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@aolinto aolinto/MODISA_sst.R
Last active May 17, 2016

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R script to extract Aqua MODIS Sea Surface Temperature data from a nc file
# Antonio Olinto Avila-da-Silva, Instituto de Pesca, Brasil
# ver 2016-05-17
# https://gist.github.com/aolinto/79e184f6c156c6ab21b3
# script to process Aqua MODIS Sea Surface Temperature
# files downloaded from http://oceancolor.gsfc.nasa.gov/cgi/l3
# Aqua MODIS Sea Surface temperature 11 u daytime Monthly 9 km SMI images
# all .L3m_MO_SST_sst_9km.nc files must be in the working directory
# the script will open each nc file, read date, lon, lat and sst data,
# then select data from specified area and write them into
# a single csv file named MODISA_sst.csv
# Some reference pages
# http://geog.uoregon.edu/GeogR/topics/netCDF-read-ncdf4.html
# https://scottishsnow.wordpress.com/2014/08/24/many-rastered-beast/
# load libraries
# ncdf4 needs libnetcdf-dev netcdf-bin in Linux
# install.packages(c("ncdf4","reshape2"))
library("ncdf4")
library("reshape2")
# set working directory
setwd("/mnt/Dados02/MODIS/SST") # indicate the path to the files
file.exists("MODISA_sst.csv") # caution new data will be appended to this file if it already exists
# file.rename("MODISA_sst.csv","MODISA_sst.old")
# file.remove("MODISA_sst.csv")
# list and remove objects
ls()
rm(list = ls())
# set the study area in decimal degrees
lonmax<--40
lonmin<--50
latmax<--22
latmin<--29
# create a list of files and indicate its length
(f <- list.files(".", pattern="*.L3m_MO_SST_sst_9km.nc",full.names=F))
(lf<-length(f))
# variable
var<-"sst"
for (i in 1:lf) {
# progress indicator
print(paste("Processing file",i,"from",length(f),f[i],sep=" "))
# open netCDF file
data<-nc_open(f[i])
# extract data
lon<-ncvar_get(data,"lon")
lat<-ncvar_get(data,"lat")
value<-ncvar_get(data,var)
unit<-ncatt_get(data,var,"units")$value
# matrix to data.frame
dimnames(value)<-list(lon=lon,lat=lat)
dat.var<-melt(value,id="lon")
# select data from the study area taking out missing data
dat.varSAtmp<-subset(dat.var,lon<=lonmax & lon>=lonmin & lat<=latmax & lat>=latmin & value<45)
# extract date information
dateini<-ncatt_get(data,0,"time_coverage_start")$value
dateend<-ncatt_get(data,0,"time_coverage_end")$value
datemean<-mean(c(as.Date(dateend,"%Y-%m-%dT%H:%M:%OSZ"),as.Date(dateini,"%Y-%m-%dT%H:%M:%OSZ")))
year<-substring(datemean,0,4)
month<-substring(datemean,6,7)
# prepare final data set
dat.varSA<-data.frame(rep(as.integer(year,nrow(dat.varSAtmp))),rep(as.integer(month,nrow(dat.varSAtmp))),
dat.varSAtmp,rep(unit,nrow(dat.varSAtmp)),rep(var,nrow(dat.varSAtmp)))
names(dat.varSA)<-c("year","month","lon","lat","value","unit","var")
# save csv file
fe<-file.exists("MODISA_sst.csv")
write.table(dat.varSA,"MODISA_sst.csv",row.names=FALSE,col.names=!fe,sep=";",dec=",",append=fe)
# close connection
nc_close(data)
# clean workspace
rm(data,lon,lat,value,unit,dat.var,dat.varSAtmp,dateini,dateend,datemean,year,month,dat.varSA,fe)
}
rm(var,f,i,latmax,latmin,lf,lonmax,lonmin)
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