Now showing items 1-7 of 7
Using the Extended Kalman Filter with a Multilayer Quasi-Geostrophic Ocean Model
(American Geophysical Union, 1992-11-15)
The formulation of the extended Kalman filter for a multilayer nonlinear quasi-geostrophic ocean circulation model is discussed. The nonlinearity in the ocean model leads to an approximative equation for error covariance ...
Data assimilation for coastal zone monitoring and forecasting
(Elsevier Science, 1997)
The Effect of Diapycnal Mixing on the Ventilation and CFC-11 Uptake in the Southern Ocean
(Science Press, 2004-03-04)
The Miami Isopycnic Coordinate Ocean Model (MICOM) is used to investigate the effect of diapycnal mixing on the oceanic uptake of CFC-11 and the ventilation of the surface waters in the Southern Ocean (south of 45°S). ...
Open Boundary Conditions for the Extended Kalman Filter With a Quasi-Geostrophic Ocean Model
(American Geophysical Union, 1993-05-18)
The formulation of consistent boundary conditions for the quasi-geostrophic (QG) model with an extended Kaiman filter in a data assimilation scheme is discussed. To form a well-posed boundary value problem for the QG model, ...
Evaluating two numerical advection schemes in HYCOM for eddy-resolving modelling of the Agulhas Current
(Copernicus Publications on behalf of the European Geosciences Union, 2009-06-02)
A 4th order advection scheme is applied in a nested eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) of the greater Agulhas Current system for the purpose of testing advanced numerics as a means for improving the model ...
Inverse Methods and Data Assimilation in Nonlinear Ocean Models
An overview is given of the current status of inverse methods and data assimilation for nonlinear ocean models. The inverse theory for time dependent dynamical models is formulated and the most promising solution methods ...
Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics
(American Geophysical Union, 1994-05-15)
A new sequential data assimilation method is discussed. It is based on forecasting the error statistics using Monte Carlo methods, a better alternative than solving the traditional and computationally extremely demanding ...