version 1.2.42

cran · Sep 25, 2017 · 00b52f4 · 00b52f4
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diff --git a/DESCRIPTION b/DESCRIPTION
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+Package: rSQM
+Type: Package
+Title: Statistical Downscaling Toolkit for Climate Change Scenario
+        using Non Parametric Quantile Mapping
+Version: 1.2.42
+Date: 2017-09-20
+Authors@R: c(person("Jaepil Cho", role="aut", email="jpcho89@gmail"),
+			       person("Wonil Cho", role=c("aut", "cre"), email="climate.service@apcc21.org"),
+			       person("Imgook Jung", role="aut", email="igjung@apcc21.org"))
+Author: Jaepil Cho [aut],
+  Wonil Cho [aut, cre],
+  Imgook Jung [aut]
+Maintainer: Wonil Cho <climate.service@apcc21.org>
+Description: Conducts statistical downscaling of daily CMIP5 (Coupled Model Intercomparison Project 5) climate change scenario data at a station level using empirical quantile mapping method by Jaepil Cho et al. (2016) <doi:10.1002/ird.2035>.
+License: GPL (>= 2)
+LazyData: TRUE
+RoxygenNote: 6.0.1
+Depends: R (>= 3.3.3)
+Imports: ncdf4, zoo, stringr, EcoHydRology, dplyr, gsubfn, yaml, mise,
+        reshape2, qmap, ggplot2
+Suggests: knitr, rmarkdown, testthat
+NeedsCompilation: no
+Packaged: 2017-09-25 00:53:23 UTC; jowonil
+VignetteBuilder: knitr
+Repository: CRAN
+Date/Publication: 2017-09-25 08:27:42 UTC
diff --git a/MD5 b/MD5
@@ -0,0 +1,49 @@
+2e5fe4813264a0b741a51e2fdbdac242 *DESCRIPTION
+c2bf446f4749cdb3205dafe8a5023d3c *NAMESPACE
+5045ba5a023d8ba975d1a62e566fcdad *R/CalSradiation.R
+eedd2e72379cfe4de97835672419ce8a *R/CheckDaysOfYear.R
+98bf8c16687bafcaf4fc52b475ef7fb7 *R/Cmip5Var2Stn.R
+c0ee2dcc77985e571ea66833ef0ea0e0 *R/ConvertGhcnDaily.R
+089e327d3155f100aa889109daa0d123 *R/DailyExtractAll.R
+edaef2baa79a8f7ede095a46181180ef *R/DailyQMapAll.R
+1dfe2ac56a9b042587d7e76842e9546a *R/ExtractPointValue.R
+8d889e85bfb26eec848fe0068352e700 *R/Fill360Date.R
+55dc94a1d93bc5172a070e06e110a823 *R/Fill365Date.R
+651891ff9e4f6e7d21b0479c1ebe80d1 *R/FillDate.R
+f61896863f62bbdff81e39f19572c9fc *R/GetCommonPeriod.R
+ff6107a9dc0e50dc16077fe557cbc7db *R/GetQmapFit.R
+0ad4c5460ab9e709fd3affdd3a891525 *R/GetQmapFit2.R
+d816a5430c19250b787000d136c0ae85 *R/GetVarLists4CMIP5.R
+f0fbc8005ccbd25c15ca7a5e6234fa7f *R/GhcnDailyUpdate.R
+fdf7c50e94fdfdc3bf7223f159053514 *R/Interpolate360Days2Caldendar.R
+24b3a13a73242fb751a836e90920ce4a *R/Interpolate365Days2Calendar.R
+4b6bff9e9eb280da89d12bac3ae98fd0 *R/LoadCmip5DataFromAdss.R
+029f96bef1701e9a7b5d5994363046df *R/NumberOfDays.R
+bdcae5b317820089f251d2c0ce1fcb5c *R/ObsDataSummary.R
+d4073a9fb17b022f5a63306a91a9e2d5 *R/Qmap.R
+6db030ba7fecfa9d2efedf1011fab4e4 *R/ReadNetCDF4.R
+8cfae3cb3983d4dbab49f869c5452677 *R/ReadObsData.R
+c2b65248faa82d5531148d22ef360997 *R/SetWorkingDir.R
+7aaa5ec4ad423346e306e9b261f1192a *R/SetWorkingEnvironment.R
+8983035e8fc7a42970ae0bb59925098c *R/deco.R
+3ae83b2673ed910f63608c90c2d87bd8 *R/doQmap.R
