Extracting subset from netCDF file using lat/lon and converting into .csv in R

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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!!

2

There are 2 answers

1
and-bri On

1.) We don't know your file, but you can get some insides of a netCDF object in R like this:

data <- ncvar_get(ncin)
data

Or you address the slots directly. You can also try other numbers like 11 or 7, to address other slots on the list object.

ncin[[7]]
ncin[[11]]

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:

write.csv(cbind(lat, lon), "result.csv", row.names=F)
0
ExHunter On

you can extract point in nc with library raster

library(raster)
library(sp)

r <- brick("csiromk3.6-rcp45-2010-2099-pr.nc", varname = "pr")
vals <- extract(r, matrix(c(95.46400, 5.40400), ncol = 2))
vals

you can write it into csv by convert vals to dataframe

vals <- as.data.frame(t(vals),row.names = FALSE)

write.csv(vals, "D:\\ch_2010_2099_rcp45.csv")