I have dealt with
E-OBS gridded dataset and how to cropped raster grid for a particular country (I used
0.25-degree regular grid daily mean temperature observation). However, I have read about
E-OBS grid dataset' publication and they told about maximum 20 percent of missing values might be occurred. After I cropped the raster grid for my interested regions and want to render plain text data with its metadata (geo-coordinate pair and daily level temperature observation), original missing values become
It is important to me because it is difficult for me to differentiate which one is temperature observation (it could be
0 Celsius degree) and which one is missing observation. I want to render missing value with
To avoid this problem, I want to preserve missing values in a cropped raster grid, and treat those missing values when I intend to calculate the yearly average temperature for each coordinate of grid.
How can I deal with missing values in raster grid? Any idea?
I tried @Rodrigo' solution down below:
> tg1980 <- raster::brick("data/tg_0.25deg_reg_1980-1994_v17.0.nc") > tg1980 <- reclassify(tg1980, cbind(NA, -999)) Error: cannot allocate vector of size 1.9 Gb
But now I got a memory problem in R. Any quick solution for that?