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5. ensembleClimatologies.R
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5. ensembleClimatologies.R
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## ------------------------------------------------------------------ ##
## ##
## ClimateData v3.0 ##
## R Pipelines for climate data request and processing ##
## ##
## -------------------------------------------- ##
## ##
## Jorge Assis [ jorgemfa@gmail.com ] ##
## biodiversityDS ##
## biodiversitydatascience.com ##
## ##
## ------------------------------------------------------------------ ##
cat("# ---------------\n")
cat("# Ensemble climatologies //",depthInterpolation,"\n")
time.i <- Sys.time()
## ------------------------------
## ------------------------------
## Get matching timeSteps and test for range of values
minValuesListClimatology <- numeric(0)
maxValuesListClimatology <- numeric(0)
for( i in 1:length(availableClimatologiesModels) ) {
metadata <- list.files(availableClimatologiesModels[i],full.names=TRUE,pattern=".txt")
metadata <- metadata[grepl(firstToupper(depthInterpolation),metadata)]
metadata <- read.csv(metadata, sep=";")
timeSteps.i <- metadata$value[ metadata$descriptor == "climatologyPeriod"]
timeSteps.i <- substr(timeSteps.i,1,4):substr(timeSteps.i,6,9)
if( i == 1) { timeSteps <- timeSteps.i }
if( i != 1) { timeSteps <- intersect(timeSteps , timeSteps.i) }
minValuesListClimatology <- c(minValuesListClimatology, min(as.numeric(strsplit(metadata[which(metadata$descriptor == "minValues"),2],", ")[[1]]), na.rm=T) )
maxValuesListClimatology <- c(maxValuesListClimatology, max(as.numeric(strsplit(metadata[which(metadata$descriptor == "maxValues"),2],", ")[[1]]), na.rm=T) )
}
## ------------------------------ ##
metadata <- list.files(mainFolderBaselineClimatology,full.names=TRUE,pattern=".txt")
metadata <- metadata[grepl(firstToupper(depthInterpolation),metadata)]
metadata <- read.csv(metadata, sep=";")
minValuesListBaseline <- min(as.numeric(strsplit(metadata[which(metadata$descriptor == "minValues"),2],", ")[[1]]),na.rm=T)
maxValuesListBaseline <- max(as.numeric(strsplit(metadata[which(metadata$descriptor == "maxValues"),2],", ")[[1]]),na.rm=T)
## ------------------------------ ##
metadataUnitsClimatologies <- unique(sapply(availableClimatologiesModels,function(x) { metadata.i <- read.csv(paste0(x,"/rawDataMetadata.txt"), sep=";", header=TRUE) ; metadata.i[which(metadata.i$descriptor == "units"),2] } ))
if( length(metadataUnitsClimatologies) > 1) { stop("Error :: 183")}
metadataUnitsBaseline <- read.csv(paste0(mainFolderBaselineClimatology,"/rawDataMetadata.txt"), sep=";", header=TRUE)
metadataUnitsBaseline <- metadataUnitsBaseline[which(metadataUnitsBaseline$descriptor == "units"),2]
## ------------------------------ ##
# Correct climatology
correctClimatology <- FALSE
correctBaseline <- FALSE
if( metadataUnitsClimatologies != "degC" & metadataUnitsClimatologies != "degrees_C" & metadataUnitsBaseline == "degrees_C" ) {
stop("Review :: 281")
}
if( metadataUnitsClimatologies == "0.001" & metadataUnitsBaseline == "1e-3" ) {
metadataUnitsClimatologies <- "1e-3"
}
if( metadataUnitsClimatologies == "%" & metadataUnitsBaseline == "(0 - 1)" ) {
metadataUnitsClimatologies <- "1"
metadataUnitsBaseline <- "1"
climatologyCorrect <- 100
climatologyCorrectType <- "div"
correctClimatology <- TRUE
minValuesListClimatology <- minValuesListClimatology / climatologyCorrect
maxValuesListClimatology <- maxValuesListClimatology / climatologyCorrect
}
if( metadataUnitsClimatologies == "K" & metadataUnitsBaseline == "K" ) {
metadataUnitsClimatologies <- "degC"
metadataUnitsBaseline <- "degC"
}
if( metadataUnitsClimatologies == "%" & metadataUnitsBaseline == "1" ) {
metadataUnitsClimatologies <- "1"
climatologyCorrect <- 100
