Ano_CrossValid: Computes Anomalies In Cross-Validation Mode

In s2dverification: Set of Common Tools for Forecast Verification

Computes Anomalies In Cross-Validation Mode

Description

Computes the anomalies from the arrays of the experimental and observational data output from load() by subtracting the climatologies computed with a cross-validation technique and a per-pair method.

Usage

Ano_CrossValid(var_exp, var_obs, memb = TRUE)

Arguments

var_exp	Model data: c(nmod/nexp, nmemb/nparam, nsdates, nltime) up to c(nmod/nexp, nmemb/nparam, nsdates, nltime, nlevel, nlat, nlon).
var_obs	Observational data: c(nobs, nmemb, nsdates, nltime) up to c(nobs, nmemb, nsdates, nltime, nlevel, nlat, nlon).
memb	TRUE/FALSE (1 climatology for each member/1 climatology averaging all the members). Default = TRUE.

Value

$ano_exp	Matrix with same dimensions as var_exp
$ano_obs	Matrix with same dimensions as var_obs

Author(s)

History:
0.1 - 2011-12 (V. Guemas) - Original code
1.0 - 2013-09 (N. Manubens) - Formatting to CRAN

Examples

# Load sample data as in Load() example:
example(Load)
anomalies <- Ano_CrossValid(sampleData$mod, sampleData$obs)
 
PlotAno(anomalies$ano_exp, anomalies$ano_obs, startDates, 
       toptitle = paste('anomalies'), ytitle = c('K', 'K', 'K'), 
       legends = 'ERSST', biglab = FALSE, fileout = 'tos_ano_crossvalid.eps')
 

s2dverification documentation built on April 20, 2022, 9:06 a.m.