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dtrend

Estimates and removes the least squares linear trend of the rightmost dimension from all grid points.

Prototype

	function dtrend (
		y               : numeric,  
		return_info [1] : logical   
	)

	return_val [dimsizes(y)] :  numeric

Arguments

A multi-dimensional array or scalar value equal to the data to be detrended. The dimension from which the trend is calculated needs to be the rightmost dimension. This is usually time.

return_info

A logical scalar controlling whether attributes corresponding to the y-intercept and slope are attached to return_val. True = attributes returned. False = no attributes returned.

Return value

An array of the same size as y. Double if y is double, float otherwise.

Two attributes (slope and y_intercept) may be attached to return_val if return_info = True. These attributes will be one-dimensional arrays if y is one-dimensional. If y is multi-dimensional, the attributes will be the same size as y minus the rightmost dimension but in the form of a one-dimensional array. e.g. if y is 45 x 34, then the attributes will be a one-dimensional array of size 45*34. This occurs because attributes can not be multi-dimensional. Double if return_val is double, float otherwise.

You access the attributes through the @ operator:

print(return_val@slope)
print(return_val@y_intercept)

Description

Estimates and removes the least squares linear trend of the rightmost dimension from all grid points. Missing values are not allowed, use dtrend_msg if missing values exist. The mean is also removed. Optionally returns the slope (eg, linear trend per unit time interval) and y-intercept for graphical purposes.

Assumes y is equally spaced. If this is not the case, then use dtrend_msg even if the data do not contain missing values.

Use dtrend_n if the dimension to do the calculation on is not the rightmost dimension and reordering is not desired. This function can be significantly faster than dtrend.

Examples

Example 1

y is three-dimensional with dimensions lat, lon, and time. The returned array will have the same size. Remember that the mean is also removed.

    yDtrend = dtrend(y,False)

Example 2

Same as example 1 but with the optional attributes. Let y be temperatures in units of K and the time dimension have units of months.

  yDtrend = dtrend(y,True)
; yDtrend@slope = a one-dimensional array of nlat * nlon elements.
; the units are K/month

Since attributes can not be returned as two-dimensional arrays, the user should use onedtond to create a two-dimensional array for plotting purposes:

 
   slope2D = onedtond(yDtrend@slope,(/nlat,nlon/))
   delete (YDtrend@slope)
   slope2D = slope2D*120        ; would give [K/decade]

   yInt2D  = onedtond(yDtrend@y_intercept,(/nlat,nlon/))

Example 3

Let y be three-dimensional array with dimensions time, lat, lon. reorder y so that time is the rightmost dimension.