Question

我对R比较陌生。我试图从netCDF文件中获取温度数据的不同点（lat，lon）的时间序列。我的示例数据文件是here，here是小文件。我已经尝试过netCDF包和我到目前为止使用的代码

library(ncdf)
obsdata = open.ncdf("obs.nc")

print.ncdf(obsdata) 

obsdatadates = obsdata$dim$time$vals
obsdatadates = as.Date(obsdatadates,origin = '1950-01-01') 
obsdatadates
obsoutput = get.var.ncdf(obsdata, varid = 'tasmin', start = c(1,1,1),
                         count = c(1,1,22280))
dim(obsoutput)
datafinal=merge(obsdatadates,obsoutput)

任何人都可以帮助我获取该数据的特定点（纬度，经度）的时间序列数据帧（第一列）和另一个数据值。在这种情况下，我正在寻找特定纬度点（并重复多个兴趣点）和给定变量（在这种情况下）的时间序列（1950-01-01至2010-12-31，其中数据为） tasmin）。非常感谢您的帮助。谢谢， aseem

Answer 1

也许使用raster包，这不适用于所有NetCDF文件，但它适用于您的：

library(raster)
## brick reads all 22280 layers
r <- brick("obs.nc", varname = "tasmin")
## extract works for all time steps
vals <- extract(r, matrix(c(-120, 52.5), ncol = 2))

dim(vals)
## [1]     1 22280

注意，给出一个1行，多列矩阵，因为我只给了extract()一个点。

（从最近的单元格直接复制，提取很简单，使用method =“bilinear”进行插值）。有关其他选项，请参阅?extract。

Answer 2

以下是我将如何使用ncdf：

继续执行此操作

library(ncdf)
obsdata = open.ncdf("obs1.nc")
obsdatadates = as.Date(obsdata$dim$time$vals,origin = '1950-01-01')
#Get the whole data first
obsoutput = get.var.ncdf(obsdata, varid = 'tasmin')
#Prepare your points of interest
points_of_interest = data.frame(lat=seq(1,8,by=2),lon=c(1,5,3,6))
#Subset your data accordingly
data_at_point = apply(points_of_interest,1,function(x)obsoutput[x[1],x[2],])
#Turn it into a dataframe
data_at_point = as.data.frame(data_at_point)
#Add the dates to the dataframe
data_at_point$Date = obsdatadates

Answer 3

不推荐使用＆＃39; ncdf＆＃39; -package：http://cirrus.ucsd.edu/~pierce/ncdf/

使用ncdf4包进行更新：

library(ncdf4)
obsdata <- nc_open("obs1.nc")
print(obsdata) # check that dims are lon-lat-time

# location of interest
lon <- 6  # longitude of location
lat <- 51 # latitude  of location

# get dates
obsdatadates <- as.Date(obsdata$dim$time$vals, origin = '1950-01-01')

# get values at location lonlat
obsoutput <- ncvar_get(obsdata, varid = 'tasmin',
                  start= c(which.min(abs(obsdata$dim$longitude$vals - lon)), # look for closest long
                           which.min(abs(obsdata$dim$latitude$vals - lat)),  # look for closest lat
                           1),
                  count = c(1,1,-1)) #count '-1' means 'all values along that dimension'that dimension'
# create dataframe
datafinal <- data.frame(dates= obsdatadates, obs = obsoutput)

从R中的netCDF中提取点（lon，lat）的时间序列

3 个答案: