reddPrec (version 2.0.4)

gridPcp: Gridded dataset creation

Description

This function creates a gridded precipitation dataset from a station-based dataset.

Usage

gridPcp(
  prec,
  grid,
  sts,
  dates,
  ncpu,
  thres,
  neibs,
  coords,
  crs,
  coords_as_preds
)

Arguments

prec

matrix or data.frame containing the original (cleaned) precipitation data. Each column represents one station. The names of columns must coincide with the names of the stations.

grid

SpatRaster. Collection of rasters representing each one of the predictors.

sts

matrix or data.frame. A column "ID" (unique ID of stations) is required. The rest of the columns (all of them) will act as predictors of the model.

dates

vector of class "Date" with all days of observations (yyyy-mm-dd).

ncpu

number of processor cores used to parallel computing.

thres

numeric. Maximum radius (in km) where neighboring stations will be searched. NA value uses the whole spatial domain.

neibs

integer. Number of nearest neighbors to use.

coords

vector of two character elements. Names of the fields in "sts" containing longitude and latitude.

crs

character. Coordinates system in EPSG format (e.g.: "EPSG:4326").

coords_as_preds

logical. If TRUE (default), "coords" are also taken as predictors.

Examples

if (FALSE) {
alt <- terra::rast(volcano, crs = 'EPSG:4326')
terra::ext(alt) <- c(-1,3,38,42)
lon <- terra::rast(cbind(terra::crds(alt),terra::crds(alt)[,1]),type='xyz',crs='EPSG:4326')
lat <- terra::rast(cbind(terra::crds(alt),terra::crds(alt)[,2]),type='xyz',crs='EPSG:4326')
dcoast <- terra::costDist(alt,target=min(terra::values(alt)))/1000
grid <- c(alt, lon, lat, dcoast)
names(grid) <- c('alt', 'lon', 'lat', 'dcoast')

prec <- round(matrix(rnorm(2*25, mean = 1.2, sd = 4), 2, 25), 1)+1
prec[prec<0] <- 0
colnames(prec) <- paste0('sts_',1:25)
sts <- data.frame(ID = paste0('sts_',1:25), as.data.frame(terra::spatSample(grid, 25)))
gridPcp(prec, grid, sts, 
        dates = seq.Date(as.Date('2023-04-01'),as.Date('2023-04-02'),by='day'),
        thres = NA, coords = c('lon','lat'),coords_as_preds = TRUE, 
        crs = 'EPSG:4326', neibs = 10, ncpu = 2)

r <- terra::rast(c('./pred/20230401.tif','./err/20230401.tif'))
}