Ubuntu Manpage: ncbo - netCDF Binary Operator

NAME

       ncbo - netCDF Binary Operator

SYNTAX

       ncbo  [-3]  [-4]  [-5] [-6] [-7] [-A] [--bfr sz_byt][-C][-c] [--cmp cmp_sng] [--cnk_byt sz_byt][--cnk_csh
       sz_byt][--cnk_dmn nm,sz_lmn] [--cnk_map map] [--cnk_min sz_byt]  [--cnk_plc  plc]  [--cnk_scl  sz_lmn][-D
       dbg_lvl]  [-d  dim,[  min][,[  max]]]  [-F]  [--fl_fmt=fmt] [-G gpe_dsc] [-g grp[,...]]  [--glb att_name=
       att_val]] [-H] [-h] [--hdf] [--hdr_pad sz_byt][--hpss_try] [-L dfl_lvl] [-l path] [--msa]  [--no_cll_msr]
       [--no_frm_trm]  [--no_tmp_fl]  [-O]  [-p  path]  [-R]  [-r]  [--ram_all] [-t thr_nbr] [--uio] [--unn] [-v
       var[,...]]  [-X box] [-x] file_1 file_2 file_3

DESCRIPTION

ncbo subtracts variables in file_2 from the corresponding variables (those with the same name) in file_1
and stores the results in file_3. Variables in file_2 are broadcast to conform to the corresponding
variable in file_1 if necessary. Broadcasting a variable means creating data in non-existing dimensions
from the data in existing dimensions. For example, a two dimensional variable in file_2 can be
subtracted from a four, three, or two (but not one or zero) dimensional variable (of the same name) in
file_1. This functionality allows the user to compute anomalies from the mean. Note that variables in
file_1 are not broadcast to conform to the dimensions in file_2. Thus, ncbo, the number of dimensions,
or rank, of any processed variable in file_1 must be greater than or equal to the rank of the same
variable in file_2. Furthermore, the size of all dimensions common to both file_1 and file_2 must be
equal.

When computing anomalies from the mean it is often the case that file_2 was created by applying an
averaging operator to a file with the same dimensions as file_1, if not file_1 itself. In these cases,
creating file_2 with ncra rather than ncwa will cause the ncbo operation to fail. For concreteness say
the record dimension in file_1 is time. If file_2 were created by averaging file_1 over the time
dimension with the ncra operator rather than with the ncwa operator, then file_2 will have a time
dimension of size 1 rather than having no time dimension at all In this case the input files to ncbo,
file_1 and file_2, will have unequally sized time dimensions which causes ncbo to fail. To prevent this
from occurring, use ncwa to remove the time dimension from file_2. An example is given below.

ncbo will never difference coordinate variables or variables of type NC_CHAR or NC_BYTE. This ensures
that coordinates like (e.g., latitude and longitude) are physically meaningful in the output file,
file_3. This behavior is hardcoded. ncbo applies special rules to some NCAR CSM fields (e.g., ORO).
See NCAR CSM Conventions for a complete description. Finally, we note that ncflint (ncflint netCDF File
Interpolator) can be also perform file subtraction (as well as addition, multiplication and
interpolation).

EXAMPLES

Say files 85_0112.nc and 86_0112.nc each contain 12 months of data. Compute the change in the monthly
averages from 1985 to 1986:
ncbo 86_0112.nc 85_0112.nc 86m85_0112.nc

The following examples demonstrate the broadcasting feature of ncbo. Say we wish to compute the monthly
anomalies of T from the yearly average of T for the year 1985. First we create the 1985 average from the
monthly data, which is stored with the record dimension time.
ncra 85_0112.nc 85.nc
ncwa -O -a time 85.nc 85.nc
The second command, ncwa, gets rid of the time dimension of size 1 that ncra left in 85.nc. Now none of
the variables in 85.nc has a time dimension. A quicker way to accomplish this is to use ncwa from the
beginning:
ncwa -a time 85_0112.nc 85.nc
We are now ready to use ncbo to compute the anomalies for 1985:
ncbo -v T 85_0112.nc 85.nc t_anm_85_0112.nc
Each of the 12 records in t_anm_85_0112.nc now contains the monthly deviation of T from the annual mean
of T for each gridpoint.

Say we wish to compute the monthly gridpoint anomalies from the zonal annual mean. A zonal mean is a
quantity that has been averaged over the longitudinal (or x) direction. First we use ncwa to average
over longitudinal direction lon, creating xavg_85.nc, the zonal mean of 85.nc. Then we use ncbo to
subtract the zonal annual means from the monthly gridpoint data:
ncwa -a lon 85.nc xavg_85.nc
ncbo 85_0112.nc xavg_85.nc tx_anm_85_0112.nc
Assuming 85_0112.nc has dimensions time and lon, this example only works if xavg_85.nc has no time or lon
dimension.

As a final example, say we have five years of monthly data (i.e., 60 months) stored in 8501_8912.nc and
we wish to create a file which contains the twelve month seasonal cycle of the average monthly anomaly
from the five-year mean of this data. The following method is just one permutation of many which will
accomplish the same result. First use ncwa to create the file containing the five-year mean:
ncwa -a time 8501_8912.nc 8589.nc
Next use ncbo to create a file containing the difference of each month's data from the five-year mean:
ncbo 8501_8912.nc 8589.nc t_anm_8501_8912.nc
Now use ncks to group the five January anomalies together in one file, and use ncra to create the average
anomaly for all five Januarys. These commands are embedded in a shell loop so they are repeated for all
twelve months:
foreach idx (01 02 03 04 05 06 07 08 09 10 11 12)
ncks -F -d time,,,12 t_anm_8501_8912.nc foo.
ncra foo. t_anm_8589_.nc
end
Note that ncra understands the stride argument so the two commands inside the loop may be combined into
the single command
ncra -F -d time,,,12 t_anm_8501_8912.nc foo.
Finally, use ncrcat to concatenate the 12 average monthly anomaly files into one twelve-record file which
contains the entire seasonal cycle of the monthly anomalies:
ncrcat t_anm_8589_??.nc t_anm_8589_0112.nc

AUTHOR

       NCO manual pages written by Charlie Zender and originally formatted by Brian Mays.

REPORTING BUGS

       Report bugs to <http://sf.net/bugs/?group_id=3331>.

COPYRIGHT

       Copyright © 1995-present Charlie Zender
       This is free software; see the source for copying  conditions.   There  is  NO  warranty;  not  even  for
       MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

HOMEPAGE

       The NCO homepage at <http://nco.sf.net> contains more information.

                                                                                                         NCBO(1)