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A Multivariate Regression Approach to Adjust AATSR Sea Surface Temperature to In Situ Measurements ArchiMer
Tandeo, Pierre; Autret, Emmanuelle; Piolle, Jean-francois; Tournadre, Jean; Ailliot, Pierre.
The Advanced Along-Track Scanning Radiometer (AATSR) onboard Envisat is designed to provide very accurate measurements of sea surface temperature (SST). Using colocated in situ drifting buoys, a dynamical matchup database (MDB) is used to assess the AATSR-derived SST products more precisely. SST biases are then computed. Currently, Medspiration AATSR SST biases are discrete values and can introduce artificial discontinuities in AATSR level-2 SST fields. The new AATSR SST biases presented in this letter are continuous. They are computed, for nighttime and best proximity confidence data, by linear regression with different MDB covariables (wind speed, latitude, aerosol optical depth, etc.). As found, the difference between dual-view and nadir-only SST...
Tipo: Text Palavras-chave: Validation; Sea surface temperature (SST); Remote sensing; Advanced Along Track Scanning Radiometer (AATSR).
Ano: 2009 URL: http://archimer.ifremer.fr/doc/2009/publication-6135.pdf
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An autoregressive model with time-varying coefficients for wind fields ArchiMer
Ailliot, Pierre; Monbet, Valérie; Prevosto, Marc.
In this article, an original Markov-switching autoregressive model is proposed to describe the space-time evolution of wind fields. At first, a non-observable process is introduced in order to model the motion of the meteorological structures. Then, conditionally to this process, the evolution of the wind fields is described using autoregressive models with time-varying coefficients. The proposed model is calibrated and validated on data ill the North Atlantic.
Tipo: Text Palavras-chave: Markov switching autoregressive model; Wind fields; Space time model.
Ano: 2006 URL: http://archimer.ifremer.fr/doc/2006/publication-1225.pdf
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Dynamical partitioning of directional ocean wave spectra ArchiMer
Ailliot, Pierre; Maisondieu, Christophe; Monbet, Valerie.
Directional wave spectra generally exhibit several peaks due to the coexistence of wind sea generated by local wind conditions and swells originating from distant weather systems. This paper proposes a new algorithm for partitioning such spectra and retrieving the various systems which compose a complex sea-state. It is based on a sequential Monte-Carlo algorithm which allows to follow the time evolution of the various systems. The proposed methodology is validated on both synthetic and real spectra and the results are compared with a method commonly used in the literature.
Tipo: Text Palavras-chave: Partitioning algorithm; Directional wave spectrum; Sequential Monte Carlo algorithm.
Ano: 2013 URL: http://archimer.ifremer.fr/doc/00134/24563/22688.pdf
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Improvement ocean wave spectra estimation using the temporal structure of wave systems ArchiMer
Kpogo Nuwoklo, Komlan Agbéko; Ailliot, Pierre; Olagnon, Michel; Guede, Zakoua; Arnault, Sabine.
Sea states are usually the combination of several time-evolving wave systems whereas the classical spectral estimation methods assume stationarity. A method that adapts to the dynamical evolution of the spectral components is proposed to improve both omnidirectional and directional sea wave spectral estimations. In this method, periodograms are computed for each sea state as in the conventional methods, and rather than only smoothing individual periodograms, the overall time-history of periodograms are simultaneously smoothed in frequency and time dimensions. Since a simple two dimensional averaging would not be appropriate because the temporal evolution of the wave systems reflects typical non-stationary behaviors, we use either kriging or adaptive 2D...
Tipo: Text Palavras-chave: Directional wave spectrum; Spectral estimation; Periodogram smoothing; Kriging.
Ano: 2015 URL: http://archimer.ifremer.fr/doc/00252/36309/37313.pdf
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Lee wave generation rates in the deep ocean ArchiMer
Wright, Corwin J.; Scott, Robert; Ailliot, Pierre; Furnival, Darran.
Using the world's largest data set of in situ ocean current measurements, combined with a high-resolution topography roughness data set, we use a model-assisted hierarchical clustering methodology to estimate the global lee wave generation rate at the ocean floor. Our analysis suggests that internal wave generation contributes 0.750.19 TW (2 standard deviation) to the oceanic energy budget but with a strong dependence on the Brunt-Vaisala (buoyancy) frequency climatology used. This estimate is higher than previous calculations and suggests that internal wave generation may be a much more significant contributor to the global oceanic mechanical energy budget than had previously been assumed. Our results imply that lee wave generation and propagation may be...
Tipo: Text Palavras-chave: Lee waves; Deep ocean; Current meters.
Ano: 2014 URL: http://archimer.ifremer.fr/doc/00192/30306/28798.pdf
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Linear Gaussian state-space model with irregular sampling: application to sea surface temperature ArchiMer
Tandeo, Pierre; Ailliot, Pierre; Autret, Emmanuelle.
