I'm working with a netCDF file with a spatially averaged wind variable, which is a function of time only.
I would like to split the file into years with east wind and years with west wind.
I thought I would do it with cdo but I don't know how to write the condition.
Anything with splityear, 'u <0'?
I do not think this is advisable, as you will split the files in to two different NetCDF files with incompatible grids. In my view this would defeat the purpose of storing the data in NetCDF files.
But, if you wish to do it, there is a way within CDO. As you haven't provided files I can outline a strategy.
First create a mask file identifying cells with u<0:
cdo -setrtomiss,-10000,0 -selname,u infile.nc mask.nc
Then apply reducegrid to the infile using this mask:
cdo -reducegrid,mask.nc infile.nc outfile.nc
That should do it for the u condition. Just test that and modify it for the other variables.
Related
I have 9 NC files, corresponding to 9 regions of the world, where longitude is divided by 60, latitude is divided by 120, how can I combine the above 9 files into one global file?
Have tried CDO mergegrid, but can only merge 2 files at a time, is there a way to merge 9 files at a time?
cdo mergegrid is likely the wrong operation for this. You want to try collgrid instead. It sounds like you have the world split into 3x3 equally sized rectangles. Combining these is exactly what collgrid is designed to do. The command should be something like:
cdo collgrid *infile.nc outfile.nc
See page 45 of the user guide for more details https://code.mpimet.mpg.de/projects/cdo/embedded/cdo.pdf
I want to regrid my variable to a file in such a way that the fluxes and other important conservation fields remain conserved and there is no violation of conservation laws.
You can use cdo in the following way
cdo remapcon,newgrid.nc input_file.nc output_file.nc
where newgrid.nc can be any file which has the target grid and input_file is the file which is to be regridded. The result obtained is output_file.nc, one thing to note in this is that the metadata/attributes should be CF compliant for cdo to understand the files and data.
remapcon ensures that conservation laws are not violated.
I have 20 netCDF files containing oceanographic CTD data. Each file contains the same dimension and variable names, however they differ in the size of the vertical coordinate (ie. CTD profiles inshore have a smaller depth range than profiles offshore). I need to concatenate these separate files into one netCDF file with a record variable "station".
I have tried:
ncecat -u station *.nc outfile.nc
This concatenates the files in the correct way, but it takes the dimension size of the first netCDF file (which is the smallest) and so I lose the data below the depth of the shallowest CTD profile for the rest of the netCDF files.
I'm assuming I need to add FillValues (or similar) in place of the data that is shallower than the maximum depth of the deepest CTD profile.
Is there a way to do this using ncecat?
The closest you can get with ncecat alone is to use group aggregation to store each station profile as its own group in a netCDF4 file. Then you do not need to search for and fill-in any missing data:
ncecat --gag *.nc outfile.nc
I want to do something (apparently) simple, but didn't yet find the right way to do it:
I read a netcdf file (wind speed from the ERA5 reanalysis) on a grid.
From this, I use the wind speed to calculate a wind capacity factor (using a given power curve).
I then want to write a new netcdf file, with exactly the same structure as the input file, but just replacing the input wind speed by the new variable (wind capacity factor).
Is there a simple/fast way to do this, avoiding to redefine all the dims, vars ... with ncvar_def and ncdim_def ?
Thanks in advance for your replies!
Writing a netcdf file in R is not overly complicated, there is a nice example online here:
http://geog.uoregon.edu/GeogR/topics/netCDF-write-ncdf4.html
You could copy the dimensions from the input file.
However if your wind power curve is a simple analytical expression then you could perform this task in one line from the command line in bash/linux using climate data operators (cdo).
For example, if you have two variables 10u and 10v in the file (I don't recalled the reanalysis names exactly) then you could make a new variable WCF=SQRT(U2+V2) in the following way
cdo expr,'wcf=sqrt(10u**2+10v**2)' input.nc output.nc
See an example here:
https://code.mpimet.mpg.de/boards/53/topics/1622
So if your window power function is an analytical expression you can define it this way without using R at all or worrying about dimensions etc, the new file will have an variable wcf added. You should then probably use NCO to alter the metadata (units etc) to ensure they are appropriate.
I'm reading a large wrfout data(about 100x100 in space, 30 in vertical, 400 in times) by ncl.
fid=addfile("wrfout_d03.nc","r")
u=fid->U
The variable U is about 500M, so it takes much time, and I also need to read other variables.Is there any way for ncl to read large netcdf data quickly? Or can I use other languages?
It may be more helpful to extract the variables and timeslices you need before reading them into NCL.
To select by variable:
cdo selvar,var in.nc out.nc
To select by level:
cdo sellevel
or levels selected by their index:
cdo sellevidx
you can also extract subsets in terms of dates or times...
More info here:
https://code.mpimet.mpg.de/projects/cdo/wiki/Cdo#Documentation