climatologyCorrectType <- "div"
correctClimatology <- TRUE
minValuesListClimatology <- minValuesListClimatology / climatologyCorrect
maxValuesListClimatology <- maxValuesListClimatology / climatologyCorrect
}
if( metadataUnitsClimatologies == "kg m-3" & metadataUnitsBaseline == "mg m-3" ) {
metadataUnitsClimatologies <- "mg m-3"
climatologyCorrect <- 1000
climatologyCorrectType <- "prod"
correctClimatology <- TRUE
minValuesListClimatology <- minValuesListClimatology * climatologyCorrect
maxValuesListClimatology <- maxValuesListClimatology * climatologyCorrect
}
if( metadataUnitsClimatologies == "mol m-3" & metadataUnitsBaseline == "mmol m-3" ) {
metadataUnitsClimatologies <- "mmol m-3"
climatologyCorrect <- 1000
climatologyCorrectType <- "prod"
correctClimatology <- TRUE
minValuesListClimatology <- minValuesListClimatology * climatologyCorrect
maxValuesListClimatology <- maxValuesListClimatology * climatologyCorrect
}
if( metadataUnitsClimatologies == "mmol m-3" & metadataUnitsBaseline == "mol m-3" ) {
metadataUnitsBaseline <- "mmol m-3"
baselineCorrect <- 1000
baselineCorrectType <- "prod"
correctBaseline <- TRUE
minValuesListBaseline <- minValuesListBaseline * climatologyCorrect
maxValuesListBaseline <- maxValuesListBaseline * climatologyCorrect
}
if( metadataUnitsClimatologies == "mol m-2 s-1" & metadataUnitsBaseline == "mg m-2 day-1" ) {
metadataUnitsClimatologies <- "mg m-2 day-1"
climatologyCorrect <- 12010.700000000053 * 60 * 60 * 24 # mol m-2 s-1 to milligrams of Carbon per day
climatologyCorrectType <- "prod"
correctClimatology <- TRUE
minValuesListClimatology <- minValuesListClimatology * climatologyCorrect
maxValuesListClimatology <- maxValuesListClimatology * climatologyCorrect
}
if( metadataUnitsClimatologies != metadataUnitsBaseline ) { stop("Error :: 0033") }
## -------------
metadataUnits <- metadataUnitsClimatologies
## ------------------------------ ##
## ------------------------------ ##
## Generate final ensemble .nc File
shape <- raster(paste0(bathymetryFolder,"/",bathymetryFiles[1]))
shape <- crop(shape,extent(outcomeExtent))
shape[!is.na(shape)] <- 1
ncFileName <- paste0("climatology",firstToupper(outcomePeriodType),firstToupper(depthInterpolation),".nc")
if( outcomePeriodType == "decade") {
period <- timeSteps[which(substring(timeSteps,4,4) == 0)]
period <- as.numeric(as.Date(paste0(period,"-01-01"), "%Y-%m-%d") - as.Date("01-01-1970", "%d-%m-%Y"))
if( substring(timeSteps[length(timeSteps)],4,4)=="0" ) { period <- period[-length(period)]}
}
if( outcomePeriodType == "year") {
period <- as.numeric(as.Date(paste0(timeSteps,"-01-01"), "%Y-%m-%d") - as.Date("01-01-1970", "%d-%m-%Y"))
}
exportFolderClimatologies <- paste0(exportFolder,"/mainClimatologies/",availableClimatologies)
if( file.exists(paste0(exportFolderClimatologies,"/",ncFileName))) { file.remove(paste0(exportFolderClimatologies,"/",ncFileName)) }
nc <- ncCreate(path=paste0(exportFolderClimatologies,"/",ncFileName),
xmax = extent(shape)[2], xmin = extent(shape)[1], xlength = ncol(shape),
ymax = extent(shape)[4], ymin = extent(shape)[3], ylength = nrow(shape),
realm = depthInterpolation,
experiment = experiment,
period = period)
close.nc( nc )
nc <- open.nc( paste0(exportFolderClimatologies,"/",ncFileName), write=TRUE )
ncBaseline <- nc_open( paste0(mainFolderBaselineClimatology,"/",ncFileName))
## --------
minValuesList <- ltMinValuesList <- meanValuesList <- ltMaxValuesList <- maxValuesList <- numeric(0)
for( pred in outcomePeriodPredictors[outcomePeriodPredictors != "sd"] ) {
for( t in 1:length(period)) {
climatologyArray <- array(dim = c(ncol(shape), nrow(shape), length(availableClimatologiesModels) ))
for( m in 1:length(availableClimatologiesModels)) {
ncFileName.m <- paste0(availableClimatologiesModels[m],"/climatology",firstToupper(outcomePeriodType),firstToupper(depthInterpolation),".nc")
