s2dverification (version 2.10.3)

ProjectField: Project Anomalies onto Modes of Variability

Description

Project anomalies onto modes of variability to get the temporal evolution of the EOF mode selected. Returns principal components (PCs) by area-weighted projection onto EOF pattern (from EOF()). Able to handle NAs.

Usage

ProjectField(ano, eof, mode = 1)

Arguments

ano

Array of forecast or observational reference anomalies from Ano() or Ano_CrossValid with dimensions (number of forecast systems, ensemble members, start dates, forecast horizons, latitudes, longitudes).

eof

R object with EOFs from EOF.

mode

Variability mode number in the provided EOF object which to project onto.

Value

Array of principal components in verification format (number of forecast systems, ensemble members, start dates, forecast horizons).

See Also

EOF, NAO, PlotBoxWhisker

Examples

# NOT RUN {
# See examples on Load() to understand the first lines in this example
 
# }
# NOT RUN {
data_path <- system.file('sample_data', package = 's2dverification')
expA <- list(name = 'experiment', path = file.path(data_path, 
            'model/$EXP_NAME$/$STORE_FREQ$_mean/$VAR_NAME$_3hourly',
            '$VAR_NAME$_$START_DATE$.nc'))
obsX <- list(name = 'observation', path = file.path(data_path, 
            '$OBS_NAME$/$STORE_FREQ$_mean/$VAR_NAME$',
            '$VAR_NAME$_$YEAR$$MONTH$.nc'))

# Now we are ready to use Load().
startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
sampleData <- Load('tos', list(expA), list(obsX), startDates,
                  leadtimemin = 1, leadtimemax = 4, output = 'lonlat',
                  latmin = 27, latmax = 48, lonmin = -12, lonmax = 40)
 
# }
# NOT RUN {
 
# }
# NOT RUN {
# Now ready to compute the EOFs and project.
ano <- Ano_CrossValid(sampleData$mod, sampleData$obs)

# Compute the EOF of the observation.
eof <- EOF(ano$ano_obs[1, 1, , 1, , ], sampleData$lon, sampleData$lat)
# check the first mode represent the NAO
PlotEquiMap(eof$EOFs[1, , ], sampleData$lon, sampleData$lat, filled.continents = FALSE)

mode1_exp <- ProjectField(ano$ano_exp, eof, 1)
mode1_obs <- ProjectField(ano$ano_obs, eof, 1)

# Plot the forecast and the observation of the first mode
# for the last year of forecast
plot(mode1_obs[1, 1, dim(sampleData$mod)[3], ], type = "l", ylim = c(-1, 1), lwd = 2)
for (i in 1:dim(sampleData$mod)[2]) {
 par(new = TRUE)
 plot(mode1_exp[1, i, dim(sampleData$mod)[3], ], type = "l", col = rainbow(10)[i], 
      ylim = c(-15000, 15000))
}

# }