Predictability {CSTools}R Documentation

Computing scores of predictability using two dynamical proxies based on dynamical systems theory.

Description

This function divides in terciles the two dynamical proxies computed with CST_ProxiesAttractor or ProxiesAttractor. These terciles will be used to measure the predictability of the system in dyn_scores. When the local dimension 'dim' is small and the inverse of persistence 'theta' is small the predictability is high, and viceversa.

Usage

Predictability(dim, theta, ncores = NULL)

Arguments

dim

An array of N named dimensions containing the local dimension as the output of CST_ProxiesAttractor or ProxiesAttractor.

theta

An array of N named dimensions containing the inverse of the persistence 'theta' as the output of CST_ProxiesAttractor or ProxiesAttractor.

ncores

The number of cores to use in parallel computation

Value

A list of length 2:

dyn_scores values from 0 to 1. A dyn_score of 1 indicates the highest predictability.

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

# Creating an example of matrix dat(time,grids):
m <- matrix(rnorm(2000) * 10, nrow = 50, ncol = 40)
names(dim(m)) <- c('time', 'grid')
# imposing a threshold
 quanti <-  0.90
# computing dyn_scores from parameters dim and theta of the attractor
attractor <- ProxiesAttractor(dat = m, quanti = 0.60)
predyn <- Predictability(dim = attractor$dim, theta = attractor$theta)

[Package CSTools version 4.0.1 Index]