+b5445f6813b3cf0432807ed64eadee5a *R/rSQMSampleProject.R
+2b3ff2d846aba293afc5abdc31268ed6 *build/vignette.rds
+5291dfb44a8e8ad492a728be12cfc3a9 *inst/doc/rSQM-workflow.Rmd
+b3270637aaf6527f57ca466fea5057bf *inst/doc/rSQM-workflow.html
+d72cc4aae3959dcd0414254a1a0838f8 *inst/extdata/Sample_3-Stations.csv
+3ece3707c6e5ffa9aff2792cd03f7468 *inst/extdata/Sample_ID108.csv
+cc582e504e6c53169552708ad954395d *inst/extdata/Sample_ID133.csv
+54b968dce347d43e3522e6ae7a107275 *inst/extdata/Sample_ID159.csv
+fe4e61c3298ab81e874c7f0a1656d7be *inst/extdata/rSQM.yaml
+62ca7232748a0c63932702f677fc7af2 *inst/extdata/sample_script.R
+91e2cdc155420dec7e50ba675d2585fb *man/DailyExtractAll.Rd
+3955ca2d09e205909fd7d91308b78d4c *man/DailyQMapAll.Rd
+47daab70cad66560e7f61aa116990e5f *man/GhcnDailyUpdate.Rd
+6761169179a352393eec9823483c64f3 *man/LoadCmip5DataFromAdss.Rd
+ac51157ec31a01a7655b8960b8dc693b *man/ObsDataSummary.Rd
+10113ce0620cff3c929bbea64e5d4b03 *man/SetWorkingEnvironment.Rd
+012ad76edddb7d1e3bcf4018aaa73358 *man/rSQMSampleProject.Rd
+67b6be1d36eacd0e44bc4385bd764d25 *tests/testthat.R
+77758fdd79a6220e95acf51358a3abb4 *tests/testthat/test_loadExternalEnvironmentalArguments.R
+5291dfb44a8e8ad492a728be12cfc3a9 *vignettes/rSQM-workflow.Rmd
diff --git a/NAMESPACE b/NAMESPACE
@@ -0,0 +1,27 @@
+importFrom("stats","aggregate","filter","approx","splinefun")
+importFrom("utils","capture.output","download.file","glob2rx","read.csv","read.fwf","read.table","setTxtProgressBar","txtProgressBar","unzip","write.csv")
+importFrom(dplyr,"%>%")
+importFrom(utils,globalVariables)
+importFrom(ggplot2,"%+%")
+importFrom(ggplot2,aes)
+importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_rect)
+importFrom(ggplot2,geom_text)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,xlim)
+importFrom(ggplot2,ylim)
+importFrom(ggplot2,geom_line)
+importFrom(ggplot2,labs)
+importFrom(ggplot2,theme)
+importFrom(ggplot2,ggsave)
+importFrom(ggplot2,element_text)
+importFrom(ggplot2,geom_point)
+importFrom(qmap,fitQmapQUANT)
+importFrom(qmap,doQmapQUANT)
+export(SetWorkingEnvironment)
+export(LoadCmip5DataFromAdss)
+export(GhcnDailyUpdate)
+export(DailyExtractAll)
+export(DailyQMapAll)
+export(ObsDataSummary)
+export(rSQMSampleProject)
diff --git a/R/CalSradiation.R b/R/CalSradiation.R
@@ -0,0 +1,18 @@
+CalSradiation <- function(obs, stnid, stndir, stnfile) {
+
+  if(!any(is.na(obs$tmin)) & !any(is.na(obs$tmax))){
+    obs$tmin[obs$tmin > obs$tmax] = obs$tmax[obs$tmin > obs$tmax]
+  }
+  stns <- read.csv(file.path(stndir, stnfile) ,header=T)
+  stns <- stns[,c("ID","Y")]
+  colnames(stns) <- c('ID', 'Lat')
+  lat <- stns[which(stnid == stns[,1]),2]
+  jday <- strptime(obs[,c("date")], "%Y-%m-%d")$yday+1
+
+  isNA <- which(is.na(obs[,"rsds"]) & !is.na(obs[,"tmax"]) & !is.na(obs[,"tmin"]))
+  if(length(isNA[]) >= 1) {
+    obs[isNA,"rsds"] = EcoHydRology::Solar(lat,jday[isNA], obs[isNA,"tmax"], obs[isNA,"tmin"], latUnits='degrees')/1000.0
