R/loadDecadalForecast.R

Defines functions loadDecadalForecast

Documented in loadDecadalForecast

# loadDecadalForecast.R Load a user-defined spatio-temporal slice from decadal forecasts
#
#     Copyright (C) 2016 Santander Meteorology Group (http://www.meteo.unican.es)
#
#     This program is free software: you can redistribute it and/or modify
#     it under the terms of the GNU General Public License as published by
#     the Free Software Foundation, either version 3 of the License, or
#     (at your option) any later version.
# 
#     This program is distributed in the hope that it will be useful,
#     but WITHOUT ANY WARRANTY; without even the implied warranty of
#     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#     GNU General Public License for more details.
# 
#     You should have received a copy of the GNU General Public License
#     along with this program.  If not, see <http://www.gnu.org/licenses/>.

#' @title Load a grid from a decadal forecast
#' @description Load a user-defined spatio-temporal slice from decadal forecasts
#' @template templateParams
#' @param dictionary Default to TRUE, indicating that a dictionary is used and the .dic file is stored in the same path than the
#' dataset. If the .dic file is stored elsewhere, then the argument is the full path to the .dic file (including the extension,
#' e.g.: \code{"/path/to/the/dictionary_file.dic"}). This is the case for instance when the dataset is stored in a remote URL,
#' and we have a locally stored dictionary for that particular dataset. If FALSE no variable homogenization takes place,
#' and the raw variable, as originally stored in the dataset, will be returned. See details for dictionary specification.
#' @param members Vector of integers indicating the members to be loaded.
#' @param time A character vector indicating the temporal filtering/aggregation 
#' of the output data. Default to \code{"none"}, which returns the original time 
#' series as stored in the dataset. For sub-daily variables, instantantaneous data at 
#' selected verification times can be filtered using one of the character strings 
#' \code{"00"}, \code{"03"}, \code{"06"}, \code{"09"}, \code{"12"}, \code{"15"},
#'  \code{"18"}, \code{"21"},and \code{"00"} when applicable. If daily aggregated data are 
#' required use \code{"DD"}. If the requested variable is static (e.g. orography) it will be ignored. 
#' See the next arguments for time aggregation options.
#' @param aggr.d Character string. Function of aggregation of sub-daily data for daily data calculation. 
#' Currently accepted values are \code{"none"}, \code{"mean"}, \code{"min"}, \code{"max"} and \code{"sum"}.
#' @param aggr.m Same as \code{aggr.d}, bun indicating the aggregation function to compute monthly from daily data.
#' If \code{aggr.m = "none"} (the default), no monthly aggregation is undertaken.
#' 
#' @template templateReturnGridData
#' @template templateDicDetails  
#' @template templateGeolocation
#' @export
#' @author J. Bedia, S. Herrera, M. Iturbide, J.M. Gutierrez 
#' @family loading.grid
#' @importFrom utils tail
#' @importFrom climate4R.UDG C4R.vocabulary
#' @importFrom rJava J
#'
#' @examples \dontrun{
#' latLim <- c(40,50)
#' lonLim <-  c(-5,10)
#' season <- 3:5
#' period <- 1981:1991
#' loginUDG(username = "myuser", password = "mypassword") 
#' tasDECA <- loadDecadalForecast(
#'    dataset = "http://www.meteo.unican.es/tds5/dodsC/specs/gfdl_specs_decadal.ncml", 
#'    latLim = latLim, 
#'    lonLim = lonLim,
#'    var = "tas", 
#'    years = period, 
#'    season = season)
#' }


