rDAF-package: An R Data Assimilation Framework

In garciapintado/rDAF: An R Data Assimilation Framework

Description

In the geophysical community the issue of fusing data into models is referred to as inverse methods and data assimilation, whose aim is finding the best estimate of the state, by combining information from the observations and from the numerical and theoretical knowledge of the underlying governing dynamical laws. This package provides a simple R framework for sequential data assimilation based on ensemble covariances [Evensen (1994) <doi:10.1016/0167-2789(94)90130-9>]. The package includes the mean-preserving ensemble transform Kalman filter described by Ott et al. <doi:10.1111/j.1600-0870.2004.00076.x>, and also provides the simplified sensitivity-based filters described in Garcia-Pintado and Paul (2018) <doi:10.5194/gmd-11-5051-2018>.

Details

The DESCRIPTION file: This package was not yet installed at build time.

Index: This package was not yet installed at build time.
A software for data assimilation based on R. The current version only provides the core function assimilateLite(). A version including localization, inflation, rotation, and MPI parallelization is under testing and being documented. Please contact the author for information requests.

Author(s)

Javier Garcia-Pintado

Maintainer: Javier Garcia-Pintado <[e-mail]>

garciapintado/rDAF documentation built on May 25, 2019, 7:26 p.m.