World Wide Web access to real-time and historical data from the TAO array of moored buoys in the tropical Pacific Ocean: updates for 1996

Soreide, N. N.; McClurg, D.C.; Wei, Zhu; McPhaden, Michael J.; Denbo, D.W.; Renton, M.W.

doi:10.1109/oceans.1996.569100

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…The first-guess fields are those of Reynolds and Smith (1995) for SST; a combination of Kessler (1990) expendable bathythermograph (XBT) analyses and Kessler and McCreary (1993) conductivity, temperature, and depth analyses for Z20, and Comprehensive Ocean-Atmosphere Data Set analyses (Woodruff et al, 1987) for surface winds. The procedure is univariate and involves bilinear interpolation followed by smoothing with a gappy running mean filter (Soreide et al, 1996). Given this splendid and growing data set (see the TOGA-TAO website), the question arises: can it be better analyzed by generalized inverse methods?…”

Section: Enso: Testing Intermediate Coupled Modelsmentioning

confidence: 99%

Inverse Modeling of the Ocean and Atmosphere

Bennett

2002

348

359

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Inverse Modeling of the Ocean and Atmosphere is a graduate-level textbook for students of oceanography and meteorology, and anyone interested in combining computer models and observations of the hydrosphere or solid earth. The scientific emphasis is on the formal testing of models, formulated as rigorous hypotheses about the errors in all the information: dynamics, initial conditions, boundary conditions and data. The products of successful inversions include four-dimensional multivariate analyses or maps of, for example, ocean circulation fields such as temperature, pressure and currents; analyses of residuals in the dynamics, inputs and data; error statistics for all the analyses, and assessments of the instrument arrays or observing systems. A step-by-step development of maximally-efficient inversion algorithms, using ideal models, is complemented by computer codes and comprehensive details for realistic models. Variational tools and statistical concepts are concisely introduced, and applications to contemporary research models, together with elaborate observing systems, are examined in detail. The book offers a review of the various alternative approaches, and further advanced research topics are discussed. Derived from the author's lecture notes, this book constitutes an ideal course companion for advanced undergraduates and graduate students, as well as being a valuable reference source for researchers and managers in the theoretical earth sciences, civil engineering, and applied mathematics. Tutors are also directed towards the author's ftp site where they may download complementary overheads for class teaching.

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Section: Enso: Testing Intermediate Coupled Modelsmentioning

confidence: 99%

Inverse Modeling of the Ocean and Atmosphere

Bennett

2002

348

359

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“…These data are available via the Internet from the National Oceanic and Atmospheric Association (NOAA) Pacific Marine Environmental Laboratory (PMEL). See Soreide et al (1996). There are about 2400 scalar data values in our 12-month-long years 1 and 2, and about 4000 values in our 18-monthlong year 3.…”

Section: Some Detailsmentioning

confidence: 85%

Generalized Inversion of Tropical Atmosphere–Ocean (TAO) Data and a Coupled Model of the Tropical Pacific. Part II: The 1995–96 La Niña and 1997–98 El Niño

et al. 2000

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The investigation of the consequences of trying to blend tropical Pacific observations from the Tropical Atmosphere-Ocean (TAO) array into the dynamical framework of an intermediate coupled ocean-atmosphere model is continued. In a previous study it was found that the model dynamics, the prior estimates of uncertainty in the observations, and the estimates of the errors in the dynamical equations of the model could not be reconciled with data from the 1994-95 period. The error estimates and the data forced the rejection of the model physics as being unacceptably in error. In this work, data from two periods (1995-96 and 1997-98) were used when the tropical Pacific was in states very different from the previous study. The consequences of increasing the prior error estimates were explored in an effort to find out if it is possible at least to use the intermediate model physics to assist in mapping the observations into fields in a statistically consistent way. It was found that such a result is possible for the new data periods, with larger prior error assumptions. However, examination of the behavior of the mapped fields indicates that they have no dynamical utility. The model dynamical residuals, that is, the size of the quantity that is left after evaluating all of the terms in each intermediate model equation, dominate the terms themselves. Evidently the intermediate model is not able to add insight into the processes that caused the tropical Pacific to behave as it was observed to, during these time intervals. The inverse techniques described here together with the relatively dense TAO dataset have made it possible for the unambiguous rejection of the nonlinear intermediate model dynamical system. This is the first time that data have been able to provide such a clear-cut appraisal of simplified dynamics.

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“…3 and 4 are defined relative to the climatologies of Reynolds and Smith (1995). These SST and Z20 plots were prepared from the TAO data using univariate bilinear interpolation (Soreide 1996). The principal anomalous SST feature is the warm pool just east of the date line, reaching a maximum of about 2.5Њ in November 1994 and fading entirely by March 1995.…”

Section: The Datamentioning

confidence: 99%

“…The first-guess fields are those of Reynolds and Smith (1995) for SST: a combination of Kessler (1990) expendable bathythermographs (XBT) analyses and Kessler and McCreary (1993) conductivity, temperature, and depth analyses for Z20; and Comprehensive Ocean-Atmosphere Data Set analyses (Woodruff et al 1987) for surface winds. The procedure is univariate and involves bilinear interpolation followed by smoothing with a gappy running mean filter (Soreide et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Generalized Inversion of Tropical Atmosphere–Ocean Data and a Coupled Model of the Tropical Pacific

Bennett¹,

Chua²,

Harrison³

et al. 1998

J. Climate

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It is hypothesized that the circulation of the tropical Pacific Ocean and atmosphere satisfies the equations of a simple coupled model to within errors having specified covariances, and that the Tropical Atmosphere-Ocean array (TAO) measures the circulation to within errors also having specified covariances. This hypothesis is tested by finding the circulation that is the weighted least squares best fit to the dynamics of the simple model, to its initial and boundary conditions, and to a year of monthly mean TAO data for sea surface temperature, for the depth of the 20ЊC isotherm, and for surface winds. The fit is defined over the entire tropical Pacific and from 1 April 1994 to 31 March 1995. The best-fit circulation or state estimate is calculated using variational methods. Posterior error covariances are estimated using statistical simulation. The best fit is also subjected to a significance test.It is found that, although the fit to data is largely within standard errors, the misfit to dynamics is significantly larger than standard errors. These standard errors are estimated a priori, and with difficulty, from published scale analyses of tropical circulation. An examination of the dynamical residuals indicates that the simple coupled model should be improved by including momentum advection both in the oceanic and atmospheric components.

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World Wide Web access to real-time and historical data from the TAO array of moored buoys in the tropical Pacific Ocean: updates for 1996

Cited by 5 publications

References 6 publications

Inverse Modeling of the Ocean and Atmosphere

Inverse Modeling of the Ocean and Atmosphere

Generalized Inversion of Tropical Atmosphere–Ocean (TAO) Data and a Coupled Model of the Tropical Pacific. Part II: The 1995–96 La Niña and 1997–98 El Niño

Generalized Inversion of Tropical Atmosphere–Ocean Data and a Coupled Model of the Tropical Pacific

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