ProxiesAttractor {CSTools}R Documentation

Computing two dinamical proxies of the attractor.

Description

This function computes two dinamical proxies of the attractor: The local dimension (d) and the inverse of the persistence (theta). These two parameters will be used as a condition for the computation of dynamical scores to measure predictability and to compute bias correction conditioned by the dynamics with the function DynBiasCorrection. Funtion based on the matlab code (davide.faranda@lsce.ipsl.fr) used in:

Usage

ProxiesAttractor(data, quanti, ncores = NULL)

Arguments

data

a multidimensional array with named dimensions to create the attractor. It requires a temporal dimension named 'time' and spatial dimensions called 'lat' and 'lon', or 'latitude' and 'longitude' or 'grid'.

quanti

a number lower than 1 indicating the quantile to perform the computation of local dimension and theta

ncores

The number of cores to use in parallel computation.

Value

dim and theta

Author(s)

Carmen Alvarez-Castro, carmen.alvarez-castro@cmcc.it

Maria M. Chaves-Montero, mdm.chaves-montero@cmcc.it

Veronica Torralba, veronica.torralba@cmcc.it

Davide Faranda, davide.faranda@lsce.ipsl.fr

References

Faranda, D., Alvarez-Castro, M.C., Messori, G., Rodriguez, D., and Yiou, P. (2019). The hammam effect or how a warm ocean enhances large scale atmospheric predictability. Nature Communications, 10(1), 1316. DOI = https://doi.org/10.1038/s41467-019-09305-8 "

Faranda, D., Gabriele Messori and Pascal Yiou. (2017). Dynamical proxies of North Atlantic predictability and extremes. Scientific Reports, 7-41278, 2017.

Examples

# Example 1: Computing the attractor using simple data
# Creating an example of matrix data(time,grids):
mat <- array(rnorm(36 * 40), c(time = 36, grid = 40)) 
qm <- 0.90 # imposing a threshold
Attractor <- ProxiesAttractor(data = mat, quanti = qm)
# to plot the result
time = c(1:length(Attractor$theta))
layout(matrix(c(1, 3, 2, 3), 2, 2))
plot(time, Attractor$dim, xlab = 'time', ylab = 'd',
    main = 'local dimension', type = 'l')
plot(time, Attractor$theta, xlab = 'time', ylab = 'theta', main = 'theta') 
plot(Attractor$dim, Attractor$theta, col = 'blue', 
    main = "Proxies of the Attractor",
    xlab = "local dimension", ylab = "theta", lwd = 8, 'p')


[Package CSTools version 4.0.1 Index]