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###  Script to compile the monthly cloud data from earth engine into a netcdf file for further processing
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library(raster)
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library(doMC)
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library(multicore)
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library(foreach)
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#library(doMPI)
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registerDoMC(4)
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#beginCluster(4)
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wd="~/acrobates/adamw/projects/cloud"
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setwd(wd)
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tempdir="tmp"
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if(!file.exists(tempdir)) dir.create(tempdir)
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##  Get list of available files
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df=data.frame(path=list.files("/mnt/data2/projects/cloud/mod09",pattern="*.tif$",full=T,recur=T),stringsAsFactors=F)
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df[,c("region","year","month")]=do.call(rbind,strsplit(basename(df$path),"_|[.]"))[,c(1,2,3)]
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df$date=as.Date(paste(df$year,"_",df$month,"_15",sep=""),"%Y_%m_%d")
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## add stats to test for missing data
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addstats=F
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if(addstats){
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    df[,c("max","min","mean","sd")]=do.call(rbind.data.frame,mclapply(1:nrow(df),function(i) as.numeric(sub("^.*[=]","",grep("STATISTICS",system(paste("gdalinfo -stats",df$path[i]),inter=T),value=T)))))
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    table(df$sd==0)
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}
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## subset to testtiles?
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#df=df[df$region%in%testtiles,]
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#df=df[df$month==1,]
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table(df$year,df$month)
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writeLines(paste("Tiling options will produce",nrow(tiles),"tiles and ",nrow(jobs),"tile-months.  Current todo list is ",length(todo)))
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## drop some if not complete
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#df=df[df$month%in%1:9&df$year%in%c(2001:2012),]
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rerun=T  # set to true to recalculate all dates even if file already exists
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## Loop over existing months to build composite netcdf files
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foreach(date=unique(df$date)) %dopar% {
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    ## get date
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  print(date)
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  ## Define output and check if it already exists
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  vrtfile=paste(tempdir,"/mod09_",date,".vrt",sep="")
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  ncfile=paste(tempdir,"/mod09_",date,".nc",sep="")
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  tffile=paste(tempdir,"/mod09_",date,".tif",sep="")
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  if(!rerun&file.exists(ncfile)) return(NA)
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  ## merge regions to a new netcdf file
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#  system(paste("gdal_merge.py -o ",tffile," -init -32768  -n -32768.000 -ot Int16 ",paste(df$path[df$date==date],collapse=" ")))
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  system(paste("gdalbuildvrt -overwrite -srcnodata -32768 -vrtnodata -32768 ",vrtfile," ",paste(df$path[df$date==date],collapse=" ")))
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  ## Warp to WGS84 grid and convert to netcdf
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  ##ops="-t_srs 'EPSG:4326' -multi -r cubic -te -180 0 180 10 -tr 0.008333333333333 -0.008333333333333 -wo SOURCE_EXTRA=50" #-wo SAMPLE_GRID=YES -wo SAMPLE_STEPS=100
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  ops="-t_srs 'EPSG:4326' -multi -r cubic -te -180 -90 180 90 -tr 0.008333333333333 -0.008333333333333  -wo SOURCE_EXTRA=50"
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  system(paste("gdalwarp -overwrite ",ops," -et 0 -srcnodata -32768 -dstnodata -32768 ",vrtfile," ",tffile," -ot Int16"))
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  system(paste("gdal_translate -of netCDF ",tffile," ",ncfile))
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                                        #  system(paste("gdalwarp -overwrite ",ops," -srcnodata -32768 -dstnodata -32768 -of netCDF ",vrtfile," ",tffile," -ot Int16"))
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  file.remove(tffile)
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  setwd(wd)
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  system(paste("ncecat -O -u time ",ncfile," ",ncfile,sep=""))
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## create temporary nc file with time information to append to MOD06 data
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  cat(paste("
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    netcdf time {
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      dimensions:
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        time = 1 ;
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      variables:
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        int time(time) ;
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      time:units = \"days since 2000-01-01 00:00:00\" ;
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      time:calendar = \"gregorian\";
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      time:long_name = \"time of observation\"; 
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    data:
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      time=",as.integer(date-as.Date("2000-01-01")),";
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    }"),file=paste(tempdir,"/",date,"_time.cdl",sep=""))
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system(paste("ncgen -o ",tempdir,"/",date,"_time.nc ",tempdir,"/",date,"_time.cdl",sep=""))
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system(paste("ncks -A ",tempdir,"/",date,"_time.nc ",ncfile,sep=""))
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## add other attributes
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  system(paste("ncrename -v Band1,CF ",ncfile,sep=""))
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  system(paste("ncatted ",
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               " -a units,CF,o,c,\"%\" ",
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#               " -a valid_range,CF,o,b,\"0,100\" ",
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               " -a scale_factor,CF,o,f,\"0.1\" ",
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               " -a _FillValue,CF,o,f,\"-32768\" ",
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               " -a long_name,CF,o,c,\"Cloud Frequency(%)\" ",
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               " -a NETCDF_VARNAME,CF,o,c,\"Cloud Frequency(%)\" ",
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               " -a title,global,o,c,\"Cloud Climatology from MOD09 Cloud Mask\" ",
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               " -a institution,global,o,c,\"Jetz Lab, EEB, Yale University, New Haven, CT\" ",
