Temporal aggregation of gridded data — period_apply

Aggregates gridded time series data to coarser temporal scales. Accepts an sxts object, a Raster* object, or a NetCDF file path; when a filename is supplied, data are imported through nc2xts first. The aggregation period is controlled by period and period_multiplier. For common aggregation functions ("mean", "sum", "min", "max", "median", "var", "sd"), the function very efficient column-wise function from matrixStats package, which ensures good computational efficiency. Unsupported functions (e.g. custom functions) fall back to a per-column lapply which is significantly slower.

Usage

period_apply_nc(
  data = NULL,
  filename = NA,
  varname = NA,
  period = "months",
  period_multiplier = 1,
  FUN = "mean",
  ...
)

Arguments

data: An sxts object, or a Raster* object. Leave NULL when supplying filename and varname.
filename: Optional NetCDF file path to import if data is not provided.
varname: Optional variable name to extract from filename.
period: Period string passed to xts::endpoints (e.g."months", "years").
period_multiplier: Integer multiplier for custom period lengths (default 1).
FUN: Summary function as a string ("mean", "sum", etc.) or a function.
...: Additional arguments passed to nc2xts when filename and varname are supplied.

Value

An sxts object when the input is sxts or NetCDF; an xts when the input is a Raster*.

Examples

# Synthetic sxts
set.seed(123)
dates <- seq(as.POSIXct("2000-01-01"), as.POSIXct("2000-12-31"), by = "day")
coords <- data.frame(x = c(1, 2, 3, 4), y = c(1, 1, 1, 1))
vals <- matrix(rnorm(length(dates) * 4, 10, 5), nrow = length(dates), ncol = 4)
ncdf_sxts <- sxts(vals, order.by = dates, coords = coords,
                  projection = "+proj=longlat")

# Monthly mean
result <- period_apply_nc(ncdf_sxts, period = "months", FUN = "mean")

# Quarterly sum
result <- period_apply_nc(ncdf_sxts, period = "months",
                          period_multiplier = 3, FUN = "sum")