As far as I know, RNetCDF does not support version 4 format netcdf files, while ncdf4 (which is the current version and should be used in preference to ncdf) does.
They also differ philosophically. RNetCDF is closer to being a straightforward implementation of the C language interface to the netcdf library in R. Ncdf4 is closer to being an interface that maps a netcdf file conveniently into an R style of programming. Which one is preferable depends on your programming background and what you are more familiar and comfortable with. I have not timed RNetCDF. The newest versions of ncdf4 are pretty close to straight C speed (although the older versions are slower -- I've been working on improving the efficiency recently). I use ncdf4 pretty much every day, which means that I keep it up to date with regards to new versions of the netcdf library. However, it is worth pointing out that either RNetCDF or ncdf4 depends on having the underlying netcdf library available on the platform you are using. On some platforms -- notably windows 64 -- that can be problematic. Regards, --Dave On Tue, Sep 17, 2013 at 9:09 AM, Jannis <bt_jan...@yahoo.de> wrote: > Dear package authors, dear r-help list, > > > are there any big differences between the ncdf and the RNetCDF package, > especially with regards to the support of different netcdf versions, future > maintenacne or speed? I have looked at both packages and their capabilities > seem to be quiet identical (with regards to their functions). I ask because > I will give some advice on ncdf and R to a group of people highlighting > some of the (possible) differences. > > > Thanks a lot > Jannis > -- David W. Pierce Division of Climate, Atmospheric Science, and Physical Oceanography Scripps Institution of Oceanography, La Jolla, California, USA (858) 534-8276 (voice) / (858) 534-8561 (fax) dpie...@ucsd.edu [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.