vignettes/marine-region.R

In RS-eco/rISIMIP: R Package for processing ISIMIP data in R

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE, fig.width=14, fig.height=8, warning=FALSE, comment=NA, message=FALSE, eval=F)

## -----------------------------------------------------------------------------
#  library(rISIMIP)

## ----global_options-----------------------------------------------------------
#  # Specify path of file directory
#  filedir <- "/media/matt/Data/Documents/Wissenschaft/Data"

## ----install_processNC, eval=FALSE--------------------------------------------
#  # Install processNC package
#  remotes::install_github("RS-eco/processNC")

## -----------------------------------------------------------------------------
#  library(processNC)

## -----------------------------------------------------------------------------
#  # Crop data by given extent
#  hurs_ns <- lapply(hurs, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  huss_ns <- lapply(huss, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  tas_ns <- lapply(tas, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  tmin_ns <- lapply(tmin, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  tmax_ns <- lapply(tmax, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  prec_ns <- lapply(prec, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  bioclim_ns <- lapply(bioclim, FUN=function(x) crop(x, y=c(-30,75,30,90)))
#  
#  # Change name from .grd to _NorthSea.grd
#  hurs_ns_names <- gsub(x = hurs_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  huss_ns_names <- gsub(x = huss_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  tas_ns_names <- gsub(x = tas_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  tmin_ns_names <- gsub(x = tmin_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  tmax_ns_names <- gsub(x = tmax_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  prec_ns_names <- gsub(x = prec_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  bioclim_ns_names <- gsub(x = bioclim_names, pattern = "\\.grd", replacement = "_NorthSea.grd")
#  
#  # Save to file into NorthSea subfolder
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=hurs_ns, y=hurs_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=huss_ns, y=huss_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=tas_ns, y=tas_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=tmin_ns, y=tmin_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=tmax_ns, y=tmax_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=prec_ns, y=prec_ns_names)
#  mapply(FUN=function(x,y) writeRaster(x, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", y)), x=bioclim_ns, y=bioclim_ns_names)

## -----------------------------------------------------------------------------
#  # Read and crop wind data and save to file in NorthSea subfolder
#  sfcWind_ns <- lapply(list.files(paste0(filedir, "/ISIMIP2b/ProcessedData/global"),
#                                  pattern="monthly_sfcWind_.*\\.grd", full.names=TRUE),
#                       FUN=function(x){
#                         data <- stack(x)
#                         data <- crop(data, y=c(-30,75,30,90))
#                         names <- basename(x)
#                         name <- gsub(x = names, pattern = "\\.grd",
#                                      replacement = "_NorthSea.grd")
#                         writeRaster(data, filename=paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/", name))
#                       })

## ---- eval=FALSE--------------------------------------------------------------
#  # Install ggmap2 package from Github
#  devtools::install_github("RS-eco/ggmap2")

## -----------------------------------------------------------------------------
#  library(ggmap2)

## -----------------------------------------------------------------------------
#  # Read huss NorthSea data files
#  hurs <- lapply(list.files(paste0(filedir, "/ISIMIP2b/ProcessedData/NorthSea/historical"),
#                                  pattern="monthly_hurs_.*\\.grd", full.names=TRUE), stack)
#  hurs[[1]]
#  
#  # Create Map
#  createMap(hurs[[1]], name="hurs", subnames=month.abb, split=FALSE, ncol=4, width=12, height=8, units="in", dpi=100)

## -----------------------------------------------------------------------------
#  # Climate variables
#  vars <- c("to", "o2", "intpp", "phy", "zooc", "so", "pic", "prsn")
#  
#  # Climate models
#  models <- c("gfdl-esm2m", "ipsl-cm5a-lr")
#  
#  # Timeframes (Current, Horizon 2050, 2080, 2100, 2150)
#  timeframes <- c("ref", "2050","2080","2100","2150")
#  startyears <- c(1970,2036,2066,2086,2136)
#  endyears <- c(1999,2065,2095,2115,2165)
#  counter <- 1
#  
#  # Run summariseNC for all combinations
#  for(a in 1:length(vars)){
#    for(b in 1:length(models)){
#      for(c in 1:length(timeframes)){
#        files <- listISIMIP(path=filedir, version="ISIMIP2a", type="ocean", var=vars[a],
#                            model=models[b], startyear=startyears[c],
#                            endyear=endyears[c])
#        filename1 <- paste0(filedir, "ISIMIP2a/ProcessedData/monthly_", vars[a],"_",
#                           timeframes[c], "_", models[b], ".tif")
#        filename2 <- paste0(filedir, "ISIMIP2a/ProcessedData/monthly_cv_", vars[a],"_",
#                           timeframes[c], "_", models[b], ".tif")
#        if(unique(!is.na(files))){
#          if(!file.exists(filename1)){
#            data_sub <- summariseNC(files=files, startyear=startyears[c], tres="month",
#                                    endyear=endyears[c], filename1=filename1,
#                                    filename2=filename2, format="GTiff",
#                                    overwrite=FALSE)
#          }
#        }
#        d <- round((counter*100/(length(vars)*length(models)*length(timeframes))),
#                   digits = 2)
#        print(paste(d,"% done"))
#        counter <- counter + 1
#      }
#    }
#  }