nc.m <- nc_open( ncFileName.m, readunlim=FALSE )
climatologyArray[,,m] <- ncvar_get( nc.m, paste0(variable,"_",tolower(pred)), start=c(1,1,t), count=c(ncol(shape),nrow(shape),1))
nc_close( nc.m )
}
climatologyArray <- arma3DMean(climatologyArray,3)
if( correctClimatology ) {
if( climatologyCorrectType == "prod" ) {
climatologyArray <- climatologyArray * climatologyCorrect
}
if( climatologyCorrectType == "div" ) {
climatologyArray <- climatologyArray / climatologyCorrect
}
}
# Apply to baseline
climatologyArrayBaseline.time <- ncvar_get( ncBaseline, "time")
climatologyArrayBaseline.time <- substr(as.Date(climatologyArrayBaseline.time,origin = "1970-01-01"),1,4)
climatologyArrayBaseline.time <- which(as.numeric(climatologyArrayBaseline.time) %in% baselinePeriod)
if( length(climatologyArrayBaseline.time) == 1 ) {
climatologyArrayBaseline <- ncvar_get( ncBaseline, paste0(variable.m,"_",tolower(pred)), start=c(1,1,climatologyArrayBaseline.time), count=c(ncol(shape),nrow(shape),1))
}
if( length(climatologyArrayBaseline.time) > 1 ) {
variable.n <- ifelse(variable.m == "nppv" & "PP_mean" %in% names(ncBaseline$var),"PP",variable.m)
climatologyArrayBaseline <- ncvar_get( ncBaseline, paste0(variable.n,"_",tolower(pred)), start=c(1,1,min(climatologyArrayBaseline.time)), count=c(ncol(shape),nrow(shape),length(climatologyArrayBaseline.time)))
climatologyArrayBaseline <- arma3DMean(climatologyArrayBaseline,3)
}
if( correctBaseline ) {
if( baselineCorrectType == "prod" ) {
climatologyArrayBaseline <- climatologyArrayBaseline * baselineCorrect
} else { stop("Review :: 445")}
}
climatologyArray <- climatologyArrayBaseline + climatologyArray
# if( t == 1 & pred == "Mean" & length(unique(log10Ceiling(c( mean(climatologyArray,na.rm=T) , mean(climatologyArrayBaseline,na.rm=T))))) > 1 ) { stop("Error :: 333") }
# if( t == 1 & pred == "Mean" & length(unique(log10Ceiling(c( max(climatologyArray,na.rm=T) , max(climatologyArrayBaseline,na.rm=T))))) > 1 ) { stop("Error :: 334") }
# Correct to maximum allowed value
if( pred != "Range" ) {
climatologyArray[climatologyArray < listVariables[listVariables$name == variable,"minPossibleValue"] ] <- listVariables[listVariables$name == variable,"minPossibleValue"]
climatologyArray[climatologyArray > listVariables[listVariables$name == variable,"maxPossibleValue"] ] <- listVariables[listVariables$name == variable,"maxPossibleValue"]
}
if( t == 1) {
if( pred == "Max" ) { predictorLongName <- paste0("Maximum ", variableLongName); predictorStandardName <- "maximum"; varRangeMax <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T)) }
if( pred == "ltMax" ) { predictorLongName <- paste0("Long-term maximum ", variableLongName); predictorStandardName <- "long_term_maximum"; varRangeLtMax <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T)) }
if( pred == "Mean" ) { predictorLongName <- paste0("Average ", variableLongName); predictorStandardName <- "mean"; varRangeMean <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T)) }
if( pred == "ltMin" ) { predictorLongName <- paste0("Long-term minimum ", variableLongName); predictorStandardName <- "long_term_minimum"; varRangeLtMin <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T)) }
if( pred == "Min" ) { predictorLongName <- paste0("Minimum ", variableLongName); predictorStandardName <- "minimum"; varRangeMin <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T)) }
if( pred == "Range" ) { predictorLongName <- paste0("Range ", variableLongName); predictorStandardName <- "range" }
ncAddVar(nc, varname = paste0(variable,"_",tolower(pred)), varUnits = metadataUnitsClimatologies, long_name = predictorLongName, "crs", compression=9)
}
var.put.nc(nc, variable = paste0(variable,"_",tolower(pred)), data = climatologyArray, start = c( 1, 1, t), count=c(ncol(shape),nrow(shape),1))
