Crossvalidation Variables

Variables for the Crossvalidation methodology that can be accessed for plotting.

VARIABLE	MEANING	DIMENSION LENGTH
.zhat_separated_modes	Hindcast of field to predict using crosvalidation for each individual mode	nm x z_ns x nt
.zhat_accumulated_modes	Hindcast of field to predict using crosvalidation for n modes (1, 1->2, …, 1->nm)	nm x z_ns x nt
.scf	Squared covariance fraction of the mca for each mode	nm x nt
.r_z_zhat_t_separated_modes	Correlation between zhat and Z for each time (time series) for each individual mode	nm x nt
.r_z_zhat_t_accumulated_modes	Correlation between zhat and Z for each time (time series) for n modes (1, 1->2, …, 1->nm)	nm x nt
.p_z_zhat_t_separated_modes	P values of rt for each individual mode	nm x nt
.p_z_zhat_t_accumulated_modes	P values of rt for n modes (1, 1->2, …, 1->nm)	nm x nt
.r_z_zhat_s_separated_modes	Correlation between time series (for each point) of zhat and z (map) for each individual mode	nm x z_ns
.r_z_zhat_s_accumulated_modes	Correlation between time series (for each point) of zhat and z (map) for n modes (1, 1->2, …, 1->nm)	nm x z_ns
.p_z_zhat_s_separated_modes	P values of rr for each individual mode	nm x z_ns
.p_z_zhat_s_accumulated_modes	P values of rr for n modes (1, 1->2, …, 1->nm)	nm x z_ns
.r_uv	Correlation score betweeen u and v for each mode	nm x nt
.r_uv_sig	Correlation score betweeen u and v for each mode where significative	nm x nt
.p_uv	P value of ruv	nm x nt
.psi_separated_modes	Skill for each individual mode	nm x y_ns x z_ns x nt
.psi_accumulated_modes	Skill for n modes (1, 1->2, …, 1->nm)	nm x y_ns x z_ns x nt
.suy	Correlation in space of the predictor with the singular vector. Dimension: y_space x time x nm	y_ns x nt x nm
.suz	Correlation in space of the predictand with the singular vector. Dimension: z_space x time x nm	z_ns x nt x nm
.suy_sig	Correlation in space of the predictor with the singular vector where pvalue is smaller than alpha. Dimension: y_space x time x nm	y_ns x nt x nm
.suz_sig	Correlation in space of the predictand with the singular vector where pvalue is smaller than alpha. Dimension: z_space x time x nm	z_ns x nt x nm
.us	Singular vectors of the predictor field. Dimension: nm x time x time	nm x nt x nt
.vs	Singular vectors of the predictand field. Dimension: nm x time x time	nm x nt x nt
.alpha	Correlation factor	1

VARIABLE	MEANING	TYPE
.dsy	Preprocessed dataset that was introduced as predictor.	Preprocess
.dsz	Preprocessed dataset that was introduced as predictand.	Preprocess