| 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: 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$theta))
plot(time, Attractor$dim, xlab = 'time', ylab = 'd',
main = 'local dimension', type = 'l')