https://github.com/cran/FedData
Tip revision: e7952465c2a8026d38c6dd7b03df7c458a87a808 authored by R. Kyle Bocinsky on 12 March 2018, 19:21:35 UTC
version 2.5.2
version 2.5.2
Tip revision: e795246
GHCN_FUNCTIONS.R
# globalVariables(c('.', 'ELEMENT','YEAR','MONTH','LONGITUDE','LATITUDE'))
#' Download and crop the Global Historical Climate Network-Daily data.
#'
#' \code{get_ghcn_daily} returns a named list of length 2:
#' \enumerate{
#' \item 'spatial': A \code{SpatialPointsDataFrame} of the locations of GHCN weather stations
#' in the template, and
#' \item 'tabular': A named list of \code{\link{data.frame}s} with the daily weather data for each station.
#' The name of each list item is the station ID.
#' }
#'
#' @param template A Raster* or Spatial* object to serve
#' as a template for cropping. Alternatively, a character vector providing GHCN station IDs. If missing, all stations
#' will be downloaded!
#' @param label A character string naming the study area.
#' @param elements A character vector of elements to extract.\cr
#' The five core elements are:\cr
#' PRCP = Precipitation (tenths of mm)\cr
#' SNOW = Snowfall (mm)\cr
#' SNWD = Snow depth (mm)\cr
#' TMAX = Maximum temperature (tenths of degrees C)\cr
#' TMIN = Minimum temperature (tenths of degrees C)\cr
#' \cr
#' The other elements are:\cr
#'
#' ACMC = Average cloudiness midnight to midnight from 30-second
#' ceilometer data (percent)\cr
#' ACMH = Average cloudiness midnight to midnight from
#' manual observations (percent)\cr
#' ACSC = Average cloudiness sunrise to sunset from 30-second
#' ceilometer data (percent)\cr
#' ACSH = Average cloudiness sunrise to sunset from manual
#' observations (percent)\cr
#' AWDR = Average daily wind direction (degrees)\cr
#' AWND = Average daily wind speed (tenths of meters per second)\cr
#' DAEV = Number of days included in the multiday evaporation
#' total (MDEV)\cr
#' DAPR = Number of days included in the multiday precipitation
#' total (MDPR)\cr
#' DASF = Number of days included in the multiday snowfall
#' total (MDSF)\cr
#' DATN = Number of days included in the multiday minimum temperature
#' (MDTN)\cr
#' DATX = Number of days included in the multiday maximum temperature
#' (MDTX)\cr
#' DAWM = Number of days included in the multiday wind movement
#' (MDWM)\cr
#' DWPR = Number of days with non-zero precipitation included in
#' multiday precipitation total (MDPR)\cr
#' EVAP = Evaporation of water from evaporation pan (tenths of mm)\cr
#' FMTM = Time of fastest mile or fastest 1-minute wind
#' (hours and minutes, i.e., HHMM)\cr
#' FRGB = Base of frozen ground layer (cm)\cr
#' FRGT = Top of frozen ground layer (cm)\cr
#' FRTH = Thickness of frozen ground layer (cm)\cr
#' GAHT = Difference between river and gauge height (cm)\cr
#' MDEV = Multiday evaporation total (tenths of mm; use with DAEV)\cr
#' MDPR = Multiday precipitation total (tenths of mm; use with DAPR and
#' DWPR, if available)\cr
#' MDSF = Multiday snowfall total \cr
#' MDTN = Multiday minimum temperature (tenths of degrees C; use with DATN)\cr
#' MDTX = Multiday maximum temperature (tenths of degrees C; use with DATX)\cr
#' MDWM = Multiday wind movement (km)\cr
#' MNPN = Daily minimum temperature of water in an evaporation pan
#' (tenths of degrees C)\cr
#' MXPN = Daily maximum temperature of water in an evaporation pan
#' (tenths of degrees C)\cr
#' PGTM = Peak gust time (hours and minutes, i.e., HHMM)\cr