if( pred == "Max" ) { maxValuesList <- range(c(maxValuesList,range(climatologyArray,na.rm=T))) }
if( pred == "ltMax" ) { ltMaxValuesList <- range(c(ltMaxValuesList,range(climatologyArray,na.rm=T))) }
if( pred == "Mean" ) { meanValuesList <- range(c(meanValuesList,range(climatologyArray,na.rm=T))) }
if( pred == "ltMin" ) { ltMinValuesList <- range(c(ltMinValuesList,range(climatologyArray,na.rm=T))) }
if( pred == "Min" ) { minValuesList <- range(c(minValuesList,range(climatologyArray,na.rm=T))) }
}
}
## ------------------------------ ##
# Standard deviation of models
for( t in 1:length(period)) {
climatologyArray <- array(dim = c(ncol(shape), nrow(shape), length(availableClimatologiesModels) ))
for( m in 1:length(availableClimatologiesModels)) {
ncFileName.m <- paste0(availableClimatologiesModels[m],"/climatology",firstToupper(outcomePeriodType),firstToupper(depthInterpolation),".nc")
nc.m <- nc_open( ncFileName.m, readunlim=FALSE )
climatologyArray[,,m] <- ncvar_get( nc.m, paste0(variable,"_","mean"), start=c(1,1,t), count=c(ncol(shape),nrow(shape),1))
nc_close( nc.m )
}
cl <- makeCluster(nCores)
climatologyArray <- parApply(cl = cl, X = climatologyArray, MARGIN = 1:2, FUN = sd)
stopCluster(cl)
closeAllConnections()
if( t == 1) {
predictorLongName <- paste0("Standard deviation ", variableLongName); predictorStandardName <- "std"; varRangeSD <- c(min(climatologyArray,na.rm=T),max(climatologyArray,na.rm=T))
ncAddVar(nc, varname = paste0(variable,"_","sd"), varUnits = metadataUnits, long_name = predictorLongName, "crs", compression=9)
}
var.put.nc(nc, variable = paste0(variable,"_","sd"), data = climatologyArray, start = c( 1, 1, t), count=c(ncol(shape),nrow(shape),1))
}
close.nc(nc)
nc_close( ncBaseline )
## ------------------------------ ##
modelList <- character(0)
for( i in 1:length(availableClimatologiesModels) ) {
metadata.i <- read.csv(paste0(availableClimatologiesModels[i],"/rawDataMetadata.txt"), sep=";", header=TRUE)
modelList <- c(modelList,metadata.i[which(metadata.i$descriptor == "dataSource"),2])
}
metadata <- data.frame( descriptor = c("variableLongName" ,
"variableStandardName",
"variable",
"realm",
"units",
"absoluteValues",
"dataSource",
"dataProduct",
"dataDataset",
"experiment",
"ensemble",
"climatologyType",
"climatologyPeriod",
"climatologyPeriodN",
"vectorValues",
"minValues",
"maxValues",
"resolution",
"nCells"),
value = c(variableLongName,
variableStandardName,
ifelse( variable == "intpp","nppv",variable),
ifelse(realm == "Benthic",paste0(realm,firstToupper(depthInterpolation)),realm),
metadataUnitsClimatologies,
listVariables[listVariables$name == variable,4],
paste0(modelList,collapse = ", "),
"Ensemble",
"Ensemble",
experiment,
length(modelList),
firstToupper(outcomePeriodType),
paste0(min(as.numeric(substr(as.Date(period, origin = "1970-01-01"),1,4))),"-",max(as.numeric(substr(as.Date(period, origin = "1970-01-01"),1,4)))),
length(period),
paste0(c("min","ltmin","mean","ltmax","max"), collapse = ", "),
paste0(c( minValuesList[1], ltMinValuesList[1], meanValuesList[1], ltMaxValuesList[1], maxValuesList[1] ), collapse = ", "),
paste0(c( minValuesList[2], ltMinValuesList[2], meanValuesList[2], ltMaxValuesList[2], maxValuesList[2] ), collapse = ", "),
res(shape)[1],
ncell(shape)
) )
metadata$value <- gsub(";", ",", metadata$value, fixed = TRUE)
write.table(metadata,file=paste0(exportFolderClimatologies,"/",gsub(".nc","Metadata.txt",ncFileName)),col.names = TRUE,sep=";",dec=".",row.names = FALSE,quote=FALSE)
## ------------------
closeAllConnections()
gc(reset=TRUE, full = TRUE)
cat("# End process // ET:", round(difftime(Sys.time(), time.i, units='hours'), digits = 3) ,"hours\n")
## --------------------------------------------------------
## --------------------------------------------------------