R/ncdf_jra55_minmax_surf.R
In rijaf-iri/CDTDownload: Download gridded data used by Climate Data Tools (CDT)
#' Download and extract the Japanese Re-Analysis 55 Years (JRA-55) minimum and maximum temperature at 2 meters
#'
#' This function download JRA-55 minimum and maximum temperature at 2 meters above ground and extract it
#' over a specified region.
#'
#' @param start_date Start date to be downloaded, a character in the form "YYYY-MM-DD".
#' @param end_date End date to be downloaded, a character in the form "YYYY-MM-DD".
#' @param output.dir Full path to the directory where the downloaded and extracted files will be saved;
#' default to the working directory.
#' @param grads.bin Full path name of GrADS executable. For Mac and Linux, you can use \code{"grads"}
#' if GrADS is in your PATH environment variable.
#' @param range.lon A numeric vector of length 2; minimum and maximum longitude of the area to be extracted;
#' default c(-180, 180).
#' @param range.lat A numeric vector of length 2; minimum and maximum latitude of the area to be extracted;
#' default c(-89.570, 89.570).
#' @param tstep The time steps of the extracted data. Useful values are \code{"daily"} (aggregated to daily data)
#' and \code{"hourly3"} (3-hourly data).
#' @param username Your user ID for JMA Data Dissemination System (JDDS).
#' @param password Your password for JDDS.
#'
#' @return A directory named "GRIB" and "Extracted" are created. "GRIB" contains the downloaded GRIB data and
#' "Extracted" contains the extracted data in NetCDF format over the area that you specified.
#'
#' @examples
#'
#' \dontrun{
#' temp_jra55_minmax_surf(
#' start_date = "2019-05-26",
#' end_date = "2019-05-26",
#' output.dir = "~/Desktop/DATA/JRA55",
#' grads.bin = "grads",
#' range.lon = c(42, 52),
#' range.lat = c(-26, -11.5),
#' tstep = "daily",
#' username = "my.UID",
#' password = "my.PWD"
#' )
#' }
#'
#' @export
temp_jra55_minmax_surf <- function(
start_date = "2019-05-01",
end_date = "2019-05-31",
output.dir = getwd(),
grads.bin = "grads",
range.lon = c(-180, 180),
range.lat = c(-89.570, 89.570),
tstep = c("daily", "hourly3"),
username = NA, password = NA
)
{
download_jra55_minmax_surf(start_date, end_date,
output.dir,
username, password)
extarct_jra55_minmax_surf(start_date, end_date,
output.dir, grads.bin,
range.lon, range.lat,
tstep)
}
#' Extract the Japanese Re-Analysis 55 Years (JRA-55) minimum and maximum temperature at 2 meters
#'
#' This function extract an existing downloaded GRIB data from JRA-55 minimum and maximum temperature at 2 meters above ground
#' over a specified region.
#'
#' @param start_date Start date to be extracted, a character in the form "YYYY-MM-DD".
#' @param end_date End date to be extracted, a character in the form "YYYY-MM-DD".
#' @param output.dir Full path to the directory where the extracted files will be saved.
#' @param grads.bin Full path name of GrADS executable. For Mac and Linux, you can use \code{"grads"}
#' if GrADS is in your PATH environment variable.
#' @param range.lon A numeric vector of length 2; minimum and maximum longitude of the area to be extracted.
#' @param range.lat A numeric vector of length 2; minimum and maximum latitude of the area to be extracted.
#' @param tstep The time steps of the extracted data. Useful values are \code{"daily"} (aggregated to daily data)
#' and \code{"hourly3"} (3-hourly data).
#'
#' @return The extracted data are located under the directory called "Extracted".
#'
#' @examples
#'
#' \dontrun{
#' extarct_jra55_minmax_surf(
#' start_date = "2019-05-26",
#' end_date = "2019-05-26",
#' output.dir = "~/Desktop/DATA/JRA55",
#' grads.bin = "grads",
#' range.lon = c(42, 52),
#' range.lat = c(-26, -11.5),
#' tstep = "daily"
#' )
#' }
#'
#' @export
extarct_jra55_minmax_surf <- function(
start_date, end_date,
output.dir, grads.bin,
range.lon, range.lat, tstep
)
{
if(WindowsOS()){
if(!file.exists(grads.bin))
stop(paste(grads.bin, "not found!"))
}else{
pthgs <- split_path(grads.bin)
if(length(pthgs) == 1){
ret <- system(paste('which', grads.bin), intern = TRUE)
if(length(ret) == 0) stop("grads not found!")
