


Registros recuperados: 10  


Tandeo, Pierre; Autret, Emmanuelle; Piolle, Jeanfrancois; Tournadre, Jean; Ailliot, Pierre. 
The Advanced AlongTrack 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 AATSRderived SST products more precisely. SST biases are then computed. Currently, Medspiration AATSR SST biases are discrete values and can introduce artificial discontinuities in AATSR level2 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 dualview and nadironly SST... 
Tipo: Text 
Palavraschave: Validation; Sea surface temperature (SST); Remote sensing; Advanced Along Track Scanning Radiometer (AATSR). 
Ano: 2009 
URL: http://archimer.ifremer.fr/doc/2009/publication6135.pdf 
 

 

 

 


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 highresolution topography roughness data set, we use a modelassisted 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 BruntVaisala (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 
Palavraschave: Lee waves; Deep ocean; Current meters. 
Ano: 2014 
URL: http://archimer.ifremer.fr/doc/00192/30306/28798.pdf 
 


Tandeo, Pierre; Ailliot, Pierre; Autret, Emmanuelle. 
Satellites provide important information on many meteorological and oceanographic variables. Statespace models are commonly used to analyse such data sets with measurement errors. In this work, we propose to extend the usual linear and Gaussian statespace 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 ExpectationMaximisation algorithm, which is combined with a standard numerical... 
Tipo: Text 
Palavraschave: Statespace model; Irregular sampling; OrnsteinUhlenbeck process; EM algorithm; Sea surface temperature. 
Ano: 2011 
URL: http://archimer.ifremer.fr/doc/00039/15047/12441.pdf 
 

 

 


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 nonGaussian noise built using the generalized Laplace distribution. The objective is to propose a new nonparametric 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 
Palavraschave: Laplace moving average; Nonlinear time series; FIR estimation; Splines; Highorder spectrum; Asymmetries. 
Ano: 2015 
URL: http://archimer.ifremer.fr/doc/00201/31189/29588.pdf 
 


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 seastate 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 
Palavraschave: Spacetime model; Significant wave height; Statespace models. 
Ano: 2011 
URL: http://archimer.ifremer.fr/doc/00363/47443/47472.pdf 
 
Registros recuperados: 10  