Satellites provide important information on many meteorological and oceanographic variables. State-space models are commonly used to analyse such data sets with measurement errors. In this work, we propose to extend the usual linear and Gaussian state-space to analyse time series with irregular time sampling, such as the one obtained when keeping all the satellite observations available at some specific location. We discuss the parameter estimation using a method of moment and the method of maximum likelihood. Simulation results indicate that the method of moment leads to a computationally efficient and numerically robust estimation procedure suitable for initializing the Expectation-Maximisation algorithm, which is combined with a standard numerical...
Tipo: Text Palavras-chave: State-space model; Irregular sampling; Ornstein-Uhlenbeck process; EM algorithm; Sea surface temperature.
Ano: 2011 URL: http://archimer.ifremer.fr/doc/00039/15047/12441.pdf
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Modèles autorégressifs à changements de régimes markoviens. Applications aux séries tempo-relles de vent ArchiMer
Ailliot, Pierre.
In this thesis, several original Markov switching autoregressive model are proposed for wind time series. The first chapter is devoted to a theoretical study of these models. We focus mainly on the problems of the numerical calculation of the maximum likelihood estimators, of the asymp-totic behavior of these estimators and finally of model selection and validation. In the second chapter, we propose various Markov switching autoregressive model to describe the evolution of the wind in a fixed point, and then in the third chapter its space-time evolution. For each suggested model, we check the physical interpretability of the various parameters, and their capacity to simulate realistic artificial sequences. The obtained results are compared to those...
Tipo: Text Palavras-chave: Space time model; Wind time series; Asymptotic properties; Maximum likelihood estimator; Stability; Markov Switching autoregressive model; Modèle spatio temporel; Séries temporelles de vent; Propriétés asymptotiques; Estimateurs du maximum de vraisemblance; Stabilité; Modèles autorégressifs à changements de régimes markoviens.
Ano: 2004 URL: http://archimer.ifremer.fr/doc/2004/these-325.pdf
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Modeling extreme values of processes observed at irregular time steps: Application to significant wave height ArchiMer
Raillard, Nicolas; Ailliot, Pierre; Yao, Jianfeng.
This work is motivated by the analysis of the extremal behavior of buoy and satellite data describing wave conditions in the North Atlantic Ocean. The available data sets consist of time series of significant wave height (Hs) with irregular time sampling. In such a situation, the usual statistical methods for analyzing extreme values cannot be used directly. The method proposed in this paper is an extension of the peaks over threshold (POT) method, where the distribution of a process above a high threshold is approximated by a maxstable process whose parameters are estimated by maximizing a composite likelihood function. The efficiency of the proposed method is assessed on an extensive set of simulated data. It is shown, in particular, that the method is...
Tipo: Text Palavras-chave: Extreme values; Time series; Max-stable process; Composite likelihood; Irregular time sampling; Significant wave height; Satellite data.
Ano: 2014 URL: http://archimer.ifremer.fr/doc/00218/32888/31372.pdf
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Modeling process asymmetries with Laplace moving average ArchiMer
Raillard, Nicolas; Prevosto, Marc; Ailliot, Pierre.
Many records in environmental science exhibit asymmetries: for example in shallow water and with variable bathymetry, the sea wave time series shows front–back asymmetries and different shapes for crests and troughs. In such situation, numerical models are available but their computational cost and complexity are high. A stochastic process aimed at modeling such asymmetries has recently been proposed, the Laplace moving average process, which consists in applying a linear filter on a non-Gaussian noise built using the generalized Laplace distribution. The objective is to propose a new non-parametric estimator for the kernel involved in the definition of this process. Results based on a comprehensive numerical study will be shown in order to evaluate the...
Tipo: Text Palavras-chave: Laplace moving average; Non-linear time series; FIR estimation; Splines; High-order spectrum; Asymmetries.
Ano: 2015 URL: http://archimer.ifremer.fr/doc/00201/31189/29588.pdf
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Space-time models for moving fields with an application to significant wave height fields ArchiMer
Ailliot, Pierre; Baxevani, Anastassia; Cuzol, Anne; Monbet, Valerie; Raillard, Nicolas.
The surface of the ocean, and so such quantities as the significant wave height, equation image, can be thought of as a random surface that develops over time. In this paper, we explore certain types of random fields in space and time, with and without dynamics that may or may not be driven by a physical law, as models for the significant wave height. Reanalysis data is used to estimate the sea-state motion which is modeled as a hidden Markov chain in a state space framework by means of an AR(1) process or in the presence of the dispersion relation. Parametric covariance models with and without dynamics are fitted to reanalysis and satellite data and compared to the empirical covariance functions. The derived models have been validated against satellite...
Tipo: Text Palavras-chave: Space-time model; Significant wave height; State-space models.
Ano: 2011 URL: http://archimer.ifremer.fr/doc/00363/47443/47472.pdf
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