}else{
if(!file.exists(grads.bin))
stop(paste(grads.bin, "not found!"))
}
}
grads_wraper_jra55_minmax_surf(start_date, end_date, output.dir, grads.bin)
tstep <- tstep[1]
hours <- time_step_3hour(start_date, end_date)
dir.month <- format(hours, "%Y%m")
ret <- lapply(unique(dir.month), function(mo){
dir.mon <- file.path(output.dir, "GRIB", mo)
get_jra55_minmax_surf(dir.mon, range.lon, range.lat, output.dir, tstep)
})
invisible()
}
get_jra55_minmax_surf <- function(
dir.month, range.lon, range.lat,
dir.out, tstep
)
{
dir.ext <- file.path(dir.out, "Extracted", tstep)
if(!dir.exists(dir.ext)) dir.create(dir.ext, recursive = TRUE)
file.tmax <- file.path(dir.month, "tmax.nc")
if(!file.exists(file.tmax))
stop(paste(file.tmax, "not found!"))
create_nc_jra55_minmax_surf("tmax", file.tmax, dir.ext, range.lon, range.lat, tstep)
file.tmin <- file.path(dir.month, "tmin.nc")
if(!file.exists(file.tmin))
stop(paste(file.tmin, "not found!"))
create_nc_jra55_minmax_surf("tmin", file.tmin, dir.ext, range.lon, range.lat, tstep)
invisible()
}
create_nc_jra55_minmax_surf <- function(
varid, ncfile, ncdir,
range.lon, range.lat, tstep
)
{
temp <- read_jra55_minmax_surf(ncfile, range.lon, range.lat, tstep)
dx <- ncdim_def("Longitude", "degrees_east", temp$x)
dy <- ncdim_def("Latitude", "degrees_north", temp$y)
vars <- switch(varid,
"tmax" = list("maximum temperature", max),
"tmin" = list("maximum temperature", min)
)
longname <- switch(tstep,
"daily" = paste("daily", vars[[1]], "computed from 3 hourly JRA55"),
"hourly3" = paste("3-hourly", vars[[1]], "JRA55")
)
outnc.z <- ncvar_def(varid, "degC", list(dx, dy), -9999, longname, "float", compression = 9)
dir.temp <- file.path(ncdir, varid)
if(!dir.exists(dir.temp)) dir.create(dir.temp, recursive = TRUE)
if(tstep == "daily"){
idx <- split(seq_along(temp$t), format(temp$t, "%Y%m%d"))
jour <- names(idx)
ret <- lapply(seq_along(idx), function(j){
fileout <- file.path(dir.temp, paste0(varid, "_", jour[j], ".nc"))
tmp <- temp$z[, , idx[[j]]]
tmp <- apply(tmp, 1:2, vars[[2]], na.rm = TRUE)
tmp[is.na(tmp) | is.nan(tmp)] <- -9999
nc <- nc_create(fileout, outnc.z)
ncvar_put(nc, outnc.z, tmp)
nc_close(nc)
})
}
if(tstep == "hourly3"){
tm <- format(temp$t, "%Y%m%d%H")
ret <- lapply(seq_along(tm), function(j){
fileout <- file.path(dir.temp, paste0(varid, "_", tm[j], ".nc"))
tmp <- temp$z[, , j]
tmp[is.na(tmp) | is.nan(tmp)] <- -9999
nc <- nc_create(fileout, outnc.z)
ncvar_put(nc, outnc.z, tmp)
nc_close(nc)
})
}
invisible()
}
read_jra55_minmax_surf <- function(ncfile, range.lon, range.lat, tstep)
{
nc <- nc_open(ncfile)
x <- nc$dim[[1]]$vals
y <- nc$dim[[2]]$vals
tm <- nc$dim[[4]]$vals
units <- nc$dim[[4]]$units
z <- ncvar_get(nc, varid = "var")
nc_close(nc)
x <- ((x + 180) %% 360) - 180
orig <- paste0(strsplit(units, " ")[[1]][3:4], collapse = " ")
orig <- as.POSIXct(orig, tz = "GMT", format = "%Y-%m-%d %H:%M")
tm <- orig + tm * 60
ix <- x >= range.lon[1] & x <= range.lon[2]
iy <- y >= range.lat[1] & y <= range.lat[2]
x <- x[ix]
y <- y[iy]
z <- z[ix, iy, ] - 273.15
ox <- order(x)
x <- x[ox]
z <- z[ox, , ]
i2 <- duplicated(x)
if(any(i2)){
x <- x[!i2]
z <- z[!i2, , ]
}
list(t = tm, x = x, y = y, z = z)
}
rijaf-iri/CDTDownload documentation built on June 5, 2019, 12:37 a.m.