+    # 1000: Unit conversion kj/m2/day --> MJ/m2 (Default unit of Solar() is Kj/m2)
+  }
+  return(obs)
+}
diff --git a/R/CheckDaysOfYear.R b/R/CheckDaysOfYear.R
@@ -0,0 +1,18 @@
+CheckDaysOfYear <- function(sdate, edate, nday) {
+
+
+  sdate = as.Date(sdate)
+  edate = as.Date(edate)
+
+  difcald = as.integer(edate - sdate + 1)
+  difmon = (zoo::as.yearmon(edate)- zoo::as.yearmon(sdate))*12 + 1
+  dif360d = as.integer(difmon + 0.5) * 30
+  dif365d = as.integer(difmon + 0.5) /12  * 365
+
+  if(abs(nday - difcald) <5) { str = "cald" }
+  if (abs(nday - dif365d) <5) { str = "365d" }
+  if (abs(nday - dif360d) <5) { str = "360d" }
+
+  return(str)
+
+}
diff --git a/R/Cmip5Var2Stn.R b/R/Cmip5Var2Stn.R
@@ -0,0 +1,62 @@
+Cmip5Var2Stn <- function(stnid, varnms, rcpnm, wdir, mdlnm) {
+
+#  setwd(wdir)
+  nvar = length(varnms)
+  #rcpname = c("historical", "rcp26", "rcp45", "rcp60", "rcp85")
+  for (i in 1:nvar) {
+
+    # User have to define RCP scenario : rcp[i]
+    #rcpfile = paste(mdlnm,"_",rcpname[(rcpid+1)],"_",varnms[i],".csv",sep="")
+    rcpfile = file.path(wdir, paste(mdlnm,"_",rcpnm,"_",varnms[i],".csv",sep=""))
+
+    if(i==1) {
+
+      if(file.exists(rcpfile)) {
+        rcp_var1 = read.csv(rcpfile, header=T, na.strings = -99.00)
+        coln = match(stnid, names(rcp_var1))
+        nrows = length(rcp_var1[,1])
+        rcpstn = rcp_var1[ ,c(1,coln)]
+        colnames(rcpstn) = c("date", varnms[i])
+        rcpstn$date = as.Date(rcpstn$date)
+      } else {
+        sdate = as.Date("1976-01-01")
+        edate = as.Date("2100-12-31")
+        dummydate = seq(sdate, edate, by=1)
+        nrow = length(dummydate)
+        dummyval = rep(-99.00, times=nrow)
+        rcpstn = as.data.frame(cbind(dummydate, dummyval))
+        colnames(rcpstn) = c("date", varnms[i])
+        rcpstn$date = as.Date(dummydate)
+
+      } # end of IF
+
+    } else {
+
+      if(file.exists(rcpfile)) {
+        rcp_imsi = read.csv(rcpfile,header=T, na.strings = -99.00)
+        coln = match(stnid, names(rcp_imsi))
+        nrows = length(rcp_imsi[,1])
+        rcp_imsi = rcp_imsi[ ,c(1,coln)]
+        colnames(rcp_imsi) = c("date", varnms[i])
+        rcp_imsi$date = as.Date(rcp_imsi$date)
+        rcpstn = merge(rcpstn, rcp_imsi, by="date", all=T)
+      } else {
+        sdate = as.Date("1976-01-01")
+        edate = as.Date("2100-12-31")
+        dummydate = seq(sdate, edate, by=1)
+        nrow = length(dummydate)
+        dummyval = rep(-99.00, times=nrow)
+        rcp_imsi = as.data.frame(cbind(dummydate, dummyval))
+        colnames(rcp_imsi) = c("date", varnms[i])
+        rcp_imsi$date = as.Date(dummydate)
+        rcpstn = merge(rcpstn, rcp_imsi, by="date", all=T)
+      } # end of IF
+    } # end of IF
+  } # varialbe LOOP
+
+  rcpstn[is.na(rcpstn)] = -99.00
+
+  data = FillDate(rcpstn)
+
+  return(data)
+}
