Statistical values over an ensemble — cdo

This module computes statistical values over an ensemble of input files. Depending on the chosen operator, the minimum, maximum, range, sum, average, standard deviation, variance, skewness, kurtosis, median or a certain percentile over all input files is written to outfile. All input files need to have the same structure with the same variables. The date information of a timestep in outfile is the date of the first input file.

Usage

cdo_ensavg(ifiles, p = NULL, ofile = NULL)

cdo_enskurt(ifiles, p = NULL, ofile = NULL)

cdo_ensmax(ifiles, p = NULL, ofile = NULL)

cdo_ensmean(ifiles, p = NULL, ofile = NULL)

cdo_ensmedian(ifiles, p = NULL, ofile = NULL)

cdo_ensmin(ifiles, p = NULL, ofile = NULL)

cdo_enspctl(ifiles, p = NULL, ofile = NULL)

cdo_ensrange(ifiles, p = NULL, ofile = NULL)

cdo_ensskew(ifiles, p = NULL, ofile = NULL)

cdo_ensstd(ifiles, p = NULL, ofile = NULL)

cdo_ensstd1(ifiles, p = NULL, ofile = NULL)

cdo_enssum(ifiles, p = NULL, ofile = NULL)

cdo_ensvar(ifiles, p = NULL, ofile = NULL)

cdo_ensvar1(ifiles, p = NULL, ofile = NULL)

Arguments

ifiles: Character vector with the path to the input files.
p: FLOAT - Percentile number in {0, ..., 100}
ofile: String with the path to the output file.

Value

Operators that output one or more files return a character vector to the output files.

Operators that output an indefinite number of files return a string with the basename of the files.

Operatos that don't return filenames return a character vector with the string output.

Details

ensmin     Ensemble minimum
           o(t,x) = min\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensmax     Ensemble maximum
           o(t,x) = max\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensrange   Ensemble range
           o(t,x) = range\{i1(t,x), i2(t,x), ..., in(t,x)\}
enssum     Ensemble sum
           o(t,x) = sum\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensmean    Ensemble mean
           o(t,x) = mean\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensavg     Ensemble average
           o(t,x) = avg\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensstd     Ensemble standard deviation
           Normalize by n.

           o(t,x) = std\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensstd1    Ensemble standard deviation (n-1)
           Normalize by (n-1).

           o(t,x) = std1\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensvar     Ensemble variance
           Normalize by n.

           o(t,x) = var\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensvar1    Ensemble variance (n-1)
           Normalize by (n-1).

           o(t,x) = var1\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensskew    Ensemble skewness
           o(t,x) = skew\{i1(t,x), i2(t,x), ..., in(t,x)\}
enskurt    Ensemble kurtosis
           o(t,x) = kurt\{i1(t,x), i2(t,x), ..., in(t,x)\}
ensmedian  Ensemble median
           o(t,x) = median\{i1(t,x), i2(t,x), ..., in(t,x)\}
enspctl    Ensemble percentiles
           o(t,x) = pth percentile \{i1(t,x), i2(t,x), ..., in(t,x)\}

Note

Operators of this module need to open all input files simultaneously. The maximum number of open files depends on the operating system!