scholarly journals On divergence- and gradient-preserving coarse-graining for finite volume primitive equation ocean models

2022 ◽  
pp. 101941
Author(s):  
Stuart Patching
Keyword(s):  
Finite Volume ◽  
Coarse Graining ◽  
Primitive Equation ◽  
Ocean Models

scholarly journals Comparison of extended and ensemble based Kalman filters with low and high resolution primitive equation ocean models

2005 ◽  
Vol 12 (5) ◽  
pp. 755-765 ◽  
Author(s):  
I. Hoteit ◽  
G. Korres ◽  
G. Triantafyllou
Keyword(s):  
High Resolution ◽  
Kalman Filters ◽  
Linear Analysis ◽  
Ocean Model ◽  
Primitive Equation ◽  
Gaussian Distributions ◽  
Resolution Model ◽  
High Resolution Model ◽  
Ocean Models ◽  
Very High

Abstract. Kalman filters are widely used for data assimilation into ocean models. The aim of this study is to discuss the relevance of these filters with high resolution ocean models. This was investigated through the comparison of two advanced Kalman filters: the singular evolutive extended Kalman (SEEK) filter and its ensemble-based variant, called SEIK filter. The two filters were implemented with the Princeton Ocean model (POM) considering a low spatial resolution configuration (Mediterranean sea model) and a very high one (Pagasitikos Gulf coastal model). It is shown that the two filters perform reasonably well when applied with the low resolution model. However, when the high resolution model is considered, the behavior of the SEEK filter seriously degrades because of strong model nonlinearities while the SEIK filter remains remarkably more stable. Based on the assumption of prior Gaussian distributions, the linear analysis step of the latter can still be improved though.

Finite volume and spectral methods applied to Pb-30%TI alloy solidification

2001 ◽  
Vol 11 (PR6) ◽  
pp. Pr6-151-Pr6-159 ◽  
Author(s):  
R. Guérin ◽  
M. El Ganaoui ◽  
P. Haldenwang ◽  
P. Bontoux
Keyword(s):  
Finite Volume ◽  
Spectral Methods ◽  
Ti Alloy ◽  
Alloy Solidification
Sign in / Sign up

Export Citation Format

Share Document