diff --git a/R/ConvertGhcnDaily.R b/R/ConvertGhcnDaily.R
@@ -0,0 +1,75 @@
+ConvertGhcnDaily <- function(dlydir, csvdir, dlyfile, csvfile) {
+
+  DlyDFile <- file.path(dlydir, dlyfile)
+  CsvDFile <- file.path(csvdir, csvfile)
+
+  data <- read.fwf(DlyDFile, header = F, widths = c(11, 6, 4, rep(c(5, 3), 31)))
+  data <- data[, c(1:3, seq(4, 64, by=2))]
+  colnames(data) <- c("ID", "yearmon", "varnm", seq(1, 31))
+  data[data == "-9999"] <- NA
+
+  varnms <- c("PRCP", "TMAX", "TMIN", "AWND", "PSUN", "TAVG")
+  varcnt <- length(varnms)
+
+  sdate <- as.Date(sprintf("%s-%s-01", substr(data[1, "yearmon"], 1, 4), substr(data[1, "yearmon"], 5, 6)))
+  daycnt <- NumberOfDays(as.Date(paste(substr(data[nrow(data), "yearmon"], 1, 4), "-", substr(data[nrow(data), "yearmon"], 5, 6), "-01", sep="")))
+  edate <- as.Date(sprintf("%s-%s-%02d", substr(data[nrow(data), "yearmon"], 1, 4), substr(data[nrow(data), "yearmon"], 5, 6), daycnt))
+  dates <- as.data.frame(seq(sdate, edate, by = "day"))
+  colnames(dates) <- "date"
+  dates$date <- as.character(dates$date)
+
+  flag <- TRUE
+  for(i in 1:varcnt){
+
+    varnm <- varnms[i]
+    val <- as.vector(t(data[which(data$varnm == varnm), 4:34]))
+
+    if(length(val) > 0){
+
+      if(varnm == "PSUN") {
+        val <- as.numeric(val) / 100.0
+      } else {
+        val <- as.numeric(val) / 10.0
+      }
+
+      yearmon <- data[which(data$varnm == varnm), "yearmon"]
+      yearmonstr <- rep(yearmon, each=31)
+      daystr <- sprintf("%02d",rep(seq(1:31), length(yearmon)))
+      datestr <- paste(substr(yearmonstr, 1, 4), "-", substr(yearmonstr, 5, 6), "-", daystr, sep="")
+
+      if(flag){
+        varout <- cbind(datestr, val)
+        colnames(varout) <- c("date", varnm)
+        flag <- FALSE
+      } else {
+        imsi <- cbind(datestr, val)
+        colnames(imsi) <- c("date", varnm)
+        varout <- merge(varout, imsi, all=T)
+      }
+    }
+
+  }
+
+  out <- merge(dates, varout)
+
+  out[is.na(out)] <- "-99.00"
+  out$Year <- substr(out$date, 1, 4)
+  out$Mon <- substr(out$date, 6, 7)
+  out$Day <- substr(out$date, 9, 10)
+
+  if(!("PRCP" %in% colnames(out))) out$PRCP <- "-99.00"
+  if(!("TMAX" %in% colnames(out))) out$TMAX <- "-99.00"
+  if(!("TMIN" %in% colnames(out))) out$TMIN <- "-99.00"
+  if(!("TAVG" %in% colnames(out))) out$TAVG <- "-99.00"
+  if(!("AWND" %in% colnames(out))) out$AWND <- "-99.00"
+  if(!("PSUN" %in% colnames(out))) out$PSUN <- "-99.00"
+  if(!("SRAD" %in% colnames(out))) out$SRAD <- "-99.00"
+  if(!("RHUM" %in% colnames(out))) out$RHUM <- "-99.00"
+  if(!("CLOD" %in% colnames(out))) out$CLOD <- "-99.00"
+
+  out <- out[c("Year", "Mon", "Day", "PRCP", "TMAX", "TMIN", "AWND", "RHUM", "SRAD", "PSUN", "CLOD", "TAVG")]
+  colnames(out) <- c("Year", "Mon", "Day", "Pcp(mm)", "Tmax(c)", "Tmin(c)", "WSpeed(m/s)", "RHumidity(fr)", "SRad(MJ/m2)", "SShine(hr)", "Cloud(1/10)", "Tavg(c)")
+
+  write.csv(out, CsvDFile, row.names = F)
+
+}