Provided by: nco_4.7.9-1_amd64 bug


       ncbo - netCDF Binary Operator


       ncbo  [-3]  [-4]  [-5]  [-6] [-7] [-A] [--bfr sz_byt][-C][-c] [--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]  [--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] [--unn] [-v var[,...]]  [-X box] [-x] file_1 file_2 file_3


       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).


       Say files and each contain 12 months of data.  Compute the change in
       the monthly averages from 1985 to 1986:

       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.
              ncwa -O -a time
       The second command, ncwa, gets rid of the time dimension of  size  1  that  ncra  left  in   Now  none  of  the  variables  in  has a time dimension.  A quicker way to
       accomplish this is to use ncwa from the beginning:
              ncwa -a time
       We are now ready to use ncbo to compute the anomalies for 1985:
              ncbo -v T
       Each of the 12 records in 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, the
       zonal mean of  Then we use ncbo to subtract the zonal annual means from the monthly
       gridpoint data:
              ncwa -a lon
       Assuming has dimensions time and lon, this example only works if has
       no time or lon dimension.

       As a final example, say we have five years of monthly data (i.e.,  60  months)  stored  in  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
       Next use ncbo to create a file containing the difference of each  month's  data  from  the
       five-year mean:
       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 foo.
              ncra foo.
       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 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


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


       Report bugs to <>.


       Copyright © 1995-2018 Charlie Zender
       This  is  free software; see the source for copying conditions.  There is NO warranty; not


       The full documentation for NCO is maintained as a Texinfo  manual  called  the  NCO  Users
       Guide.   Because  NCO  is mathematical in nature, the documentation includes TeX-intensive
       portions  not  viewable  on  character-based  displays.   Hence  the  only  complete   and
       authoritative  versions  of  the  NCO  Users  Guide  are  the  PDF (recommended), DVI, and
       Postscript  versions  at  <>,  <>,   and
       <>,   respectively.   HTML  and  XML  versions  are  available  at
       <> and <>, respectively.

       If the info and NCO programs are properly installed at your site, the command

              info nco

       should give you access to the complete manual, except for the TeX-intensive portions.


       The NCO homepage at <> contains more information.