I have a series of nertCDF files containing global data for a particular variable, e.g. tmin/tmax/precipiation/windspeed/relative humuidity/radiation etc. I get the following information when using nc_open function in R:
datafile: https://www.dropbox.com/s/xpo7zklcmtm3g5r/gfdl_preci.nc?dl=0
File gfdl_preci.nc (NC_FORMAT_NETCDF4_CLASSIC):
1 variables (excluding dimension variables):
float prAdjust[lon,lat,time]
_FillValue: 1.00000002004088e+20
missing_value: 1.00000002004088e+20
comment: includes all types (rain, snow, large-scale, convective, etc.)
long_name: Bias-Corrected Precipitation
units: kg m-2 s-1
standard_name: precipitation_flux
3 dimensions:
lon Size:720
standard_name: longitude
long_name: longitude
units: degrees_east
axis: X
lat Size:360
standard_name: latitude
long_name: latitude
units: degrees_north
axis: Y
time Size:365 *** is unlimited ***
standard_name: time
units: days since 1860-1-1 00:00:00
calendar: standard
axis: T
14 global attributes:
CDI: Climate Data Interface version 1.7.0 (http://mpimet.mpg.de/cdi)
Conventions: CF-1.4
title: Model output climate of GFDL-ESM2M r1i1p1 Interpolated to 0.5 degree and bias corrected using observations from 1960 - 1999 for EU WATCH project
CDO: Climate Data Operators version 1.7.0 (http://mpimet.mpg.de/cdo)
product_id: input
model_id: gfdl-esm2m
institute_id: PIK
experiment_id: historical
ensemble_id: r1i1p1
time_frequency: daily
creator: [email protected]
description: GFDL-ESM2M bias corrected impact model input prepared for ISIMIP2.
I have been able to read the netCDF file (variables and dimensions) and fragment the time into fields. But, I still need to extract a slice of information based on location (using 4 co-ordinates of a square) e.g., europe. Later, I have to convert the slice into .csv format.
so far I could make up to this step:
# load the ncdf4 package
library(ncdf4)
# set path and filename
setwd("D:/netcdf")
ncname <- "gfdl_preci"
ncfname <- paste(ncname, ".nc", sep = "")
dname <- "prAdjust"
# open a netCDF file
ncin <- nc_open(ncfname)
print(ncin)
# get longitude and latitude
lon <- ncvar_get(ncin,"lon")
nlon <- dim(lon)
head(lon)
lat <- ncvar_get(ncin,"lat")
nlat <- dim(lat)
head(lat)
print(c(nlon,nlat))
# get time
time <- ncvar_get(ncin,"time")
time
tunits <- ncatt_get(ncin,"time","units")
nt <- dim(time)
nt
tunits
# get variable
preci.array <- ncvar_get(ncin,dname)
dlname <- ncatt_get(ncin,"prAdjust","long_name")
dunits <- ncatt_get(ncin,"prAdjust","units")
fillvalue <- ncatt_get(ncin,"prAdjust","_FillValue")
dim(preci.array)
# split the time units string into fields
tustr <- strsplit(tunits$value, " ")
tdstr <- strsplit(unlist(tustr)[3], "-")
tmonth = as.integer(unlist(tdstr)[2])
tday = as.integer(unlist(tdstr)[3])
tyear = as.integer(unlist(tdstr)[1])
chron(time, origin = c(tmonth, tday, tyear))
Any help would be appreciated!!
1.) We don't know your file, but you can get some insides of a netCDF object in R like this:
Or you address the slots directly. You can also try other numbers like 11 or 7, to address other slots on the list object.
2.) Here is the documentation of the package you use, i think the answer of your problem is somewhere in there:
https://cran.r-project.org/web/packages/ncdf4/ncdf4.pdf
3.) You save information from R in a file like this: