Convert a netcdf time variable to an R date object

EDIT 2023: It seems this package/answer is now obsolete, see accepted answer of Patrick for new way to do this.

I have just discovered (two years after posting the question!) that there is a package called ncdf.tools which has the function:

convertDateNcdf2R

which

converts a time vector from a netCDF file or a vector of Julian days (or seconds, minutes, hours) since a specified origin into a POSIXct R vector.

Usage:

convertDateNcdf2R(time.source, units = "days", origin = as.POSIXct("1800-01-01", tz = "UTC"), time.format = c("%Y-%m-%d", "%Y-%m-%d %H:%M:%S", "%Y-%m-%d %H:%M", "%Y-%m-%d %Z %H:%M", "%Y-%m-%d %Z %H:%M:%S")) 

Arguments:

time.source 

numeric vector or netCDF connection: either a number of time units since origin or a netCDF file connection, In the latter case, the time vector is extracted from the netCDF file, This file, and especially the time variable, has to follow the CF netCDF conventions.

units 

character string: units of the time source. If the source is a netCDF file, this value is ignored and is read from that file.

origin 

POSIXct object: Origin or day/hour zero of the time source. If the source is a netCDF file, this value is ignored and is read from that file.

Thus it is enough to simply pass the netcdf connection as the first argument and the function handles the rest. Caveat: This will only work if the netCDF file follows CF conventions (e.g. if your units are "years since" instead of "seconds since" or "days since" it will fail for example).

More details on the function are available here: https://rdrr.io/cran/ncdf.tools/man/convertDateNcdf2R.html

There is not, that I know of. I have this handy function using lubridate, which is basically identical to yours.

getNcTime <- function(nc) { require(lubridate) ncdims <- names(nc$dim) #get netcdf dimensions timevar <- ncdims[which(ncdims %in% c("time", "Time", "datetime", "Datetime", "date", "Date"))[1]] #find time variable times <- ncvar_get(nc, timevar) if (length(timevar)==0) stop("ERROR! Could not identify the correct time variable") timeatt <- ncatt_get(nc, timevar) #get attributes timedef <- strsplit(timeatt$units, " ")[[1]] timeunit <- timedef[1] tz <- timedef[5] timestart <- strsplit(timedef[4], ":")[[1]] if (length(timestart) != 3 || timestart[1] > 24 || timestart[2] > 60 || timestart[3] > 60 || any(timestart < 0)) { cat("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n") warning(paste("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n")) timedef[4] <- "00:00:00" } if (! tz %in% OlsonNames()) { cat("Warning:", tz, "not a valid timezone. Assuming UTC\n") warning(paste("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n")) tz <- "UTC" } timestart <- ymd_hms(paste(timedef[3], timedef[4]), tz=tz) f <- switch(tolower(timeunit), #Find the correct lubridate time function based on the unit seconds=seconds, second=seconds, sec=seconds, minutes=minutes, minute=minutes, min=minutes, hours=hours, hour=hours, h=hours, days=days, day=days, d=days, months=months, month=months, m=months, years=years, year=years, yr=years, NA ) suppressWarnings(if (is.na(f)) stop("Could not understand the time unit format")) timestart + f(times) } 

EDIT: One might also want to take a look at ncdf4.helpers::nc.get.time.series

EDIT2: note that the newly-proposed and currently in developement awesome stars package will handle dates automatically, see the first blog post for an example.

EDIT3: another way is to use the units package directly, which is what stars uses. One could do something like this: (still not handling the calendar correctly, I'm not sure units can)

getNcTime <- function(nc) { ##NEW VERSION, with the units package require(units) require(ncdf4) options(warn=1) #show warnings by default if (is.character(nc)) nc <- nc_open(nc) ncdims <- names(nc$dim) #get netcdf dimensions timevar <- ncdims[which(ncdims %in% c("time", "Time", "datetime", "Datetime", "date", "Date"))] #find (first) time variable if (length(timevar) > 1) { warning(paste("Found more than one time var. Using the first:", timevar[1])) timevar <- timevar[1] } if (length(timevar)!=1) stop("ERROR! Could not identify the correct time variable") times <- ncvar_get(nc, timevar) #get time data timeatt <- ncatt_get(nc, timevar) #get attributes timeunit <- timeatt$units units(times) <- make_unit(timeunit) as.POSIXct(time) } 

I couldn't get @AF7's function to work with my files so I wrote my own. The function below creates a POSIXct vector of dates, for which the start date, time interval, unit and length are read from the nc file. It works with nc files of many (but probably not every...) shapes or forms.

 ncdate <- function(nc) { ncdims <- names(nc$dim) #Extract dimension names timevar <- ncdims[which(ncdims %in% c("time", "Time", "datetime", "Datetime", "date", "Date"))[1]] # Pick the time dimension ntstep <-nc$dim[[timevar]]$len tm <- ncvar_get(nc, timevar) # Extract the timestep count tunits <- ncatt_get(nc, timevar, "units") # Extract the long name of units tspace <- tm[2] - tm[1] # Calculate time period between two timesteps, for the "by" argument tstr <- strsplit(tunits$value, " ") # Extract string components of the time unit a<-unlist(tstr[1]) # Isolate the unit .i.e. seconds, hours, days etc. uname <- a[which(a %in% c("seconds","hours","days"))[1]] # Check unit startd <- as.POSIXct(gsub(paste(uname,'since '),'',tunits$value),format="%Y-%m-%d %H:%M:%S") ## Extract the start / origin date tmulti <- 3600 # Declare hourly multiplier for date if (uname == "days") tmulti =86400 # Declare daily multiplier for date ## Rename "seconds" to "secs" for "by" argument and change the multiplier. if (uname == "seconds") { uname <- "secs" tmulti <- 1 } byt <- paste(tspace,uname) # Define the "by" argument if (byt == "0.0416666679084301 days") { ## If the unit is "days" but the "by" interval is in hours byt= "1 hour" ## R won't understand "by < 1" so change by and unit to hour. uname = "hours"} datev <- seq(from=as.POSIXct(startd+tm[1]*tmulti),by= byt, units=uname,length=ntstep) } 

Edit

To address the flaw highlighted by @AF7's comment that the above code would only work for regularly spaced files, datev could be calculated as

 datev <- as.POSIXct(tm*tmulti,origin=startd)