编辑2023：似乎这个包/答案现在已经过时了，请参阅帕特里克的accepted answer以获得新的方法。

我刚刚发现（两年后发布的问题！）有一个名为ncdf.tools的软件包，它的功能是：
convertDateNcdf2R
这
将netCDF文件中的时间向量或自指定原点起的儒略日（或秒、分、小时）向量转换为POSIX R向量。

用法：

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"))

参数：

time.source

数字向量或netCDF连接：在后一种情况下，从netCDF文件中提取时间向量。该文件，尤其是时间变量，必须遵循CF netCDF约定。

units

字符串：时间源的单位。* 如果源是netCDF文件，则忽略此值并从该文件读取。*

origin

POSIXct对象：时间源的原点或日/小时零点。* 如果源是netCDF文件，则忽略此值并从该文件读取。*
因此，只需将netcdf连接作为第一个参数传递就足够了，函数将处理其余部分。警告：只有当netCDF文件遵循CF conventions（例如，例如，如果你的单位是“years since”而不是“seconds since”或“days since”，它将失败）。
有关该功能的更多详细信息，请访问：https://rdrr.io/cran/ncdf.tools/man/convertDateNcdf2R.html

据我所知，没有。我有这个方便的功能使用lubridate，这是基本相同的你。

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)
}

编辑：人们可能还想看看ncdf4.helpers::nc.get.time.series
编辑2：注意，新提出的和目前正在开发的令人敬畏的stars包将自动处理日期，请参阅the first blog post的示例。
EDIT3：另一种方法是直接使用units包，这是stars使用的。可以这样做：（仍然不能正确处理日历，我不确定units是否可以）

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)
}

我无法让@AF7的函数处理我的文件，所以我自己写了一个。下面的函数创建了一个POSIXct日期向量，从nc文件中读取开始日期，时间间隔，单位和长度。它适用于许多（但可能不是每一个）形状或形式的nc文件。

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)
}

编辑

为了解决@AF7的评论所强调的缺陷，即上述代码仅适用于规则间隔的文件，datev可以计算为

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

你的希望已经被package CFtime满足了。这个包可以无缝地处理CF元数据约定的“时间”维度，包括所有定义的日历。

f1 <- nc_open("file.nc")
cf <- CFtime(f1$dim$time$units, f1$dim$time$calendar, f1$dim$time$vals)
dates <- CFtimestamp(cf)

# This works reliably only for 3 of the 9 defined calendars
dates <- as.Date(dates)

CFtimestamp()函数为所有可能的日期提供正确的输出，包括“360_day”日历上的奇数“2023-02-30”，但不包括“2023-03-31”。转换为POSIXct是很棘手的，但是你真的需要一个Date来工作吗？或者一个字符表示就可以了？