#' PSUN = Daily percent of possible sunshine (percent)\cr
#' SN*# = Minimum soil temperature (tenths of degrees C)
#' where * corresponds to a code
#' for ground cover and # corresponds to a code for soil
#' depth.\cr
#' \cr
#' Ground cover codes include the following:\cr
#' 0 = unknown\cr
#' 1 = grass\cr
#' 2 = fallow\cr
#' 3 = bare ground\cr
#' 4 = brome grass\cr
#' 5 = sod\cr
#' 6 = straw multch\cr
#' 7 = grass muck\cr
#' 8 = bare muck\cr
#' \cr
#' Depth codes include the following:\cr
#' 1 = 5 cm\cr
#' 2 = 10 cm\cr
#' 3 = 20 cm\cr
#' 4 = 50 cm\cr
#' 5 = 100 cm\cr
#' 6 = 150 cm\cr
#' 7 = 180 cm\cr
#' \cr
#' SX*# = Maximum soil temperature (tenths of degrees C)
#' where * corresponds to a code for ground cover
#' and # corresponds to a code for soil depth.\cr
#' See SN*# for ground cover and depth codes. \cr
#' TAVG = Average temperature (tenths of degrees C)
#' [Note that TAVG from source 'S' corresponds
#' to an average for the period ending at
#' 2400 UTC rather than local midnight]\cr
#' THIC = Thickness of ice on water (tenths of mm)\cr
#' TOBS = Temperature at the time of observation (tenths of degrees C)\cr
#' TSUN = Daily total sunshine (minutes)\cr
#' WDF1 = Direction of fastest 1-minute wind (degrees)\cr
#' WDF2 = Direction of fastest 2-minute wind (degrees)\cr
#' WDF5 = Direction of fastest 5-second wind (degrees)\cr
#' WDFG = Direction of peak wind gust (degrees)\cr
#' WDFI = Direction of highest instantaneous wind (degrees)\cr
#' WDFM = Fastest mile wind direction (degrees)\cr
#' WDMV = 24-hour wind movement (km)\cr
#' WESD = Water equivalent of snow on the ground (tenths of mm)\cr
#' WESF = Water equivalent of snowfall (tenths of mm)\cr
#' WSF1 = Fastest 1-minute wind speed (tenths of meters per second)\cr
#' WSF2 = Fastest 2-minute wind speed (tenths of meters per second)\cr
#' WSF5 = Fastest 5-second wind speed (tenths of meters per second)\cr
#' WSFG = Peak gust wind speed (tenths of meters per second)\cr
#' WSFI = Highest instantaneous wind speed (tenths of meters per second)\cr
#' WSFM = Fastest mile wind speed (tenths of meters per second)\cr
#' WT** = Weather Type where ** has one of the following values:\cr
#' \cr
#' 01 = Fog, ice fog, or freezing fog (may include heavy fog)\cr
#' 02 = Heavy fog or heaving freezing fog (not always
#' distinguished from fog)\cr
#' 03 = Thunder\cr
#' 04 = Ice pellets, sleet, snow pellets, or small hail \cr
#' 05 = Hail (may include small hail)\cr
#' 06 = Glaze or rime \cr
#' 07 = Dust, volcanic ash, blowing dust, blowing sand, or
#' blowing obstruction\cr
#' 08 = Smoke or haze \cr
#' 09 = Blowing or drifting snow\cr
#' 10 = Tornado, waterspout, or funnel cloud \cr
#' 11 = High or damaging winds\cr
#' 12 = Blowing spray\cr
#' 13 = Mist\cr
#' 14 = Drizzle\cr
#' 15 = Freezing drizzle \cr
#' 16 = Rain (may include freezing rain, drizzle, and freezing drizzle) \cr
#' 17 = Freezing rain \cr
#' 18 = Snow, snow pellets, snow grains, or ice crystals\cr
#' 19 = Unknown source of precipitation \cr
#' 21 = Ground fog \cr
#' 22 = Ice fog or freezing fog\cr
#' \cr
#' WV** = Weather in the Vicinity where ** has one of the following
#' values:\cr
#' 01 = Fog, ice fog, or freezing fog (may include heavy fog)\cr
#' 03 = Thunder\cr
#' 07 = Ash, dust, sand, or other blowing obstruction\cr
#' 18 = Snow or ice crystals\cr
#' 20 = Rain or snow shower
#' @param years A numeric vector indicating which years to get.
