從 netcdf 中提取特定 lat long 的值

Question

我正在嘗試讀入 R 一個 netCDF 文件。 netcdf chirps-v2.0.1981.days_p05.nc從這里下載：

ftp://ftp.chg.ucsb.edu/pub/org/chg/products/CHIRPS-2.0/global_daily/netcdf/p05/

此 netCDF 文件將全球每日降雨量描述為經度、緯度的 function，大小為 1.1 GB

我也有一套 lon lat

dat <- structure(list(locatioID = paste0('ID', 1:16), lon = c(73.73, 86, 73.45, 86.41, 85.36, 81.95, 82.57, 75.66, 82.03, 
                          81.73, 85.66, 85.31, 81.03, 81.70, 87.03, 73.38), 
                        lat = c(24.59, 20.08, 22.61, 23.33, 23.99, 19.09, 18.85, 15.25, 26.78, 
                          16.63, 25.98, 23.28, 24.5, 21.23, 25.08, 21.11)), 
                  row.names = c(1L, 3L, 5L, 8L, 11L, 14L, 17L, 18L, 19L, 21L, 
                              23L, 26L, 29L, 32L, 33L, 35L), class = "data.frame")

library(ncdf4)  
library(raster)
temp <- nc_open("chirps-v2.0.1981.days_p05.nc")

precip = list()
precip$x = ncvar_get(temp, "longitude")
precip$y = ncvar_get(temp, "latitude")
precip$z = ncvar_get(temp, "precip", start=c(1, 1, 1), count=c(-1, -1, 1))
precip.r = raster(precip)
plot(precip.r)

我有兩個問題：

• 誰能向我解釋 start 和 count 參數的作用是什么？ ?ncvar_get並沒有給我直觀的感覺。 如果我想創建儒略日 252 的柵格，我需要更改哪個參數？

• 如何提取dat中每個緯度的所有 365 天的每日降雨量值，以便我有一個 16 * 365 天的矩陣/數據框

Answer 1

您可以使用以下代碼從 .nc 文件中提取數據

dat <- structure(list(locatioID = paste0('ID', 1:16), lon = c(73.73, 86, 73.45, 86.41, 85.36, 81.95, 82.57, 75.66, 82.03, 
                                                              81.73, 85.66, 85.31, 81.03, 81.70, 87.03, 73.38), 
                      lat = c(24.59, 20.08, 22.61, 23.33, 23.99, 19.09, 18.85, 15.25, 26.78, 
                              16.63, 25.98, 23.28, 24.5, 21.23, 25.08, 21.11)), 
                 row.names = c(1L, 3L, 5L, 8L, 11L, 14L, 17L, 18L, 19L, 21L, 
                               23L, 26L, 29L, 32L, 33L, 35L), class = "data.frame")


temp <- brick("chirps-v2.0.1981.days_p05.nc")

xy <- dat[,2:3] #Column 1 is longitude and column 2 is latitude
xy
spts <- SpatialPoints(xy, proj4string=CRS("+proj=longlat +datum=WGS84"))
#Extract data by spatial point
temp2 <- extract(temp, spts)
temp3 <- t(temp2) #transpose raster object
colnames(temp3) <- dat[,1] #It would be better if you have the location names corresponding to the points
head(temp3)
write.csv(temp3, "Rainfall.csv")