NCES(1) | General Commands Manual | NCES(1) |
nces - netCDF Ensemble Statistics
nces [-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]]] [--dbl|flt] [-F] [--fl_fmt=fmt] [-G gpe_dsc] [-g grp[,...]] [-h] [--hdf] [--hdr_pad sz_byt] [-L dfl_lvl] [-l path] [--msa] [-N] [-n loop] [--no_cll_msr] [--no_frm_trm] [--no_tmp_fl] [--nsm_sfx grp_sfx] [-O] [-p path] [--ppc var1[, var2[,...]]= prc]] [-R] [-r] [--ram_all] [-t thr_nbr] [--unn] [-v var[,...]] [-X box] [-x] [-y op_typ] input-files output-file
nces performs gridpoint averages of variables across an arbitrary number (an ensemble) of input files, with each file receiving an equal weight in the average. Each variable in the output-file will be the same size as the same variable in any one of the in the input-files, and all input-files must be the same size. Whereas ncra only performs averages over the record dimension (e.g., time), and weights each record in the record dimension evenly, nces averages entire files, and weights each file evenly. All dimensions, including the record dimension, are treated identically and preserved in the output-file.
The file is the logical unit of organization for the results of many scientific studies. Often one wishes to generate a file which is the gridpoint average of many separate files. This may be to reduce statistical noise by combining the results of a large number of experiments, or it may simply be a step in a procedure whose goal is to compute anomalies from a mean state. In any case, when one desires to generate a file whose properties are the mean of all the input files, then nces is the operator to use. nces assumes coordinate variable are properties common to all of the experiments and so does not average them across files. Instead, nces copies the values of the coordinate variables from the first input file to the output file.
Consider a model experiment which generated five realizations of one year of data, say 1985. You can imagine that the experimenter slightly perturbs the initial conditions of the problem before generating each new solution. Assume each file contains all twelve months (a seasonal cycle) of data and we want to produce a single file containing the ensemble average (mean) seasonal cycle. Here the numeric filename suffix denotes the experiment number (not the month):
In the previous example, the user could have obtained the ensemble average values in a particular spatio-temporal region by adding a hyperslab argument to the command, e.g.,
NCO manual pages written by Charlie Zender and originally formatted by Brian Mays.
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Copyright © 1995-2018 Charlie Zender
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ncap(1), ncap2(1), ncatted(1), ncbo(1), ncclimo(1), nces(1), ncecat(1), ncflint(1), ncks(1), nco(1), ncpdq(1), ncra(1), ncrcat(1), ncremap(1), ncrename(1), ncwa(1)
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