#' @param raw.dir A character string indicating where raw downloaded files should be put.
#' The directory will be created if missing. Defaults to './RAW/GHCN/'.
#' @param extraction.dir A character string indicating where the extracted and cropped GHCN shapefiles should be put.
#' The directory will be created if missing. Defaults to './EXTRACTIONS/GHCN/'.
#' @param standardize Select only common year/month/day? Defaults to FALSE.
#' @param force.redo If an extraction for this template and label already exists, should a new one be created? Defaults to FALSE.
#' @return A named list containing the 'spatial' and 'tabular' data.
#' @export
#' @importFrom readr read_fwf
#' @importFrom magrittr %>%
#' @examples
#' \dontrun{
#' # Extract data for the Village Ecodynamics Project 'VEPIIN' study area:
#' # http://village.anth.wsu.edu
#' vepPolygon <- polygon_from_extent(raster::extent(672800,740000,4102000,4170000),
#' proj4string='+proj=utm +datum=NAD83 +zone=12')
#'
#' # Get the daily GHCN data (GLOBAL)
#' # Returns a list: the first element is the spatial locations of stations,
#' # and the second is a list of the stations and their daily data
#' GHCN.prcp <- get_ghcn_daily(template=vepPolygon, label='VEPIIN', elements=c('prcp'))
#'
#' # Plot the VEP polygon
#' plot(vepPolygon)
#'
#' # Plot the spatial locations
#' plot(GHCN.prcp$spatial, pch=1, add=T)
#' legend('bottomleft', pch=1, legend='GHCN Precipitation Records')
#'
#' # Elements for which you require the same data
#' # (i.e., minimum and maximum temperature for the same days)
#' # can be standardized using standardize==T
#' GHCN.temp <- get_ghcn_daily(template=vepPolygon,
#' label='VEPIIN',
#' elements=c('tmin','tmax'),
#' standardize=T)
#'
#' # Plot the VEP polygon
#' plot(vepPolygon)
#'
#' # Plot the spatial locations
#' plot(GHCN.temp$spatial, pch=1, add=T)
#' legend('bottomleft', pch=1, legend='GHCN Temperature Records')
#' }
get_ghcn_daily <- function(template = NULL,
label = NULL,
elements = NULL,
years = NULL,
raw.dir = "./RAW/GHCN",
extraction.dir = paste0("./EXTRACTIONS/", label, "/GHCN"),
standardize = F,
force.redo = F) {
raw.dir <- normalizePath(paste0(raw.dir,"/."), mustWork = FALSE)
extraction.dir <- normalizePath(paste0(extraction.dir,"/."), mustWork = FALSE)
dir.create(raw.dir, showWarnings = FALSE, recursive = TRUE)
dir.create(extraction.dir, showWarnings = FALSE, recursive = TRUE)
if (is.null(template) & is.null(label)) {
label <- "allStations"
}
if (!is.null(template) & is.null(label)) {
stop("Template provided but no label given.")
