Description Usage Arguments Details Value Parallel Processing Author(s) See Also
Computes the persistence climatology (i.e., the temporal autocorrelation at a given time lag)
1 2 |
grid |
Input grid (most likely annually aggregated) |
lag |
Time lag at which to calculate persistence. Default is 1. |
ci |
Coverage probability for confidence interval (in the range (0-1)). Default to |
parallel |
Logical. Should parallel execution be used? |
max.ncores |
Integer. Upper bound for user-defined number of cores. |
ncores |
Integer number of cores used in parallel computation. Self-selected number of
cores is used when |
The function is a wrapper of acf
to compute the autocorrelation function. Significance at the given confidence
interval is calculated as in plot.acf
In case of any missing values within the series, NA will be returned.
If ci
is specified (e.g. ci=0.95
), two global attributes are appended:
"signif:ci"
, indicating the confidence interval chosen
"is.signif"
, which is a logical matrix of dimension lat x lon
indicating which points exhibit a
significant persistence
A climatology grid (i.e., "time"
dimension size = 1).
Parallel processing is enabled using the parallel package.
Parallelization is undertaken by a FORK-type parallel socket cluster formed by ncores
.
If ncores
is not specified (default), ncores
will be one less than the autodetected number of cores.
The maximum number of cores used for parallel processing can be set with the max.ncores
argument,
although this will be reset to the auto-detected number of cores minus 1 if this number is exceeded. Note that not all
code, but just some critical loops within the function are parallelized.
In practice, parallelization does not always result in smaller execution times, due to the parallel overhead. However, parallel computing may potentially provide a significant speedup for the particular case of large multimember datasets or large grids.
Parallel computing is currently not available for Windows machines.
J Bedia
plotClimatology
, for conveniently plotting persistence climatology maps.
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