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Author Ali, M.M. ; Bhat, G.S. ; Long, D.G. ; Bharadwaj, S. ; Bourassa, M.A.
Title Estimating Wind Stress at the Ocean Surface From Scatterometer Observations Type $loc['typeJournal Article']
Year 2013 Publication IEEE Geoscience and Remote Sensing Letters Abbreviated Journal IEEE Geosci. Remote Sensing Lett.
Volume 10
Issue 5
Pages 1129-1132
Keywords Atmospheric stability ; neutral stability ; scatterometer ; wind stress
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1545-598X
ISBN Medium
Area Expedition Conference
Funding NASA, OVWST
Approved $loc['no']
Call Number COAPS @ mfield @
Serial 184
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Author Ali, M.M. ; Bourassa, M.A. ; Bhowmick, S.A. ; Sharma, R. ; Niharika, K.
Title Retrieval of Wind Stress at the Ocean Surface From AltiKa Measurements Type $loc['typeJournal Article']
Year 2016 Publication IEEE Geoscience and Remote Sensing Letters Abbreviated Journal IEEE Geosci. Remote Sensing Lett.
Volume 13
Issue 6
Pages 821-825
Keywords AltiKa ; artificial neural networks (ANNs) ; wind stress
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1545-598X
ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @
Serial 29
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Author Briggs, K.
Title ENSO Event Reproduction: A Comparison of an EOF vs. A Cyclostationary (CSEOF) Approach Type $loc['typeManuscript']
Year 2006 Publication Abbreviated Journal
Volume Issue Pages
Keywords EOF, Autoregression, Wind Stress, Sea Level Height, SST, ENSO, Regression, CSEOF, Cyclostationary
Abstract In past studies, El Niño-Southern Oscillation (ENSO) events have been linked to devastating weather extremes. Climate modeling of ENSO is often dependent on limited records of the pertinent physical variables, thus longer records of these variables is desirable. Noisy signals, such as monthly sea surface temperature, are good candidates for reproduction by several existing auto-regression techniques. Through auto-regression, influential principal component modes are broken down into a series of time points that are each dependent upon an optimal weighting of the surrounding points. Using these unique numerical relationships, a noisy signal can be reproduced by thus processing the leading modes and adding an artificial record of properly distributed noise. Statistical measures of important ENSO regions suggest that the nature of oceanic and atmospheric anomalous events is cyclic with respect to certain timescales; for example, the monthly timescale. To detect ENSO signals in the presence of a varying background noise field, the detection method should take into account the signal's strong phase-locking with this nested variation. Cyclostationary Emperical Orthogonal Functions (CSEOFs) are built upon the idea of nested cycles, unlike traditional EOFs, which incorporate a design that is better detailed for stationary processes. In this study, both EOF and CSEOF modes of a 50-year Pacific SST record are processed using an auto-regression technique, and several sets of artificial SST records are constructed. Appropriate statistical indices are applied to these artificial time series to ensure an acceptable consistency with the real record, and then artificial data is produced using the artificial time series. In all cases, the cyclostationary approach produces more realistic warm ENSO events with respect to timing, strength, and other traits than does the stationary approach. However, both methods produce only a fair representation of cold events, suggesting that further study is necessary for improvement of La Niña modeling. Shorter records of variables such as sea level height and Pacific wind stress anomalies can hinder the usefulness of auto-regression, owing to time point dependence on surrounding points. Using a regression technique to find an evolutionary consistency (i.e. physically consistent patterns) between one of these variables and a variable with a longer record (such as SST) can eliminate this problem. Once a regression relationship is found between two variables, the variable with the shorter record can be re-written to match the time evolution of the variable with the longer record. Here regression, both EOF and CSEOF, is performed on both sea surface temperature and sea level height (a 20-year record), and sea surface temperature and wind stress (a 39-year record). Once the regression relationships are found, artificial SST time series are incorporated in place of the original time series to produce several artificial 50-year SLH and wind stress data sets. 5 Pacific regions are chosen, and statistics and behavior of the artificial sets within these regions are compared to those of the original data. Once again the cyclostationary approach fares better than the stationary. In particular the EOF assumption of cross correlational symmetry fails to capture the direction-dependence of ENSO evolution, causing inconsistent ENSO behavior. This renders an EOF method insufficient for climate modeling and prediction, and implies that a better aim is to incorporate physical cyclic features via a cyclostationary method.
Address Department of Meteorology
Corporate Author Thesis $loc['Master's thesis']
Publisher Florida State University
Place of Publication Tallahassee, FL
Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @
Serial 614
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Author Kara, A.B. ; Rochford, P.A. ; Hurlburt, H.E.
Title Air-Sea Flux Estimates And The 1997-1998 Enso Event Type $loc['typeJournal Article']
Year 2002 Publication Boundary-Layer Meteorology Abbreviated Journal Boundary-Layer Meteorology
Volume 103
Issue 3
Pages 439-458
Keywords bulk formulae ; El Nino ; La Nina ; latent and sensible heat flux ; ocean mixed-layer depth ; wind stress
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0006-8314
ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @
Serial 495
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Author Nof, D. ; Jia, Y. ; Chassignet, E. ; Bozec, A.
Title Fast Wind-Induced Migration of Leddies in the South China Sea Type $loc['typeJournal Article']
Year 2011 Publication Journal of Physical Oceanography Abbreviated Journal J. Phys. Oceanogr.
Volume 41
Issue 9
Pages 1683-1693
Keywords Eddies ; Seas ; gulfs ; bays ; Wind stress ; Numerical analysis/modeling ; Monsoons
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-3670
ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @
Serial 324
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Author Smith, S.R. ; Lopez, N. ; Bourassa, M.A.
Title SAMOS air-sea fluxes: 2005-2014 Type $loc['typeJournal Article']
Year 2016 Publication Geoscience Data Journal Abbreviated Journal Geosci. Data J.
Volume 3
Issue 1
Pages 9-19
Keywords air-sea flux ; marine meteorology ; marine climatology ; heat flux ; wind stress
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2049-6060
ISBN Medium
Area Expedition Conference
Funding Approved $loc['no']
Call Number COAPS @ mfield @
Serial 52
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