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dim_rmvmean_Wrap

Calculates and removes the mean of the (rightmost) dimension at all other dimensions and retains metadata.

Prototype

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

	function dim_rmvmean_Wrap (
		x  : numeric   
	)

	return_val [dimsizes(x)] :  float or double

Arguments

x

A variable of numeric type and any dimensionality.

Return value

The output is of type double if the input is double, and float otherwise.

The dimensionality is the same as the input dimensionality.

Description

The dim_rmvmean function calculates and removes the mean from all elements of the n-1th (rightmost) dimension for each index of the dimensions 0...n-2 and retains metadata. A wrapper function. Missing values are ignored.

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

See Also

dim_rmvmean_n_Wrap, dim_rmvmean, dim_rmvmean_n, dim_rmvmed

Examples

Example 1:

Let x be a 1-dimensional array: (a) Create a new variable, xNew, that contains just the deviations from the mean; (b) replace the variable x with the deviations.

  xNew = dim_rmvmean_Wrap(x)      ; new variable
  x    = dim_rmvmean_Wrap(x)      ; overwrite with deviations
Example 2:

Let x be a 3-dimensional array with dimension sizes (ntim, nlat, nlon). To remove the means of the "nlon" dimension:

   xRmvLon = dim_rmvmean (x)         ; new variable containing deviations (no metadata)
   xRmvLon = dim_rmvmean_Wrap( x )    ; with metadata
   x       = dim_rmvmean (x)         ; overwrite with deviations
Example 3:

Let x be a 3-dimensional array with named dimensions (time, lat, lon) and dimension sizes (ntim, nlat, nlon). To remove the mean of the time dimension from all lat/lon indices, use NCL's Named Subscripting to reorder the input array such that "time" is the rightmost dimension.

   xRmvTime = dim_rmvmean(x(lat|:, lon|:, time|:))
   xRmvTime = dim_rmvmean_Wrap(x(lat|:, lon|:, time|:))
   xRmvTime = dim_rmvmean_n_Wrap(x,0)     ; no reordering needed
Note: in V5.1.1, you will be able to use dim_rmvmean_n_Wrap to avoid having to reorder your data.

Example 4:

Let x be as in Example 3 and let x contain monthly means for (say) 10 years of data (ntim=120). Monthly anomalies for each month could be calculated using array subscripting and Named Subscripting to reorder the input array such that "time" is the rightmost dimension.

   xRmvJan  = dim_rmvmean_Wrap(x(lat|:, lon|:, time|0:ntim-1:12))
   xRmvJuly = dim_rmvmean_Wrap(x(lat|:, lon|:, time|6:ntim-1:12))