sl.ens.gcdist.rmse: Calculate root mean square great-circle distance error of an...

In FESOM/spheRlab: Spherical Geometry, Analysis, and Plotting of Geoscientific Data on Arbitrary Grids

Calculate root mean square great-circle distance error of an ensemble

Description

This function can be used to calculate the root mean square of the great-circle distance errors of a trajectory ensemble, either compared to an observed trajectory or to each one of the ensemble members in a perfect-model approach.

Usage

sl.ens.gcdist.rmse(ensm.in, t.ind = 1:length(ensm.in[1,1,]), obs = NULL, mode = "pm", Rsphere = 1)

Arguments

ensm.in	a numeric array containing the trajectory positions (in lon-lat coordinates), with shape [N.mem, 2, N.time], with the number of members N.mem and the number of time steps N.time.
t.ind	a numeric vector of maximal length N.time, containing the indices of the time steps that shall be considered. All time steps are used by default, i.e. t.inds = 1:N.time.
obs	a numeric array of shape [2,N.time] which contains the coordinates of an observed trajectory. Must be provided if mode="obs" is used.
mode	a string, either 'pm' (perfect model) or 'obs' (observation), defining the type of RMSE that will be computed. See section 'Details' for more information.
Rsphere	a numerical scalar defining the radius of the sphere for which the great-circle distance of the positions is calculated.

Details

For mode='pm', the root mean square error is calculated using each ensemble member as the 'truth' once (see reference for further information). Otherwise, the observation is used to determine the position errors.

Value

Returns a numeric vector of length length(t.ind) with a time series of the RMS distance error.

Author(s)

Simon Reifenberg

References

Collins, M. (2003), Climate Predictability on Seasonal to Decadal Time Scales: The Initial Value Problem, Climate Dyamics, 19,

See Also

sl.gc.dist

FESOM/spheRlab documentation built on April 6, 2024, 6:52 p.m.