convert a netcdf time variable to an R date object

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)

I have just discovered 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.

which is helpful. More details available here: https://rdrr.io/cran/ncdf.tools/man/convertDateNcdf2R.html