}
message("(Down)Loading GHCN station inventory.")
if (!force.redo & file.exists(paste0(extraction.dir, "/", label, "_GHCN_stations.shp"))) {
stations.sp <- rgdal::readOGR(dsn = extraction.dir, layer = paste0(label, "_GHCN_stations"), verbose = F)
} else {
stations.sp <- get_ghcn_inventory(template = template, raw.dir = raw.dir)
suppressWarnings(rgdal::writeOGR(stations.sp,
dsn = normalizePath(paste0(extraction.dir,"/.")),
layer = paste0(label, "_GHCN_stations"),
driver = "ESRI Shapefile",
overwrite_layer = TRUE))
}
# If the user didn't specify target elements, get them all.
if (!is.null(elements)) {
stations.sp <- stations.sp[stations.sp@data[, "ELEMENT"] %in% toupper(elements), ]
missing.elements <- setdiff(toupper(elements), unique(stations.sp$ELEMENT))
if (length(missing.elements) == length(elements))
stop("No elements available from included stations during given years.")
if (length(missing.elements) > 0)
warning("Elements not available: ", paste(missing.elements, collapse = ", "))
}
elements <- unique(stations.sp$ELEMENT)
if (standardize) {
stations.sp.splits <- split(as.character(stations.sp$ELEMENT), f = stations.sp$ID, drop = T)
stations.sp.splits.all <- sapply(stations.sp.splits, function(x) {
all(sapply(toupper(elements), function(y) {
y %in% x
}))
})
stations.sp <- stations.sp[stations.sp$ID %in% names(stations.sp.splits.all)[stations.sp.splits.all], ]
}
if (!is.null(years)) {
stations.sp <- stations.sp[stations.sp$YEAR_START <= min(years) & stations.sp$YEAR_END >= max(years), ]
}
stations.sp <- stations.sp[!duplicated(stations.sp@data[, c("ID", "LATITUDE", "LONGITUDE")]), c("ID", "NAME")]
if (!force.redo) {
daily <- tryCatch(lapply(elements, function(element) {
ifelse(!is.null(years), paste0(extraction.dir, "/", label, "_GHCN_", element, "_", min(years), "-", max(years), ".Rds"),
paste0(extraction.dir, "/", label, "_GHCN_", element, "_all_years.Rds")) %>% readr::read_rds()
}), warning = function(w) {
return(NULL)
})
if (!is.null(daily)) {
names(daily) <- elements
daily <- lapply(as.character(stations.sp$ID), function(station) {
stationDaily <- tryCatch(lapply(daily, "[[", station), error = function(e) {
return(NULL)
})
stationDaily <- stationDaily[!sapply(stationDaily, is.null)]
return(stationDaily)
})
names(daily) <- as.character(stations.sp$ID)
daily <- daily[!sapply(daily, is.null)]
return(list(spatial = stations.sp, tabular = daily))
}
}
daily <- lapply(stations.sp$ID, function(station) {
message("(Down)Loading GHCN station data for station ", as.character(station))
tryCatch(station <- get_ghcn_daily_station(ID = station, elements = elements, years = years, raw.dir = raw.dir, standardize = standardize,
force.redo = force.redo), error = function(e) {
message("Error (down)Loading GHCN station data for station ", as.character(station))
return(NULL)
})
return(station)
})
names(daily) <- stations.sp$ID
daily <- daily[(lapply(daily, names) %>% sapply(length)) <= length(elements) & (lapply(daily, names) %>% sapply(length)) >
0]
daily.split <- lapply(as.character(elements), function(element) {
lapply(daily, "[[", element)
})
names(daily.split) <- elements
junk <- lapply(as.character(elements), function(element) {
saveRDS(daily.split[[element]], ifelse(!is.null(years), paste0(extraction.dir, "/", label, "_GHCN_", element, "_", min(years),
"-", max(years), ".Rds"), paste0(extraction.dir, "/", label, "_GHCN_", element, "_all_years.Rds")), compress = "xz")
})
return(list(spatial = stations.sp, tabular = daily))
}
#' Download the daily data for a GHCN weather station.
#'
#' @param ID A character string giving the station ID.
#' @param raw.dir A character string indicating where raw downloaded files should be put.
#' @param force.redo If this weather station has been downloaded before, should it be updated? Defaults to FALSE.
#' @return A character string representing the full local path of the GHCN station data.
