File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Estimation of the Ocean Water Albedo From Remote Sensing and Meteorological Reanalysis Data

TitleEstimation of the Ocean Water Albedo From Remote Sensing and Meteorological Reanalysis Data
Authors
KeywordsOcean water albedo (OWA)
sun glint
water-leaving reflectance
whitecaps
Issue Date2016
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2016, v. 54, n. 2, p. 850-868 How to Cite?
AbstractOcean water albedo (OWA) plays an important role in the global climate variation. Compared with the achievements in land surface albedo studies, the global distributions of ocean water and sea ice albedo are seldom addressed. This study designed an operational global OWA algorithm based on the three-component reflectance model of the ocean water: sun glint, whitecaps, and water-leaving reflectance. The related achievements in these three areas are reviewed and integrated into the operational algorithm. After the sensitive analysis, the algorithm is compared with previous studies and validated with ground observations at COVE site located 25 km east of Virginia Beach (36.91° N, 75.71° W), and the results indicate that the proposed algorithm is generally consistent with previous parameterization scheme. As an example, the global OWAs in summer and winter 2011 are generated using the remote sensing reflectance data sets via the Moderate Resolution Imaging Spectroradiometer and Modern-Era Retrospective analysis for Research and Applications meteorological reanalysis data set. The generated product includes instantaneous (e.g., local noon) and daily mean OWAs under both clear-sky and white-sky conditions. Upon the examples, the local noon clear-sky OWA shows a significant latitude variation due to the dominance of the solar angle, whereas the white-sky OWA is sensitive to wind speeds and optical constituents. The global distribution of the daily mean OWA exhibits a similar trend to the local noon OWA. However, the daily mean clear-sky OWA is significantly larger than the local noon OWA; this finding should be noted when using OWA products for energy balance research. Additionally, all forms of OWA products exhibit increase in coastal areas with high input of terrestrial matters.
Persistent Identifierhttp://hdl.handle.net/10722/321643
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFeng, Youbin-
dc.contributor.authorLiu, Qiang-
dc.contributor.authorQu, Ying-
dc.contributor.authorLiang, Shunlin-
dc.date.accessioned2022-11-03T02:20:27Z-
dc.date.available2022-11-03T02:20:27Z-
dc.date.issued2016-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2016, v. 54, n. 2, p. 850-868-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/321643-
dc.description.abstractOcean water albedo (OWA) plays an important role in the global climate variation. Compared with the achievements in land surface albedo studies, the global distributions of ocean water and sea ice albedo are seldom addressed. This study designed an operational global OWA algorithm based on the three-component reflectance model of the ocean water: sun glint, whitecaps, and water-leaving reflectance. The related achievements in these three areas are reviewed and integrated into the operational algorithm. After the sensitive analysis, the algorithm is compared with previous studies and validated with ground observations at COVE site located 25 km east of Virginia Beach (36.91° N, 75.71° W), and the results indicate that the proposed algorithm is generally consistent with previous parameterization scheme. As an example, the global OWAs in summer and winter 2011 are generated using the remote sensing reflectance data sets via the Moderate Resolution Imaging Spectroradiometer and Modern-Era Retrospective analysis for Research and Applications meteorological reanalysis data set. The generated product includes instantaneous (e.g., local noon) and daily mean OWAs under both clear-sky and white-sky conditions. Upon the examples, the local noon clear-sky OWA shows a significant latitude variation due to the dominance of the solar angle, whereas the white-sky OWA is sensitive to wind speeds and optical constituents. The global distribution of the daily mean OWA exhibits a similar trend to the local noon OWA. However, the daily mean clear-sky OWA is significantly larger than the local noon OWA; this finding should be noted when using OWA products for energy balance research. Additionally, all forms of OWA products exhibit increase in coastal areas with high input of terrestrial matters.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectOcean water albedo (OWA)-
dc.subjectsun glint-
dc.subjectwater-leaving reflectance-
dc.subjectwhitecaps-
dc.titleEstimation of the Ocean Water Albedo From Remote Sensing and Meteorological Reanalysis Data-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2015.2468054-
dc.identifier.scopuseid_2-s2.0-84940732889-
dc.identifier.volume54-
dc.identifier.issue2-
dc.identifier.spage850-
dc.identifier.epage868-
dc.identifier.isiWOS:000370350100019-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats