我有一个带有时间序列的 netcdf 文件，时间变量具有以下典型元数据：
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" ;
在 R 内部我想将时间转换为 R 日期对象。我现在以硬连线的方式实现了这一点，通过读取单位属性并分割字符串并使用第三个条目作为我的原点（因此假设间距为“天”，时间为 00:00 等）：
require("ncdf4")
f1<-nc_open("file.nc")
time<-ncvar_get(f1,"time")
tunits<-ncatt_get(f1,"time",attname="units")
tustr<-strsplit(tunits$value, " ")
dates<-as.Date(time,origin=unlist(tustr)[3])
这个硬连线解决方案适用于我的特定示例，但我希望 R 中可能有一个包可以很好地处理时间单位的 UNIDATA netcdf 日期约定并将它们安全地转换为 R 日期对象？
编辑 2023：看来这个包/答案现在已经过时了，请参阅帕特里克的接受的答案，了解执行此操作的新方法。
我刚刚发现（发布问题两年后！）有一个名为 ncdf.tools 的包，它具有以下功能：
转换日期Ncdf2R
哪个
转换来自 netCDF 文件的时间向量或儒略日向量 （或秒、分钟、小时）自指定原点到 POSIXct R 矢量。
用途：
convertDateNcdf2R(time.source, units = "days", origin = as.POSIXct("1800-01-01",
tz = "UTC"), time.format = c("%Y-%m-%d", "%Y-%m-%d %H:%M:%S",
"%Y-%m-%d %H:%M", "%Y-%m-%d %Z %H:%M", "%Y-%m-%d %Z %H:%M:%S"))
论据：
time.source
数字向量或netCDF连接：自起始点以来的多个时间单位或netCDF文件连接，在后一种情况下，时间向量是从netCDF文件中提取的，该文件，尤其是时间变量，必须遵循CF netCDF 约定。
units
字符串：时间源的单位。 如果源是 netCDF 文件，则该值将被忽略并从该文件中读取。
origin
POSIXct 对象：时间源的原点或日/小时零。 如果源是 netCDF 文件，则该值将被忽略并从该文件中读取。
因此，只需将 netcdf 连接作为第一个参数传递就足够了，函数会处理其余的事情。 警告：只有当 netCDF 文件遵循 CF 约定 时，这才有效（例如，如果您的单位是“自此后的年数”而不是“自此后的秒数”或“自此后的天数”，则会失败）。
有关该功能的更多详细信息，请参见此处： https://rdrr.io/cran/ncdf.tools/man/convertDateNcdf2R.html
据我所知没有。我使用
lubridategetNcTime <- function(nc) {
require(lubridate)
ncdims <- names(nc$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$units, " ")[[1]]
timeunit <- timedef[1]
tz <- timedef[5]
timestart <- strsplit(timedef[4], ":")[[1]]
if (length(timestart) != 3 || timestart[1] > 24 || timestart[2] > 60 || timestart[3] > 60 || any(timestart < 0)) {
cat("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n")
warning(paste("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n"))
timedef[4] <- "00:00:00"
}
if (! tz %in% OlsonNames()) {
cat("Warning:", tz, "not a valid timezone. Assuming UTC\n")
warning(paste("Warning:", timestart, "not a valid start time. Assuming 00:00:00\n"))
tz <- "UTC"
}
timestart <- ymd_hms(paste(timedef[3], timedef[4]), tz=tz)
f <- switch(tolower(timeunit), #Find the correct lubridate time function based on the unit
seconds=seconds, second=seconds, sec=seconds,
minutes=minutes, minute=minutes, min=minutes,
hours=hours, hour=hours, h=hours,
days=days, day=days, d=days,
months=months, month=months, m=months,
years=years, year=years, yr=years,
NA
)
suppressWarnings(if (is.na(f)) stop("Could not understand the time unit format"))
timestart + f(times)
}
编辑：人们可能还想看看
ncdf4.helpers::nc.get.time.seriesEDIT2：请注意，新提出的且目前正在开发的 Awesome
starsEDIT3：另一种方法是直接使用
unitsstarsunitsgetNcTime <- function(nc) { ##NEW VERSION, with the units package
require(units)
require(ncdf4)
options(warn=1) #show warnings by default
if (is.character(nc)) nc <- nc_open(nc)
ncdims <- names(nc$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$units
units(times) <- make_unit(timeunit)
as.POSIXct(time)
}
我无法让 @AF7 的函数处理我的文件，所以我编写了自己的函数。下面的函数创建一个 POSIXct 日期向量，从 nc 文件中读取开始日期、时间间隔、单位和长度。它适用于许多（但可能不是所有...）形状或形式的 nc 文件。
ncdate <- function(nc) {
ncdims <- names(nc$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评论中强调的缺陷，即上述代码仅适用于规则间隔的文件，
datev datev <- as.POSIXct(tm*tmulti,origin=startd)
CFtimef1 <- 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()Date