garciapintado/rDAF: An R Data Assimilation Framework

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>.

Getting started

Package details

AuthorJavier Garcia-Pintado
MaintainerJavier Garcia-Pintado <jgarciapintado@marum.de>
LicenseGPL (>=2)
Version1.0-0
URL https://github.com/garciapintado/rDAF
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("garciapintado/rDAF")
garciapintado/rDAF documentation built on May 25, 2019, 7:26 p.m.