Abstract
A new data assimilation scheme developed earlier and based on the theory of diffusion stochastic processes and parabolic differential equations is presented and tested. This scheme is applied to the Hybrid Circulation Ocean Model (HYCOM) and altimetry data base Archiving, Validating and Interpolating Satellite Oceanography Data (AVISO) over the Atlantic. Several numerical experiments are conducted and their results are analyzed. It is shown that the method really assimilates data, makes the output oceanic fields closer to observations and, on the other hand, conserves the model integrals and balance. The tested method is also compared with the Ensemble Optimal Interpolation scheme (EnOI) as a counterpart of the standard Kalman filter method and it is shown that the proposed general method has several advantages, in particular, it provides a better forecast and requires less computational consumptions.
Highlights
Data assimilation as a part of mathematical and numerical research is a scientific area of great practical importance that is used in ocean modelling, weather forecast, operational oceanography and many other fields of science
There is a necessity to have a powerful and, at the same time, relatively portable and economy data assimilation scheme which would be applicable to various numerical ocean and coupled ocean-atmosphere models and would provide a satisfactory and reliable forecast of the ocean characteristics in short and media-term periods
This study deals with the application of the novel data assimilation method created in [8, 9], hereafter it will be referred to as GKF
Summary
Data assimilation as a part of mathematical and numerical research is a scientific area of great practical importance that is used in ocean modelling, weather forecast, operational oceanography and many other fields of science. There is a necessity to have a powerful and, at the same time, relatively portable and economy data assimilation scheme which would be applicable to various numerical ocean and coupled ocean-atmosphere models and would provide a satisfactory and reliable forecast of the ocean characteristics in short and media-term periods. For this reason, many papers are dedicated to the developments and applications of statistical, dynamical or hybrid assimilation methods in the recent years, for instance [57]. It was shown that the proposed data assimilation scheme has many advantages in comparison with its EnOI counterpart, including less computational consumptions and better forecast properties
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
