NCL Website header
NCL Home > Documentation > Functions > General applied math, Statistics


Computes the sample standard deviation of a variable's rightmost dimension at all other dimensions and retains metadata.


load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"

	function dim_stddev_Wrap (
		x  : numeric   

	return_val  :  float or double



A variable of numeric type and any dimensionality.

Return value

The output will be double if x is double, and float otherwise.

The output dimensionality is the same as the first n-2 dimensions of the input variable. That is, the dimension rank of the input variable will be reduced by one.


The dim_stddev_Wrap function computes the sample standard deviation of all elements of the n-1 dimension for each index of the dimensions 0...n-2 and retains metadata. A wrapper function. Missing values are ignored.

Technically, this function calculates the sample standard deviation. This means that it divides by one less than the total number of non-missing values (1/(N-1)).

Use dim_stddev_n_Wrap if you want to specify which dimensions to do the calculation across.

See Also

dim_stddev_n_Wrap, dim_stddev, dim_stddev_n, stddev, dim_avg, dim_median, dim_num, dim_product, dim_rmsd, dim_rmvmean, dim_rmvmed, dim_standardize, dim_stat4, dim_stddev, dim_sum, dim_variance


Example 1

Create a variable q of size (3,5,10) array. Then calculate the sample standard deviation of the rightmost dimension.

    q   = random_uniform(-20,100,(/3,5,10/))
    qStd= dim_stddev(q)   ;==>  qStd(3,5)
Example 2

Let x be of size (ntim,nlat,mlon) and with named dimensions "time", "lat" and "lon", respectively. Then, for each time and latitude, the standard deviation is:

    xStdLon= dim_stddev( x )    ; ==> xStdLon(ntim,nlat)
Generally, users prefer that the returned variable have metadata associated with it. This can be accomplished via the dim_stddev_Wrap function
    xStdLon = dim_stddev_Wrap( x )    ; ==> xStdLon(time,lat)
Example 3

Let x be defined as in Example 2: x(time,lat,lon). Compute the temporal standard deviation at each latitude/longitude grid point. Use NCL's Named Subscripting to reorder the input array such that "time" is the rightmost dimension.

Note: in V5.1.1, you will be able to use dim_stddev_n_Wrap to avoid having to reorder your data.

    xStdTime = dim_stddev( x(lat|:, lon|:, time|:) )    ; ==> xStdTime(nlat,nlon)

    xStdTime = dim_stddev_n( x, 0 )                     ; no reordering needed
If metadata is desired use
    xStdTime = dim_stddev_Wrap( x(lat|:, lon|:, time|:) )    ; ==> xStdTime(lat,lon)

    xStdTime = dim_stddev_n_Wrap( x, 0 )                     ; no reordering needed