R Package Documentation
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#' Download and extract the Japanese Re-Analysis 55 Years (JRA-55) minimum and maximum temperature at 2 meters
#'
#' This function download JRA-55 minimum and maximum temperature at 2 meters above ground and extract it
#' over a specified region.
#'
#' @param start_date Start date to be downloaded, a character in the form "YYYY-MM-DD".
#' @param end_date End date to be downloaded, a character in the form "YYYY-MM-DD".
#' @param output.dir Full path to the directory where the downloaded and extracted files will be saved;
#' default to the working directory.
#' @param grads.bin Full path name of GrADS executable. For Mac and Linux, you can use \code{"grads"}
#' if GrADS is in your PATH environment variable.
#' @param range.lon A numeric vector of length 2; minimum and maximum longitude of the area to be extracted;
#' default c(-180, 180).
#' @param range.lat A numeric vector of length 2; minimum and maximum latitude of the area to be extracted;
#' default c(-89.570, 89.570).
#' @param tstep The time steps of the extracted data. Useful values are \code{"daily"} (aggregated to daily data)
#' and \code{"hourly3"} (3-hourly data).
#' @param username Your user ID for JMA Data Dissemination System (JDDS).
#' @param password Your password for JDDS.
#'
#' @return A directory named "GRIB" and "Extracted" are created. "GRIB" contains the downloaded GRIB data and
#' "Extracted" contains the extracted data in NetCDF format over the area that you specified.
#'
#' @examples
#'
#' \dontrun{
#' temp_jra55_minmax_surf(
#' start_date = "2019-05-26",
#' end_date = "2019-05-26",
#' output.dir = "~/Desktop/DATA/JRA55",
#' grads.bin = "grads",
#' range.lon = c(42, 52),
#' range.lat = c(-26, -11.5),
#' tstep = "daily",
#' username = "my.UID",
#' password = "my.PWD"
#' )
#' }
#'
#' @export
temp_jra55_minmax_surf <- function(
start_date = "2019-05-01",
end_date = "2019-05-31",
output.dir = getwd(),
grads.bin = "grads",
range.lon = c(-180, 180),
range.lat = c(-89.570, 89.570),
tstep = c("daily", "hourly3"),
username = NA, password = NA
)
{
download_jra55_minmax_surf(start_date, end_date,
output.dir,
username, password)
extarct_jra55_minmax_surf(start_date, end_date,
output.dir, grads.bin,
range.lon, range.lat,
tstep)
}
#' Extract the Japanese Re-Analysis 55 Years (JRA-55) minimum and maximum temperature at 2 meters
#'
#' This function extract an existing downloaded GRIB data from JRA-55 minimum and maximum temperature at 2 meters above ground
#' over a specified region.
#'
#' @param start_date Start date to be extracted, a character in the form "YYYY-MM-DD".
#' @param end_date End date to be extracted, a character in the form "YYYY-MM-DD".
#' @param output.dir Full path to the directory where the extracted files will be saved.
#' @param grads.bin Full path name of GrADS executable. For Mac and Linux, you can use \code{"grads"}
#' if GrADS is in your PATH environment variable.
#' @param range.lon A numeric vector of length 2; minimum and maximum longitude of the area to be extracted.
#' @param range.lat A numeric vector of length 2; minimum and maximum latitude of the area to be extracted.
#' @param tstep The time steps of the extracted data. Useful values are \code{"daily"} (aggregated to daily data)
#' and \code{"hourly3"} (3-hourly data).
#'
#' @return The extracted data are located under the directory called "Extracted".
#'
#' @examples
#'
#' \dontrun{
#' extarct_jra55_minmax_surf(
#' start_date = "2019-05-26",
#' end_date = "2019-05-26",
#' output.dir = "~/Desktop/DATA/JRA55",
#' grads.bin = "grads",
#' range.lon = c(42, 52),
#' range.lat = c(-26, -11.5),
#' tstep = "daily"
#' )
#' }
#'
#' @export
extarct_jra55_minmax_surf <- function(
start_date, end_date,
output.dir, grads.bin,
range.lon, range.lat, tstep
)
{
if(WindowsOS()){
if(!file.exists(grads.bin))
stop(paste(grads.bin, "not found!"))
}else{
pthgs <- split_path(grads.bin)
if(length(pthgs) == 1){
ret <- system(paste('which', grads.bin), intern = TRUE)
if(length(ret) == 0) stop("grads not found!")
