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contributor authorNardelli, Bruno Buongiorno
contributor authorSantoleri, Rosalia
date accessioned2017-06-09T17:22:57Z
date available2017-06-09T17:22:57Z
date copyright2005/11/01
date issued2005
identifier issn0739-0572
identifier otherams-84176.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4227483
description abstractDifferent methods for the extrapolation of vertical profiles from sea surface measurements have been tested on 14 yr of conductivity?temperature?depth (CTD) data collected within the Hawaii Ocean Time-series (HOT) program at A Long-Term Oligotrophic Habitat Assessment (ALOHA) station in the North Pacific Ocean. A new technique, called multivariate EOF reconstruction (mEOF-R), has been proposed. The mEOF-R technique is similar to the previously developed coupled pattern reconstruction (CPR) technique and relies on the availability of surface measurements and historical profiles of salinity, temperature, and steric heights. The method is based on the multivariate EOF analysis of the vertical profiles of the three parameters and on the assumption that only a few modes are needed to explain most of the variance/covariance of the fields. The performances of CPR, single EOF reconstruction (sEOF-R), and mEOF-R have been compared with the results of residual GEM techniques and with ad hoc climatologies, stressing the potential of each method in relation to the length of the time series used to train the models and to the accuracy expected from planned satellite missions for the measurement of surface salinity, sea level, and temperature. The mEOF-R method generally produces the most reliable estimates (in the worst cases comparable to the climatologies) and seems to be slightly less susceptible to errors in the surface input. Multivariate EOF analysis of HOT data also gave by itself interesting results, being able to discriminate the three major signals driving the temporal variability in the area.
publisherAmerican Meteorological Society
titleMethods for the Reconstruction of Vertical Profiles from Surface Data: Multivariate Analyses, Residual GEM, and Variable Temporal Signals in the North Pacific Ocean
typeJournal Paper
journal volume22
journal issue11
journal titleJournal of Atmospheric and Oceanic Technology
identifier doi10.1175/JTECH1792.1
journal fristpage1762
journal lastpage1781
treeJournal of Atmospheric and Oceanic Technology:;2005:;volume( 022 ):;issue: 011
contenttypeFulltext


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