Converting WRF files to raster stacks! Projection - r

Question

I have WRF output netCDF files with 149974991 dimensions produced with "Mercator" projection over the Horn Of Africa. I would like to convert netCDF files into raster stack to undertake further analysis. I have been trying different options but it didn't work for me. I am getting values on wrong locations. I require help in this regards and any help is much appreciated.
Here is the code :
ro_rast <- nc_open("wrf_CAM0_daily_pre.nc")
pre <- ncvar_get(ro_rast, "pre") ro_rast$dim$lon$vals -> lon ro_rast$dim$lat$vals -> lat ro_rast$dim$ncl2$vals -> time rm(ro_rast)
r1_brick <- brick(pre, xmn=min(lat), xmx=max(lat), ymn=min(lon), ymx=max(lon), crs=CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs+ towgs84=0,0,0"))
names(r1_brick)<- seq(as.Date('2018-06-01'), as.Date('2018-08-31'), 'days')
# convert names of layer into date par(mar = c(2, 2, 2, 2))
cam1_mean <- t(calc(r1_brick, sum))
# seasonal sum precipitation
cam1 <- flip(cam1_mean, direction = 2)
library(akima)# intepolation
lonlat_reg <- expand.grid(lon = seq(min(lon), max(lon), length.out = 1499),
lat = seq(min(lat), max(lat), length.out = 749))
test <- interp(x = as.vector(lon), y = as.vector(lat), z = as.vector(pre),
xo = unique(lonlat_reg[,"lon"]), yo = unique(lonlat_reg[,"lat"]),
duplicate = "error", linear = FALSE, extrap = FALSE)
test <- interp(x = as.vector(lon), y = as.vector(lat), z = as.vector(pre),
nx = 1499, ny = 749, linear = FALSE, extrap = FALSE)
# turn into a raster
test_ras <- raster(test)

Answer 1

The standard approach would be
library(raster)
b <- brick("wrf_CAM0_daily_pre.nc")
It that does not work, can you point us to the file you are using?
I get this error message (you should have added that to your question).
Error in .rasterObjectFromCDF(x, type = objecttype, band = band, ...) :
cells are not equally spaced; you should extract values as points
I checked the file, and in this case, the raster is not a regular grid. The size of the cells changes with latitude. The file does not provide the x and y values of the coordinate reference system used. So the best you can do is extract these values as points, as you were doing, using the interface of the ncdf4 or another package. You can then not directly make a RasterBrick. But you do so using rasterize or interpolate.