loadDecadalForecast <- function(dataset,
                                var,
                                dictionary = FALSE, 
                                members = NULL,
                                lonLim = NULL,
                                latLim = NULL,
                                season = NULL,
                                years = NULL,
                                time = "none",
                                aggr.d = "none",
                                aggr.m = "none") {
  time <- match.arg(time, choices = c("none","00","03","06","09","12","15","18","21","DD"))
  aggr.d <- match.arg(aggr.d, choices = c("none", "mean", "min", "max", "sum"))
  if (time != "DD" & aggr.d != "none") {
    aggr.d <- "none"
    message("NOTE: Argument 'aggr.d' ignored as 'time' was set to ", time)
  }
  aggr.m <- match.arg(aggr.m, choices = c("none", "mean", "min", "max", "sum"))
  aux.level <- findVerticalLevel(var)
  var <- aux.level$var
  level <- aux.level$level
  if (dictionary == FALSE) {
    dic <- NULL
    shortName <- var
  } else {
    if (isTRUE(dictionary)) {
      dicPath <- gsub("ncml$", "dic", dataset)
    }
    if (is.character(dictionary)) {
      dicPath <- dictionary
    }
    dic <- dictionaryLookup(dicPath, var, time)
    shortName <- dic$short_name          
  }
  message("[", Sys.time(), "] ", "Opening connection with the UDG...")
  gds <- tryCatch(expr = {
    J("ucar.nc2.dt.grid.GridDataset")$open(dataset)
  }, error = function(e) {
    if (grepl("return status=503", e)) {
      stop("UDG SERVICE TEMPORARILY UNAVAILABLE\nThe UDG server is temporarily unable to service your request due to maintenance downtime or capacity problems, please try again later.\n
                        If the problem persists after 24 h please drop a ticket (http://meteo.unican.es/trac/wiki/udg/ecoms)")
    } else if (grepl("Unauthorized to open dataset", e)) {
      stop("UNAUTHORIZED TO OPEN DATASET\nPlease check your login details in loginECOMS_UDG function.\nIf you don\'t have a valid username/password or OpenID please the UDG Administration Panel (http://www.meteo.unican.es/udg-tap/login)")
    }
  })
  if (is.null(gds)) {
    stop("Requested URL not found\nThe problem may be momentary. Try again and if the error persists please drop a ticket (http://meteo.unican.es/trac/wiki/udg/ecoms)")      
  }
  message("[", Sys.time(), "] ", "Connected successfuly")
  grid <- gds$findGridByShortName(shortName)
  if (is.null(grid)) {
    stop("Variable requested not found\nCheck available variables at http://meteo.unican.es/trac/wiki/udg/ecoms/dataserver/catalog")
  }
  # Forecasts
  if (!is.null(members)) {
    members <- sort(members)
  }
  # latLon <- getLatLonDomainForecast(grid, lonLim, latLim)      
  latLon <- getLatLonDomain(grid, lonLim, latLim)      
  runTimePars <- getRunTimeDomain.decadal(dataset, grid, members, season, years)
  memberRangeList <- getMemberDomain(grid, dataset, members)
  foreTimePars <- getForecastTimeDomain(grid, dataset, dic, runTimePars, time, aggr.d, aggr.m)
  verticalPars <- getVerticalLevelPars(grid, level)
  cube <- makeSubset.decadal(grid, latLon, runTimePars, memberRangeList, foreTimePars, verticalPars)
  auxDates <- as.POSIXlt(cube$foreTimePars$forecastDates$start, tz = "GMT")
  indMonthValid <- which(is.element(auxDates$mon + 1,season))
  if (length(indMonthValid) < dim(cube$mdArray)[grep("^time$", attr(cube$mdArray,"dimensions"))]) {
    dimName <- attr(cube$mdArray, "dimensions")
    cube$mdArray <- cube$mdArray[,,indMonthValid,]
    attr(cube$mdArray, "dimensions") <- dimName
    cube$foreTimePars$forecastDates$start <- cube$foreTimePars$forecastDates$start[indMonthValid]
    cube$foreTimePars$forecastDates$end <- cube$foreTimePars$forecastDates$end[indMonthValid]
  }
  foreTimePars <- NULL
  if (!is.null(dic)) {
    isStandard <- TRUE
    cube$mdArray <- dictionaryTransformForecast(dic, cube$mdArray)
    # var <- derInterface$origVar
  } else {
    isStandard <- FALSE
  }
  if (isTRUE(latLon$revLat)) {
    cube$mdArray <- revArrayLatDim(cube$mdArray)
  }
  # formatting initialization dates
  runTimePars$runDates <- format(as.POSIXct(runTimePars$runDates, tz = "GMT"), format = "%Y-%m-%d %H:%M:%S", usetz = TRUE)
  Variable <- list("varName" = var, "level" = level)
  attr(Variable, "is_standard") <- isStandard
  if (isStandard) {
    vocabulary <- climate4R.UDG::C4R.vocabulary()
    attr(Variable, "units") <- as.character(vocabulary[grep(paste0("^", var, "$"), vocabulary$identifier), 3])
    attr(Variable, "longname") <- as.character(vocabulary[grep(paste0("^", var, "$"), vocabulary$identifier), 2])
  } else {
    attr(Variable, "units") <- grid$getUnitsString()
    attr(Variable, "longname") <- grid$getFullName()
  }
  attr(Variable, "daily_agg_cellfun") <- cube$foreTimePars$aggr.d
  attr(Variable, "monthly_agg_cellfun") <- cube$foreTimePars$aggr.m
  attr(Variable, "verification_time") <- time
  out <- list("Variable" = Variable,
              "Data" = cube$mdArray,
              "xyCoords" = latLon$xyCoords,
              "Dates" = cube$foreTimePars$forecastDates,
              "InitializationDates" = runTimePars$runDates,
              "Members" = names(memberRangeList))
  
  gds$close()
  message("[", Sys.time(), "]", " Done")
  # So far lonlat proj is assumed
  attr(out$xyCoords, "projection") <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs +towgs84=0,0,0"
  # attr(out, "resX") <- (tail(out$xyCoords$x, 1) - out$xyCoords$x[1]) / (length(out$xyCoords$x) - 1)
  # attr(out, "resY") <- (tail(out$xyCoords$y, 1) - out$xyCoords$y[1]) / (length(out$xyCoords$y) - 1)
  if (length(out$xyCoords$x) > 1){
    attr(out$xyCoords, "resX") <- (tail(out$xyCoords$x, 1) - out$xyCoords$x[1]) / (length(out$xyCoords$x) - 1)
  } else {
    attr(out$xyCoords, "resX") <- latLon$xyCoords$resX
  }
  if (length(out$xyCoords$y) > 1){
    attr(out$xyCoords, "resY") <- (tail(out$xyCoords$y, 1) - out$xyCoords$y[1]) / (length(out$xyCoords$y) - 1)
  } else {
    attr(out$xyCoords, "resY") <- latLon$xyCoords$resY
  }
  out$xyCoords["resX"] <- NULL
  out$xyCoords["resY"] <- NULL
  
  if("lon" %in% names(out$xyCoords)){
    attr(out, "resLON") <- NA 
    attr(out, "resLAT") <- NA
  } 
  # Dimension ordering
  x <- attr(out$Data, "dimensions")
  if (length(x) > 1) {
    tab <- c("member", "time", "level", "lat", "lon")
    b <- na.exclude(match(tab, x))
    dimNames <- attr(out$Data, "dimensions")[b]
    out$Data <- aperm(out$Data, perm = b)    
    attr(out$Data, "dimensions")  <- dimNames
  }
  # Source Dataset and other metadata 
  attr(out, "dataset") <- dataset
  attr(out, "source") <- "ECOMS User Data Gateway" 
  attr(out, "URL") <- "<http://meteo.unican.es/trac/wiki/udg/ecoms>"
  return(out)
}      
# End
SantanderMetGroup/loadeR documentation built on July 4, 2023, 4:29 a.m.