我正在处理来自NARCCAP的温度.nc文件。这些数据具有极地立体投影。从温度最小值和最大值开始,我创建了一个天数矩阵,符合枫糖浆生产日。
我想将此矩阵转换为栅格,并将此栅格投影到lon / lat投影。
## This is the metadata for the projection from the .nc file:
# float lat[xc,yc]
# long_name: latitude
# standard_name: latitude
# units: degrees_north
# axis: Y
# float lon[xc,yc]
# long_name: longitude
# standard_name: longitude
# units: degrees_east
# axis: X
# float tasmax[xc,yc,time]
# coordinates: lon lat level
# _FillValue: 1.00000002004088e+20
# original_units: K
# long_name: Maximum Daily Surface Air Temperature
# missing_value: 1.00000002004088e+20
# original_name: T_MAX_GDS5_HTGL
# units: K
# standard_name: air_temperature
# cell_methods: time: maximum (interval: 24 hours)
# grid_mapping: polar_stereographic
# grid_mapping_name: polar_stereographic
# latitude_of_projection_origin: 90
# standard_parallel: 60
# false_easting: 4700000
# false_northing: 8400000
# longitude_of_central_meridian: 263
# straight_vertical_longitude_from_pole: 263
# The production days matrix I've created is called from a saved file:
path.ecp2 <- paste0("E:/all_files/production/narccap/GFDL/Production_Days_SkinnerECP2",
year, ".RData")
file.ecp2 <- get(load(path.ecp2))
dim(file.ecp2)
# 147 116
rast.ecp2 <- raster(file.ecp2)
rast.ecp2 <- flip(t(rast.ecp2), 2)
# class : RasterLayer
# dimensions : 116, 147, 17052 (nrow, ncol, ncell)
# resolution : 0.006802721, 0.00862069 (x, y)
# extent : 0, 1, 0, 1 (xmin, xmax, ymin, ymax)
# coord. ref. : NA
# data source : in memory
# names : layer
# values : 0, 671 (min, max)
# I assign the polar stereographic crs to this production days raster:
crs("+init=epsg:3031")
ecp2.proj <- "+proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +k=1 +x_0=4700000 +y_0=8400000 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0"
crs(rast.ecp2) <- crs(ecp2.proj)
rast.ecp2
# class : RasterLayer
# dimensions : 116, 147, 17052 (nrow, ncol, ncell)
# resolution : 0.006802721, 0.00862069 (x, y)
# extent : 0, 1, 0, 1 (xmin, xmax, ymin, ymax)
# coord. ref. : +proj=stere +lat_0=-90 +lat_ts=-71 +lon_0=0 +k=1 +x_0=4700000 +y_0=8400000 +datum=WGS84 +units=m +no_defs +ellps=WGS84 +towgs84=0,0,0
# data source : in memory
# names : layer
# values : 0, 671 (min, max)
当我使用之前对我有用的步骤时(请参阅here),rast.ecp2的值全部转到NA。我哪里错了?
# The projection I want to project TO:
source_rast <- raster(nrow=222, ncol=462, xmn=-124.75, xmx=-67, ymn=25.125, ymx=52.875,
crs="+proj=longlat +datum=WGS84")
rast.ecp2LL <- projectRaster(rast.ecp2, source_rast)
rast.ecp2LL
# class : RasterLayer
# dimensions : 222, 462, 102564 (nrow, ncol, ncell)
# resolution : 0.125, 0.125 (x, y)
# extent : -124.75, -67, 25.125, 52.875 (xmin, xmax, ymin, ymax)
# coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0
# data source : in memory
# names : layer
# values : NA, NA (min, max)
答案 0 :(得分:1)
我发布了我发现的解决方案。它基于this post and answer。我必须先将.nc文件的xc和yc坐标转换为经度和纬度点。 然后我可以正确地重新投影光栅。以下是有效的代码。
请注意mycrs
是&#34;附带的CRS&#34; .nc文件。必须将其分配给SpatialPoints
,因为从xc / yc转换为SpatialPoints
会丢弃相关的CRS。
years <- seq(from=1971, to=2000, by=5)
model <- "CRCM"
convert.lonlat <- function(model, year)
{
max.stem <- "E:/all_files/www.earthsystemgrid.org/CCSM/tasmax_"
inputfile <- paste0(max.stem, model, "_ccsm_", year, "010106.nc")
lat <- raster(inputfile, varname="lat")
lon <- raster(inputfile, varname = "lon")
plat <- rasterToPoints(lat)
plon <- rasterToPoints(lon)
lonlat <- cbind(plon[,3], plat[,3])
lonlat <- SpatialPoints(lonlat, proj4string = crs(base.proj))
mycrs <- crs("+proj=stere +lon_0=263 +x_0=3475000 +y_0=7475000 +lat_0=90 +ellps=WGS84")
plonlat <- spTransform(lonlat, CRSobj = mycrs)
maxs <- brick(inputfile, varname="tasmax")
projection(maxs) <- mycrs
extent(maxs) <- extent(plonlat)
max.lonlat <- projectRaster(maxs, base.proj)
save(max.lonlat, file=paste0("E:/all_files/production/narccap/CCSM/", model, "max_lonlat_", year, ".RData"))
min.stem <- "E:/all_files/www.earthsystemgrid.org/CCSM/tasmin_"
inputfile <- paste0(min.stem, model, "_ccsm_", year, "010106.nc")
lat <- raster(inputfile, varname="lat")
lon <- raster(inputfile, varname = "lon")
plat <- rasterToPoints(lat)
plon <- rasterToPoints(lon)
lonlat <- cbind(plon[,3], plat[,3])
lonlat <- SpatialPoints(lonlat, proj4string = crs(maurer.proj))
mycrs <- crs("+proj=stere +lon_0=263 +x_0=3475000 +y_0=7475000 +lat_0=90 +ellps=WGS84")
plonlat <- spTransform(lonlat, CRSobj = mycrs)
mins <- brick(inputfile, varname="tasmin")
projection(mins) <- mycrs
extent(mins) <- extent(plonlat)
min.lonlat <- projectRaster(mins, maurer.proj)
save(min.lonlat, file=paste0("E:/all_files/production/narccap/CCSM/", model, "min_lonlat_", year, ".RData"))
}
lapply(years, convert.lonlat, model=model)
从这里开始,我根据保存的文件max.lonlat
和min.lonlat
制作生产日矩阵。
谢谢!希望这有用。