#' @export
#' @keywords internal
download_ghcn_daily_station <- function(ID, raw.dir, force.redo = F) {
dir.create(raw.dir, recursive = T, showWarnings = F)
url <- paste("ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/all/", ID, ".dly", sep = "")
if (!force.redo) {
download_data(url = url, destdir = raw.dir, timestamping = T)
} else {
download_data(url = url, destdir = raw.dir, timestamping = F)
}
return(normalizePath(paste0(raw.dir, "/", ID, ".dly")))
}
#' Download and extract the daily data for a GHCN weather station.
#'
#' \code{get_ghcn_daily_station} returns a named list of \code{\link{data.frame}s}, one for
#' each \code{elements}. If \code{elements} is undefined, it returns all available weather
#' tables for the station
#'
#' @param ID A character string giving the station ID.
#' @param elements A character vector of elements to extract.\cr
#' The five core elements are:\cr
#' PRCP = Precipitation (tenths of mm)\cr
#' SNOW = Snowfall (mm)\cr
#' SNWD = Snow depth (mm)\cr
#' TMAX = Maximum temperature (tenths of degrees C)\cr
#' TMIN = Minimum temperature (tenths of degrees C)\cr
#' \cr
#' The other elements are:\cr
#'
#' ACMC = Average cloudiness midnight to midnight from 30-second
#' ceilometer data (percent)\cr
#' ACMH = Average cloudiness midnight to midnight from
#' manual observations (percent)\cr
#' ACSC = Average cloudiness sunrise to sunset from 30-second
#' ceilometer data (percent)\cr
#' ACSH = Average cloudiness sunrise to sunset from manual
#' observations (percent)\cr
#' AWDR = Average daily wind direction (degrees)\cr
#' AWND = Average daily wind speed (tenths of meters per second)\cr
#' DAEV = Number of days included in the multiday evaporation
#' total (MDEV)\cr
#' DAPR = Number of days included in the multiday precipitation
#' total (MDPR)\cr
#' DASF = Number of days included in the multiday snowfall
#' total (MDSF)\cr
#' DATN = Number of days included in the multiday minimum temperature
#' (MDTN)\cr
#' DATX = Number of days included in the multiday maximum temperature
#' (MDTX)\cr
#' DAWM = Number of days included in the multiday wind movement
#' (MDWM)\cr
#' DWPR = Number of days with non-zero precipitation included in
#' multiday precipitation total (MDPR)\cr
#' EVAP = Evaporation of water from evaporation pan (tenths of mm)\cr
#' FMTM = Time of fastest mile or fastest 1-minute wind
#' (hours and minutes, i.e., HHMM)\cr
#' FRGB = Base of frozen ground layer (cm)\cr
#' FRGT = Top of frozen ground layer (cm)\cr
#' FRTH = Thickness of frozen ground layer (cm)\cr
#' GAHT = Difference between river and gauge height (cm)\cr
#' MDEV = Multiday evaporation total (tenths of mm; use with DAEV)\cr
#' MDPR = Multiday precipitation total (tenths of mm; use with DAPR and
#' DWPR, if available)\cr
#' MDSF = Multiday snowfall total \cr
#' MDTN = Multiday minimum temperature (tenths of degrees C; use with DATN)\cr
#' MDTX = Multiday maximum temperature (tenths of degrees C; use with DATX)\cr
#' MDWM = Multiday wind movement (km)\cr
#' MNPN = Daily minimum temperature of water in an evaporation pan
#' (tenths of degrees C)\cr
#' MXPN = Daily maximum temperature of water in an evaporation pan
#' (tenths of degrees C)\cr
#' PGTM = Peak gust time (hours and minutes, i.e., HHMM)\cr
#' PSUN = Daily percent of possible sunshine (percent)\cr
