CST_ProxiesAttractor: Computing two dinamical proxies of the attractor in...

In CSTools: Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales

Computing two dinamical proxies of the attractor in s2dv_cube.

Description

This function computes two dinamical proxies of the attractor: The local dimension (d) and the inverse of the persistence (theta) for an 's2dv_cube' object. 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 Function based on the matlab code ([e-mail]) used in

Usage

CST_ProxiesAttractor(data, quanti, ncores = NULL)

Arguments

data	An s2dv_cube object with the data to create the attractor. Must be a matrix with the timesteps in nrow and the grids in ncol(dat(time,grids)
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, [e-mail]

Maria M. Chaves-Montero, [e-mail]

Veronica Torralba, [e-mail]

Davide Faranda, [e-mail]

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. \Sexpr[results=rd]{tools:::Rd_expr_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 s2dv data
obs <- rnorm(2 * 3 * 4 * 8 * 8)
dim(obs) <- c(dataset = 1, member = 2, sdate = 3, ftime = 4, lat = 8, lon = 8)
lon <- seq(10, 13.5, 0.5)
lat <- seq(40, 43.5, 0.5)
coords <- list(lon = lon, lat = lat)
data <- list(data = obs, coords = coords)
class(data) <- "s2dv_cube"
attractor <- CST_ProxiesAttractor(data = data, quanti = 0.6)

CSTools documentation built on Oct. 20, 2023, 5:10 p.m.