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dc.contributor.authorKarnauskas, Kristopher B.
dc.contributor.authorJones, Burton H.
dc.date.accessioned2018-09-03T13:21:36Z
dc.date.available2018-09-03T13:21:36Z
dc.date.issued2018-08-21
dc.identifier.citationKarnauskas KB, Jones BH (2018) The Interannual Variability of Sea Surface Temperature in the Red Sea From 35 Years of Satellite and In Situ Observations. Journal of Geophysical Research: Oceans. Available: http://dx.doi.org/10.1029/2017jc013320.
dc.identifier.issn2169-9275
dc.identifier.doi10.1029/2017jc013320
dc.identifier.urihttp://hdl.handle.net/10754/628409
dc.description.abstractFalling between the dynamics of the seasonal cycle and expressions of longer-term trends, the interannual variability of sea surface temperature (SST) in the Red Sea has not received enough attention. With multiple decades of satellite SST observations with spatial resolution capable of resolving patterns of variability within the Red Sea, the time has come for a description and diagnosis of the observed interannual variability of SST in this important semi-enclosed sea. While interannual variability of SST occurs throughout the Red Sea in both summer and winter, the greatest variability is found in the northern Red Sea during winter. Objective analysis reveals two dominant statistical modes of interannual variability of Red Sea SST: a whole-sea mode described by general warm or cool anomalies throughout the Red Sea (∼60% of total variance), and a meridional gradient mode of opposing SST anomalies in the northern and southern Red Sea (∼20% of total variance). The warm phase of the whole-sea mode corresponds to warm surface air temperature anomalies extending across the broader region and local surface wind anomalies opposite to the mean low-level circulation. The whole-sea mode is found to be a regional response to remote forcing by the East Atlantic/Western Russia (EAWR) pattern. The gradient mode, on the other hand, is a manifestation of superimposing (and statistically independent) remote impacts of El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) whereby ENSO drives SST anomalies in the southern Red Sea and the NAO drives SST anomalies in the northern Red Sea.
dc.description.sponsorshipK.B.K. acknowledges support from the Cooperative Institute for Research in Environmental Sciences (CIRES) Innovative Research Program (IRP). B.H.J. was funded by King Abdullah University of Science and Technology (KAUST). All sea surface temperature (SST) data sets used in this study are freely available via the URLs provided in section 2. NCEP/DOE Atmospheric Reanalysis II data were downloaded from the NOAA/ESRL/PSD web page at www.esrl.noaa.gov/psd/data/gridded/. ENSO, NAO and EAWR indices were downloaded from NOAA/NWS/NCEP/CPC web pages at www.cpc.ncep.noaa.gov/data/indices/sstoi.indices, www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/norm.nao.monthly.b5001.current.ascii and ftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/eawr_index.tim, respectively.
dc.publisherAmerican Geophysical Union (AGU)
dc.relation.urlhttps://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2017JC013320
dc.rightsArchived with thanks to Journal of Geophysical Research: Oceans
dc.subjectRed Sea
dc.subjectSST
dc.subjectInterannual
dc.subjectObservations
dc.subjectSatellite
dc.titleThe Interannual Variability of Sea Surface Temperature in the Red Sea from 35 Years of Satellite and In Situ\n Observations
dc.typeArticle
dc.contributor.departmentRed Sea Research Center (RSRC)
dc.identifier.journalJournal of Geophysical Research: Oceans
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Atmospheric and Oceanic Sciences; University of Colorado Boulder; United States of America
dc.contributor.institutionCooperative Institute for Research in Environmental Sciences; University of Colorado Boulder; United States of America
kaust.personJones, Burton
refterms.dateFOA2018-09-10T11:44:06Z
dc.date.published-online2018-08-21
dc.date.published-print2018-08


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