#' SN*# = Minimum soil temperature (tenths of degrees C)
#' where * corresponds to a code
#' for ground cover and # corresponds to a code for soil
#' depth.\cr
#' \cr
#' Ground cover codes include the following:\cr
#' 0 = unknown\cr
#' 1 = grass\cr
#' 2 = fallow\cr
#' 3 = bare ground\cr
#' 4 = brome grass\cr
#' 5 = sod\cr
#' 6 = straw multch\cr
#' 7 = grass muck\cr
#' 8 = bare muck\cr
#' \cr
#' Depth codes include the following:\cr
#' 1 = 5 cm\cr
#' 2 = 10 cm\cr
#' 3 = 20 cm\cr
#' 4 = 50 cm\cr
#' 5 = 100 cm\cr
#' 6 = 150 cm\cr
#' 7 = 180 cm\cr
#' \cr
#' SX*# = Maximum soil temperature (tenths of degrees C)
#' where * corresponds to a code for ground cover
#' and # corresponds to a code for soil depth.\cr
#' See SN*# for ground cover and depth codes. \cr
#' TAVG = Average temperature (tenths of degrees C)
#' [Note that TAVG from source 'S' corresponds
#' to an average for the period ending at
#' 2400 UTC rather than local midnight]\cr
#' THIC = Thickness of ice on water (tenths of mm)\cr
#' TOBS = Temperature at the time of observation (tenths of degrees C)\cr
#' TSUN = Daily total sunshine (minutes)\cr
#' WDF1 = Direction of fastest 1-minute wind (degrees)\cr
#' WDF2 = Direction of fastest 2-minute wind (degrees)\cr
#' WDF5 = Direction of fastest 5-second wind (degrees)\cr
#' WDFG = Direction of peak wind gust (degrees)\cr
#' WDFI = Direction of highest instantaneous wind (degrees)\cr
#' WDFM = Fastest mile wind direction (degrees)\cr
#' WDMV = 24-hour wind movement (km)\cr
#' WESD = Water equivalent of snow on the ground (tenths of mm)\cr
#' WESF = Water equivalent of snowfall (tenths of mm)\cr
#' WSF1 = Fastest 1-minute wind speed (tenths of meters per second)\cr
#' WSF2 = Fastest 2-minute wind speed (tenths of meters per second)\cr
#' WSF5 = Fastest 5-second wind speed (tenths of meters per second)\cr
#' WSFG = Peak gust wind speed (tenths of meters per second)\cr
#' WSFI = Highest instantaneous wind speed (tenths of meters per second)\cr
#' WSFM = Fastest mile wind speed (tenths of meters per second)\cr
#' WT** = Weather Type where ** has one of the following values:\cr
#' \cr
#' 01 = Fog, ice fog, or freezing fog (may include heavy fog)\cr
#' 02 = Heavy fog or heaving freezing fog (not always
#' distinguished from fog)\cr
#' 03 = Thunder\cr
#' 04 = Ice pellets, sleet, snow pellets, or small hail \cr
#' 05 = Hail (may include small hail)\cr
#' 06 = Glaze or rime \cr
#' 07 = Dust, volcanic ash, blowing dust, blowing sand, or
#' blowing obstruction\cr
#' 08 = Smoke or haze \cr
#' 09 = Blowing or drifting snow\cr
#' 10 = Tornado, waterspout, or funnel cloud \cr
#' 11 = High or damaging winds\cr
#' 12 = Blowing spray\cr
#' 13 = Mist\cr
#' 14 = Drizzle\cr
#' 15 = Freezing drizzle \cr
#' 16 = Rain (may include freezing rain, drizzle, and freezing drizzle) \cr
#' 17 = Freezing rain \cr
#' 18 = Snow, snow pellets, snow grains, or ice crystals\cr
#' 19 = Unknown source of precipitation \cr
#' 21 = Ground fog \cr
#' 22 = Ice fog or freezing fog\cr
#' \cr
#' WV** = Weather in the Vicinity where ** has one of the following
#' values:\cr
#' 01 = Fog, ice fog, or freezing fog (may include heavy fog)\cr
#' 03 = Thunder\cr
#' 07 = Ash, dust, sand, or other blowing obstruction\cr
#' 18 = Snow or ice crystals\cr
#' 20 = Rain or snow shower
#' @param years A numeric vector indicating which years to get.