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               " -a source,global,o,c,\"Derived from MOD09GA Daily Data\" ",
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               " -a comment,global,o,c,\"Developed by Adam M. Wilson (adam.wilson@yale.edu / http://adamwilson.us)\" ",
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               ncfile,sep=""))
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               ## add the fillvalue attribute back (without changing the actual values)
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#system(paste("ncatted -a _FillValue,CF,o,b,-32768 ",ncfile,sep=""))
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if(as.numeric(system(paste("cdo -s ntime ",ncfile),intern=T))<1) {
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  print(paste(ncfile," has no time, deleting"))
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  file.remove(ncfile)
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}
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  print(paste(basename(ncfile)," Finished"))
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}
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### merge all the tiles to a single global composite
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#system(paste("ncdump -h ",list.files(tempdir,pattern="mod09.*.nc$",full=T)[10]))
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system(paste("cdo -O  mergetime ",paste(list.files(tempdir,pattern="mod09.*.nc$",full=T),collapse=" ")," data/cloud_daily.nc"))
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#  Overall mean
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system(paste("cdo -O  -chname,CF,CF_annual -timmean data/cloud_daily.nc  data/cloud_mean.nc"))
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### generate the monthly mean and sd
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#system(paste("cdo -P 10 -O merge -ymonmean data/mod09.nc -chname,CF,CF_sd -ymonstd data/mod09.nc data/mod09_clim.nc"))
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system(paste("cdo  -O -ymonmean data/cloud_daily.nc data/cloud_ymonmean.nc"))
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system(paste("cdo  -O -chname,CF,CF_sd -ymonstd data/cloud_daily.nc data/cloud_ymonsd.nc"))
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#if(!file.exists("data/mod09_metrics.nc")) {
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#    system("cdo -chname,CF,CFmin -timmin data/mod09_clim_mean.nc data/mod09_min.nc")
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#    system("cdo -chname,CF,CFmax -timmax data/mod09_clim_mean.nc data/mod09_max.nc")
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#    system("cdo -chname,CF,CFsd -timstd data/mod09_clim_mean.nc data/mod09_std.nc")
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#    system("cdo -f nc2 merge data/mod09_std.nc data/mod09_min.nc data/mod09_max.nc data/mod09_metrics.nc")
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    system("cdo merge -chname,CF,CFmin -timmin data/cloud_clim_mean.nc -chname,CF,CFmax -timmax data/cloud_clim_mean.nc  -chname,CF,CFsd -timstd data/cloud_clim_mean.nc  data/cloud_metrics.nc")
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#}
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### Long term summaries
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seasconc <- function(x,return.Pc=T,return.thetat=F) {
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          #################################################################################################
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          ## Precipitation Concentration function
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          ## This function calculates Precipitation Concentration based on Markham's (1970) technique as described in Schulze (1997)
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          ## South Africa Atlas of Agrohydology and Climatology - R E Schulze, M Maharaj, S D Lynch, B J Howe, and B Melvile-Thomson
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          ## Pages 37-38
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          #################################################################################################
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          ## x is a vector of precipitation quantities - the mean for each factor in "months" will be taken,
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          ## so it does not matter if the data are daily or monthly, as long as the "months" factor correctly
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          ## identifies them into 12 monthly bins, collapse indicates whether the data are already summarized as monthly means.
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          #################################################################################################
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          theta=seq(30,360,30)*(pi/180)                                       # set up angles for each month & convert to radians
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                  if(sum(is.na(x))==12) { return(cbind(Pc=NA,thetat=NA)) ; stop}
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                  if(return.Pc) {
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                              rt=sqrt(sum(x * cos(theta))^2 + sum(x * sin(theta))^2)    # the magnitude of the summation
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                                        Pc=as.integer(round((rt/sum(x))*100))}
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                  if(return.thetat){
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                              s1=sum(x*sin(theta),na.rm=T); s2=sum(x*cos(theta),na.rm=T)
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                                        if(s1>=0 & s2>=0)  {thetat=abs((180/pi)*(atan(sum(x*sin(theta),na.rm=T)/sum(x*cos(theta),na.rm=T))))}
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                                        if(s1>0 & s2<0)  {thetat=180-abs((180/pi)*(atan(sum(x*sin(theta),na.rm=T)/sum(x*cos(theta),na.rm=T))))}
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                                        if(s1<0 & s2<0)  {thetat=180+abs((180/pi)*(atan(sum(x*sin(theta),na.rm=T)/sum(x*cos(theta),na.rm=T))))}
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                                        if(s1<0 & s2>0)  {thetat=360-abs((180/pi)*(atan(sum(x*sin(theta),na.rm=T)/sum(x*cos(theta),na.rm=T))))}
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                             thetat=as.integer(round(thetat))
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                            }
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                  if(return.thetat&return.Pc) return(c(conc=Pc,theta=thetat))
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                  if(return.Pc)          return(Pc)
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                  if(return.thetat)  return(thetat)
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        }
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## read in monthly dataset
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mod09=brick("data/mod09_clim_mean.nc",varname="CF")
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plot(mod09[1])
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mod09_seas=calc(mod09,seasconc,return.Pc=T,return.thetat=F,overwrite=T,filename="data/mod09_seas.nc",NAflag=255,datatype="INT1U")
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mod09_seas2=calc(mod09,seasconc,return.Pc=F,return.thetat=T,overwrite=T,filename="data/mod09_seas_theta.nc",datatype="INT1U")
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plot(mod09_seas)