}else{
if(!file.exists(grads.bin))
stop(paste(grads.bin, "not found!"))
}
}
grads_wraper_jra55_minmax_surf(start_date, end_date, output.dir, grads.bin)
tstep <- tstep[1]
hours <- time_step_3hour(start_date, end_date)
dir.month <- format(hours, "%Y%m")
ret <- lapply(unique(dir.month), function(mo){
dir.mon <- file.path(output.dir, "GRIB", mo)
get_jra55_minmax_surf(dir.mon, range.lon, range.lat, output.dir, tstep)
})
invisible()
}
get_jra55_minmax_surf <- function(
dir.month, range.lon, range.lat,
dir.out, tstep
)
{
dir.ext <- file.path(dir.out, "Extracted", tstep)
if(!dir.exists(dir.ext)) dir.create(dir.ext, recursive = TRUE)
file.tmax <- file.path(dir.month, "tmax.nc")
if(!file.exists(file.tmax))
stop(paste(file.tmax, "not found!"))
create_nc_jra55_minmax_surf("tmax", file.tmax, dir.ext, range.lon, range.lat, tstep)
file.tmin <- file.path(dir.month, "tmin.nc")
if(!file.exists(file.tmin))
stop(paste(file.tmin, "not found!"))
create_nc_jra55_minmax_surf("tmin", file.tmin, dir.ext, range.lon, range.lat, tstep)
invisible()
}
create_nc_jra55_minmax_surf <- function(
varid, ncfile, ncdir,
range.lon, range.lat, tstep
)
{
temp <- read_jra55_minmax_surf(ncfile, range.lon, range.lat, tstep)
dx <- ncdim_def("Longitude", "degrees_east", temp$x)
dy <- ncdim_def("Latitude", "degrees_north", temp$y)
vars <- switch(varid,
"tmax" = list("maximum temperature", max),
"tmin" = list("maximum temperature", min)
)
longname <- switch(tstep,
"daily" = paste("daily", vars[[1]], "computed from 3 hourly JRA55"),
"hourly3" = paste("3-hourly", vars[[1]], "JRA55")
)
outnc.z <- ncvar_def(varid, "degC", list(dx, dy), -9999, longname, "float", compression = 9)
dir.temp <- file.path(ncdir, varid)
if(!dir.exists(dir.temp)) dir.create(dir.temp, recursive = TRUE)
if(tstep == "daily"){
idx <- split(seq_along(temp$t), format(temp$t, "%Y%m%d"))
jour <- names(idx)
ret <- lapply(seq_along(idx), function(j){
fileout <- file.path(dir.temp, paste0(varid, "_", jour[j], ".nc"))
tmp <- temp$z[, , idx[[j]]]
tmp <- apply(tmp, 1:2, vars[[2]], na.rm = TRUE)
tmp[is.na(tmp) | is.nan(tmp)] <- -9999
nc <- nc_create(fileout, outnc.z)
ncvar_put(nc, outnc.z, tmp)
nc_close(nc)
})
}
if(tstep == "hourly3"){
tm <- format(temp$t, "%Y%m%d%H")
ret <- lapply(seq_along(tm), function(j){
fileout <- file.path(dir.temp, paste0(varid, "_", tm[j], ".nc"))
tmp <- temp$z[, , j]
tmp[is.na(tmp) | is.nan(tmp)] <- -9999
nc <- nc_create(fileout, outnc.z)
ncvar_put(nc, outnc.z, tmp)
nc_close(nc)
})
}
invisible()
}
read_jra55_minmax_surf <- function(ncfile, range.lon, range.lat, tstep)
{
nc <- nc_open(ncfile)
x <- nc$dim[[1]]$vals
y <- nc$dim[[2]]$vals
tm <- nc$dim[[4]]$vals
units <- nc$dim[[4]]$units
z <- ncvar_get(nc, varid = "var")
nc_close(nc)
x <- ((x + 180) %% 360) - 180
orig <- paste0(strsplit(units, " ")[[1]][3:4], collapse = " ")
orig <- as.POSIXct(orig, tz = "GMT", format = "%Y-%m-%d %H:%M")
tm <- orig + tm * 60
ix <- x >= range.lon[1] & x <= range.lon[2]
iy <- y >= range.lat[1] & y <= range.lat[2]
x <- x[ix]
y <- y[iy]
z <- z[ix, iy, ] - 273.15
ox <- order(x)
x <- x[ox]
z <- z[ox, , ]
i2 <- duplicated(x)
if(any(i2)){
x <- x[!i2]
z <- z[!i2, , ]
}
list(t = tm, x = x, y = y, z = z)
}
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