s2dverification (version 2.4.0)

ACC: Computes Anomaly Correlation Coefficient (Spatial Correlation)

Description

Matrix var_exp & var_obs should have dimensions (nexp/nobs, nsdates, nltimes, nlat, nlon) or (nexp/nobs, nsdates, nmember, nltimes, nlat, nlon). ACC computes the Anomaly Correlation Coefficient for the ensemble mean of each jexp in 1:nexp and each jobs in 1:nobs which gives nexp x nobs ACC for each startdate and each leadtime. A domain can be selected by providing the list of longitudes/latitudes (lon/lat) of the grid together with the corner of the domain: lonlatbox = c(lonmin, lonmax, latmin, latmax)

Usage

ACC(var_exp, var_obs, lon = NULL, lat = NULL, lonlatbox = NULL, conf = TRUE, 
    conftype = "parametric")

Value

ACCIf conf set as TRUE, Matrix with dimensions: c(nexp, nobs, nsdates, nleadtimes, 4) The fifth dimension of length 4 corresponds to the lower limit of the 95% confidence interval, the ACC, the upper limit of the 95% confidence interval and the 95% significance level. If conf set as FALSE, Anomaly Correlation Coefficient with dimensions: c(nexp, nobs, nsdates, nleadtimes).MACCMean Anomaly Correlation Coefficient with dimensions: c(nexp, nobs, nleadtimes)

Examples

# See examples on Load() to understand the first lines in this example
  configfile <- paste0(tempdir(), '/sample.conf')
ConfigFileCreate(configfile, confirm = FALSE)
c <- ConfigFileOpen(configfile)
c <- ConfigEditDefinition(c, 'DEFAULT_GRID', 'r20x10', confirm = FALSE)
c <- ConfigEditDefinition(c, 'DEFAULT_VAR_MIN', '-1e19', confirm = FALSE)
c <- ConfigEditDefinition(c, 'DEFAULT_VAR_MAX', '1e19', confirm = FALSE)
c <- ConfigAddVar(c, '2d', 'tos')
data_path <- system.file('sample_data', package = 's2dverification')
exp_data_path <- paste0(data_path, '/model/$EXP_NAME$')
obs_data_path <- paste0(data_path, '/$OBS_NAME$')
c <- ConfigAddEntry(c, 'experiments', 'file-per-startdate',
     dataset_name = 'experiment', var_name = 'tos', main_path = exp_data_path,
     file_path = '$STORE_FREQ$_mean/$VAR_NAME$_3hourly/$VAR_NAME$_$START_DATE$.nc')
c <- ConfigAddEntry(c, 'observations', 'file-per-month',
     dataset_name = 'observation', var_name = 'tos', main_path = obs_data_path,
     file_path = '$STORE_FREQ$_mean/$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$.nc')
ConfigFileSave(c, configfile, confirm = FALSE)

# Now we are ready to use Load().
startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
sampleData <- Load('tos', c('experiment'), c('observation'), startDates, 
                   leadtimemin = 1, leadtimemax = 4, output = 'lonlat', 
                   latmin = 27, latmax = 48, lonmin = -12, lonmax = 40, 
                   configfile = configfile)
  startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
sampleData <- s2dverification:::.LoadSampleData('tos', c('experiment'), 
                                                c('observation'), startDates,
                                                leadtimemin = 1,
                                                leadtimemax = 4,
                                                output = 'lonlat', 
                                                latmin = 27, latmax = 48, 
                                                lonmin = -12, lonmax = 40)
sampleData$mod <- Season(sampleData$mod, 4, 11, 12, 2)
sampleData$obs <- Season(sampleData$obs, 4, 11, 12, 2)
clim <- Clim(sampleData$mod, sampleData$obs)
ano_exp <- Ano(sampleData$mod, clim$clim_exp)
ano_obs <- Ano(sampleData$obs, clim$clim_obs)
acc <- ACC(Mean1Dim(ano_exp, 2), Mean1Dim(ano_obs, 2))
PlotACC(acc$ACC, startDates)