#' @param raw.dir A character string indicating where raw downloaded files should be put.
#' @param standardize Select only common year/month/day? Defaults to FALSE.
#' @param force.redo If this weather station has been downloaded before, should it be updated? Defaults to FALSE.
#' @return A named list of \code{\link{data.frame}s}, one for each \code{elements}.
#' @export
#' @keywords internal
get_ghcn_daily_station <- function(ID,
elements = NULL,
years = NULL,
raw.dir,
standardize = F,
force.redo = F) {
file <- download_ghcn_daily_station(ID = ID, raw.dir = paste(raw.dir, "/DAILY/", sep = ""), force.redo = force.redo)
# GHCN files are fixed-width. The numbers here refer to those column widths.
daily <- readr::read_fwf(file, col_positions = readr::fwf_positions(start = c(1, 12, 16, 18, seq(22, 262, 8)), end = c(11,
15, 17, 21, seq(26, 266, 8)), col_names = c("STATION", "YEAR", "MONTH", "ELEMENT", paste0("D", 1:31))), col_types = paste0(c("cicc",
rep("i", 31)), collapse = ""))
# If the user didn't specify target elements, get them all.
if (is.null(elements)) {
elements <- unique(daily$ELEMENT)
}
elements <- toupper(elements)
daily %<>% dplyr::filter_(~ELEMENT %in% elements)
missing.elements <- setdiff(toupper(elements), unique(daily$ELEMENT))
if (length(missing.elements) > 0)
warning("Elements not available: ", paste(missing.elements, collapse = ", "))
# If the user didn't specify target elements, get them all.
if (!is.null(years)) {
daily %<>% dplyr::filter_(~YEAR %in% years)
}
daily %<>% dplyr::mutate_all(dplyr::funs_(quote(ifelse(. == -9999, NA, .))))
## Separate by element
out.list <- lapply(elements, function(element) {
return(daily %>% dplyr::filter_(~ELEMENT == element) %>% dplyr::select_(quote(-ELEMENT)))
})
## If standardize, select only common year/month/day, and make NA if both not present
if (standardize) {
yearMonths <- lapply(out.list, function(element) {
element %<>% dplyr::arrange_(~YEAR, ~MONTH)
return(paste("Y", element[["YEAR"]], "M", element[["MONTH"]], sep = ""))
})
all.yearMonths <- Reduce(intersect, yearMonths)
out.list <- lapply(out.list, function(element) {
element.yearMonths <- paste("Y", element[["YEAR"]], "M", element[["MONTH"]], sep = "")
return(element %>% dplyr::filter(element.yearMonths %in% all.yearMonths))
})
}
names(out.list) <- elements
return(out.list)
}
#' Download and crop the inventory of GHCN stations.
#'
#' \code{get_ghcn_inventory} returns a \code{SpatialPolygonsDataFrame} of the GHCN stations within
#' the specified \code{template}. If template is not provided, returns the entire GHCN inventory.
#'
#' Stations with multiple elements will have multiple points. This allows for easy mapping of stations
#' by element availability.
#'
#' @param template A Raster* or Spatial* object to serve
#' as a template for cropping.
#' @param elements A character vector of elements to extract.
#' Common elements include 'tmin', 'tmax', and 'prcp'.
#' @param raw.dir A character string indicating where raw downloaded files should be put.
#' The directory will be created if missing.
