo Chelle Gentemann Wenqing Tang Dustin Carroll Hong Zhang Dimitris Menemenlis Jose Gomez-Valdes Marouan Bouali Michael Steele 2021-02-01T00:00:00Z https://doi.org/10.3390/rs13050831 https://doaj.org/article/f74c71ee7e004c90940793cb0e16f5ce EN eng MDPI AG https://www.mdpi.com/2072-4292/13/5/831 https://doaj.org/toc/2072-4292 doi:10.3390/rs13050831 2072-4292 https://doaj.org/article/f74c71ee7e004c90940793cb0e16f5ce Remote Sensing, Vol 13, Iss 5, p 831 (2021) sea surface salinity validation coastal Science Q article 2021 ftdoajarticles https://doi.org/10.3390/rs13050831 2023-12-17T01:45:14Z The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations. Article in Journal/Newspaper Arctic Arctic Ocean Sea ice Yukon river Yukon Directory of Open Access Journals: DOAJ Articles Arctic Arctic Ocean Carroll ENVELOPE(-81.183,-81.183,50.800,50.800) Yukon Remote Sensing 13 5 831 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
sea surface salinity validation coastal Science Q |
spellingShingle |
sea surface salinity validation coastal Science Q Jorge Vazquez-Cuervo Chelle Gentemann Wenqing Tang Dustin Carroll Hong Zhang Dimitris Menemenlis Jose Gomez-Valdes Marouan Bouali Michael Steele Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
topic_facet |
sea surface salinity validation coastal Science Q |
description |
The Arctic Ocean is one of the most important and challenging regions to observe—it experiences the largest changes from climate warming, and at the same time is one of the most difficult to sample because of sea ice and extreme cold temperatures. Two NASA-sponsored deployments of the Saildrone vehicle provided a unique opportunity for validating sea-surface salinity (SSS) derived from three separate products that use data from the Soil Moisture Active Passive (SMAP) satellite. To examine possible issues in resolving mesoscale-to-submesoscale variability, comparisons were also made with two versions of the Estimating the Circulation and Climate of the Ocean (ECCO) model (Carroll, D; Menmenlis, D; Zhang, H.). The results indicate that the three SMAP products resolve the runoff signal associated with the Yukon River, with high correlation between SMAP products and Saildrone SSS. Spectral slopes, overall, replicate the −2.0 slopes associated with mesoscale-submesoscale variability. Statistically significant spatial coherences exist for all products, with peaks close to 100 km. Based on these encouraging results, future research should focus on improving derivations of satellite-derived SSS in the Arctic Ocean and integrating model results to complement remote sensing observations. |
format |
Article in Journal/Newspaper |
author |
Jorge Vazquez-Cuervo Chelle Gentemann Wenqing Tang Dustin Carroll Hong Zhang Dimitris Menemenlis Jose Gomez-Valdes Marouan Bouali Michael Steele |
author_facet |
Jorge Vazquez-Cuervo Chelle Gentemann Wenqing Tang Dustin Carroll Hong Zhang Dimitris Menemenlis Jose Gomez-Valdes Marouan Bouali Michael Steele |
author_sort |
Jorge Vazquez-Cuervo |
title |
Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
title_short |
Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
title_full |
Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
title_fullStr |
Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
title_full_unstemmed |
Using Saildrones to Validate Arctic Sea-Surface Salinity from the SMAP Satellite and from Ocean Models |
title_sort |
using saildrones to validate arctic sea-surface salinity from the smap satellite and from ocean models |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doi.org/10.3390/rs13050831 https://doaj.org/article/f74c71ee7e004c90940793cb0e16f5ce |
long_lat |
ENVELOPE(-81.183,-81.183,50.800,50.800) |
geographic |
Arctic Arctic Ocean Carroll Yukon |
geographic_facet |
Arctic Arctic Ocean Carroll Yukon |
genre |
Arctic Arctic Ocean Sea ice Yukon river Yukon |
genre_facet |
Arctic Arctic Ocean Sea ice Yukon river Yukon |
op_source |
Remote Sensing, Vol 13, Iss 5, p 831 (2021) |
op_relation |
https://www.mdpi.com/2072-4292/13/5/831 https://doaj.org/toc/2072-4292 doi:10.3390/rs13050831 2072-4292 https://doaj.org/article/f74c71ee7e004c90940793cb0e16f5ce |
op_doi |
https://doi.org/10.3390/rs13050831 |
container_title |
Remote Sensing |
container_volume |
13 |
container_issue |
5 |
container_start_page |
831 |
_version_ |
1788058759760707584 |