Climdex: Wrapper for applying the climdex routine ETCCDI climate...

In ClimProjDiags: Set of Tools to Compute Various Climate Indices

Wrapper for applying the climdex routine ETCCDI climate change indices to n-dimensional arrays.

Description

This function computes the t90p, t10p, cdd or rx5day indices from n-dimensional arrays.

Usage

Climdex(
  data,
  metric,
  threshold = NULL,
  base.range = NULL,
  dates = NULL,
  timedim = NULL,
  calendar = NULL,
  ncores = NULL
)

Arguments

data	A numeric n-dimensional array containing daily maximum or minimum temperature, wind speed or precipitation amount.
metric	The metric to be computed, either 't90p', 't10p', 'Wx', 'cdd' or 'rx5day'.
threshold	For the 't90p' and 't10p' metrics, an array of the 90th/10th percentiles must be included. This parameter can be computed with the Threshold function.
base.range	The years used for the reference period. If NULL (by default), all years are used.
dates	A vector of dates with a calendar attributes. If NULL (by default), the 'time' attributes of parameter 'data' are considered.
timedim	An integer number indicating the position of the time dimension in the parameter data. If NULL (by default), the dimension called 'time' in parameter data is considered as temporal dimension.
calendar	A character indicating the calendar type.
ncores	The number of cores to be used when computing the index.

Value

A list of length 2:

• $result, an array with the same dimensions as the input array, except for the temporal dimension which is renamed to 'year', moved to the first dimension position and reduce to annual resolution.

• $years, a vector of the corresponding years.

References

David Bronaugh for the Pacific Climate Impacts Consortium (2015). climdex.pcic: PCIC Implementation of Climdex Routines. R package version 1.1-6. http://CRAN.R-project.org/package=climdex.pcic

Examples

##Example synthetic data:
data <- 1:(2 * 3 * 372 * 1)
dim(data) <- c(lon = 2, lat = 3, time = 372, model = 1)
time <- c(seq(ISOdate(1900, 1, 1), ISOdate(1900, 1, 31), "day"), 
         seq(ISOdate(1901, 1, 1), ISOdate(1901, 1, 31), "day"),
         seq(ISOdate(1902, 1, 1), ISOdate(1902, 1, 31), "day"),
         seq(ISOdate(1903, 1, 1), ISOdate(1903, 1, 31), "day"),
         seq(ISOdate(1904, 1, 1), ISOdate(1904, 1, 31), "day"),
         seq(ISOdate(1905, 1, 1), ISOdate(1905, 1, 31), "day"),
         seq(ISOdate(1906, 1, 1), ISOdate(1906, 1, 31), "day"),
         seq(ISOdate(1907, 1, 1), ISOdate(1907, 1, 31), "day"),
         seq(ISOdate(1908, 1, 1), ISOdate(1908, 1, 31), "day"),
         seq(ISOdate(1909, 1, 1), ISOdate(1909, 1, 31), "day"),
         seq(ISOdate(1910, 1, 1), ISOdate(1910, 1, 31), "day"),
         seq(ISOdate(1911, 1, 1), ISOdate(1911, 1, 31), "day"))
metadata <- list(time = list(standard_name = 'time', long_name = 'time', 
                            calendar = 'gregorian', 
                            units = 'days since 1970-01-01 00:00:00', 
                            prec = 'double', 
                            dim = list(list(name = 'time', unlim = FALSE))))
attr(time, "variables") <- metadata
attr(data, 'Variables')$dat1$time <- time

thres <- rep(10, 31 * 2 * 3)
dim(thres) <- c(jdays = 31, lon = 2, lat = 3,  model = 1)
str(thres)

clim <- Climdex(data, metric = "t90p", threshold = thres)
str(clim)

ClimProjDiags documentation built on May 29, 2024, 8:56 a.m.