bionic (1) ncbo.1.gz

Provided by: nco_4.7.2-1_amd64 bug

NAME

       ncbo - netCDF Binary Operator

SYNTAX

       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] [-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

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 © 1995-2018 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.

SEE ALSO

       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 <http://nco.sf.net/nco.pdf>, <http://nco.sf.net/nco.dvi>,
       and   <http://nco.sf.net/nco.ps>,   respectively.    HTML   and   XML   versions   are    available    at
       <http://nco.sf.net/nco.html> and <http://nco.sf.net/nco.xml>, 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.

HOMEPAGE

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

                                                                                                         NCBO(1)