#' @return A \code{SpatialPolygonsDataFrame} of the GHCN stations within
#' the specified \code{template}
#' @export
#' @keywords internal
get_ghcn_inventory <- function(template = NULL, elements = NULL, raw.dir) {
if (!is.null(template) & !(class(template) %in% c("SpatialPolygonsDataFrame", "SpatialPolygons", "character"))) {
template <- polygon_from_extent(template)
}
url <- "ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-inventory.txt"
destdir <- raw.dir
download_data(url = url, destdir = destdir)
url <- "ftp://ftp.ncdc.noaa.gov/pub/data/ghcn/daily/ghcnd-stations.txt"
destdir <- raw.dir
download_data(url = url, destdir = destdir)
# GHCN files are fixed-width. The numbers here refer to those column widths.
station.inventory <- readr::read_fwf(paste(raw.dir, "/ghcnd-inventory.txt", sep = ""), readr::fwf_positions(start = c(1, 13,
22, 32, 37, 42), end = c(11, 20, 30, 35, 40, 45), col_names = c("ID", "LATITUDE", "LONGITUDE", "ELEMENT", "YEAR_START",
"YEAR_END")), col_types = "cddcii")
stations <- readr::read_fwf(paste(raw.dir, "/ghcnd-stations.txt", sep = ""), readr::fwf_positions(start = c(1, 13, 22, 32, 42),
end = c(11, 20, 30, 38, 72), col_names = c("ID", "LATITUDE", "LONGITUDE", "ELEVATION", "NAME")), col_types = "cdddc")
# Convert to SPDF
stations.sp <- sp::SpatialPointsDataFrame(coords = station.inventory %>% dplyr::select_(~LONGITUDE, ~LATITUDE), data = station.inventory %>%
dplyr::left_join(stations %>% dplyr::select_("ID", "NAME"), by = "ID") %>% dplyr::select_("ID", "NAME", "LATITUDE", "LONGITUDE",
"ELEMENT", "YEAR_START", "YEAR_END") %>% as.data.frame(), proj4string = sp::CRS("+proj=longlat +datum=WGS84"))
if (!is.null(elements)) {
stations.sp <- stations.sp[stations.sp$ELEMENT %in% toupper(elements), ]
}
if (!is.null(template)) {
if (class(template) == "character") {
missing.stations <- setdiff(template, unique(stations.sp$ID))
if (length(missing.stations) > 0)
warning("Stations not available: ", paste(missing.stations, collapse = ", "))
stations.sp <- stations.sp[stations.sp$ID %in% template, ]
} else {
template <- methods::as(template, "SpatialPolygons")
stations.sp <- stations.sp[!is.na(sp::over(stations.sp, sp::spTransform(template, sp::CRS(raster::projection(stations.sp))))),
]
}
}
return(stations.sp)
}
#' Convert a list of station data to a single data frame.
#'
#' \code{station_to_data_frame} returns a \code{data.frame} of the GHCN station data list.
#'
#' This function unwraps the station data and merges all data into a single data frame,
#' with the first column being in the \code{Date} class.
#'
#' @param station.data A named list containing station data
#' @return A \code{data.frame} of the containing the unwrapped station data
#' @export
#' @keywords internal
station_to_data_frame <- function(station.data) {
data.list <- lapply(1:length(station.data), function(i) {
X <- station.data[[i]]
# Get just the climate info
annual.records <- as.matrix(X[, 4:34])
# Get the number of days per month in the records
n.days <- Hmisc::monthDays(as.Date(paste(X$YEAR, X$MONTH, "01", sep = "-")))
## Unnwrap each row, accounting for number of days in the month
annual.records.unwrapped <- unwrap_rows(annual.records, n.days)
dates <- as.Date(unlist(mapply(FUN = function(days, dates) {
paste(dates, days, sep = "-")
}, sapply(n.days, function(x) {
1:x
}), paste(X$YEAR, X$MONTH, sep = "-"))))
annual.records.unwrapped <- data.table::data.table(dates, annual.records.unwrapped)
names(annual.records.unwrapped) <- c("DATE", names(station.data)[i])
data.table::setkey(annual.records.unwrapped, "DATE")
return(annual.records.unwrapped)
})
return(Reduce(function(x, y) merge(x, y, all = TRUE), data.list))
}
