lm2_simulate: Simulate data from the lorenz MII model

In robertsy/lorenzr: Lorenz Models

Description

Simulate data from the lorenz MII model

Usage

lm2_simulate(duration, freq, ndim = 960, kint = 32, Forcing = 15,
  sig = sqrt(0.5), obs_type = "partial", R_sig = sig, nobs = ndim/20,
  deltat = 1/200)

Arguments

duration	total time to integrate model (duration=freq*(nsteps-1) (nsteps = duration/freq + 1)
freq	frequency of time integration (freq=duration/(nsteps-1))
ndim	dimension of system
kint	parameter K in model specification, related to number of waves
Forcing	external forcing on dynamics
sig	standard deviation of error measurments
obs_type	(all: all sites, odd: every other site, partial: regular observations at nobs sites, one: unique observation in the middle)
R_sig	standard deviation of error measurements for assimilation (default=sig)
deltat	time interval for model integration

Value

list with: state.ts matrix of nsteps x ndim y.ts list of nsteps lists, each of them containing y, R, H, d and y.loc (sites which are observed) f.propagate function to propagate the ensemble according to the model specification f.propagate <- function(state=initial state, nsteps=how many steps to propagate, ...) ndim, duration and freq to keep track of some parameters

Examples

lm2_run <- lm2_simulate(10 * .2, .2, sig=3)
lorenz_plot(lm2_run$state.ts[11,], lm2_run$y.ts[[11]])
lorenz_heatmap(lm2_run) 

robertsy/lorenzr documentation built on May 27, 2019, 10:33 a.m.