将 netcdf 时间变量转换为 R 日期对象

Question

I have a netcdf file with a timeseries and the time variable has the following typical metadata:

    double time(time) ;
            time:standard_name = "time" ;
            time:bounds = "time_bnds" ;
            time:units = "days since 1979-1-1 00:00:00" ;
            time:calendar = "standard" ;
            time:axis = "T" ;

Inside RI want to convert the time into an R date object. I achieve this at the moment in a hardwired way by reading the units attribute and splitting the string and using the third entry as my origin (thus assuming the spacing is "days" and the time is 00:00 etc):

require("ncdf4")
f1<-nc_open("file.nc")
time<-ncvar_get(f1,"time")
tunits<-ncatt_get(f1,"time",attname="units")
tustr<-strsplit(tunits$value, " ")
dates<-as.Date(time,origin=unlist(tustr)[3])

This hardwired solution works for my specific example, but I was hoping that there might be a package in R that nicely handles the UNIDATA netcdf date conventions for time units and convert them safely to an R date object?

Answer 1

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 (eg 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

Answer 2

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)
}

Answer 3

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)