using NCDatasets, DataStructures, Dates

# change the variables below with your own data

# the filename

filename = "input_file_julia.nc"

# the variable name in the netCDF file

varname = "SST"

# longitude in degrees East

lon = [1,1.5,2]

# latitude in degrees West

lat = [-1,0,1]

# time

time = [DateTime(1900,1,1),DateTime(1900,1,2),DateTime(1900,1,3)]

# time units

time_units = "days since 1900-01-01 00:00:00";

# the data to reconstruct

data = zeros((length(time),length(lat),length(lon)))

# special value to indice missing data (cloud or land)

fill_value = -9999.

# mask, one means the data location is valid, e.g. a sea points for sea surface temperature.

mask = ones((length(lat),length(lon)))

# create the NetCDF file

ds = NCDataset(filename,"c")

# Dimensions

ds.dim["lon"] = 3

ds.dim["lat"] = 3

ds.dim["time"] = Inf # unlimited dimension

# Declare variables

nclon = defVar(ds,"lon", Float32, ("lon",))

nclat = defVar(ds,"lat", Float32, ("lat",))

nctime = defVar(ds,"time", Float32, ("time",), attrib = OrderedDict(

"units" => "days since 1900-01-01 00:00:00",

))

ncSST = defVar(ds,varname, Float32, ("lon", "lat", "time"), attrib = OrderedDict(

"_FillValue" => Float32(-9999.0),

))

ncmask = defVar(ds,"mask", Int32, ("lon", "lat"), attrib = OrderedDict(

"comment" => "one means the data location is valid (e.g. sea for SST), zero the location is invalid (e.g. land for SST)",

))

# Define variables

nclon[:] = lon

nclat[:] = lat

nctime[:] = time

ncSST[:,:,:] = data

ncmask[:,:] = mask

close(ds)