NCRA
Averagers nces, ncra, and ncwa
The differences between the averagers ncra and nces are analogous to the differences between the concatenators. ncra is designed for averaging record variables from at least one file, while nces is designed for averaging fixed length variables from multiple files. ncra performs a simple arithmetic average over the record dimension of all the input files, with each record having an equal weight in the average. nces performs a simple arithmetic average of all the input files, with each file having an equal weight in the average. Note that ncra cannot average fixed-length variables, but nces can average both fixed-length and record variables. To conserve system memory, use ncra rather thannces where possible (e.g., if each input-file is one record long). The file output from nces will have the same dimensions (meaning dimension names as well as sizes) as the input hyperslabs (see nces netCDF Ensemble Statistics, for a complete description of nces). The file output from ncra will have the same dimensions as the input hyperslabs except for the record dimension, which will have a size of 1 (see ncra netCDF Record Averager, for a complete description of ncra).
ERROR: nco__open() unable to open file "wrfout_d02_2017-08-01_04_00_00"
ERROR NC_ENOTNC Not a netCDF file
ncra -O dust2.cam5.h0.????-12.nc dust2.cam5-mon12.nc
ncra 85.nc 86.nc 87.nc 88.nc 89.nc 8589.nc
// Mean noontime temperature in January正午平均！
ncra -v tpt -d time,"1990-1-1 12:00:00","1990-1-31 23:59:59",24 \
file??.nc noon.nc
平均值时间维的，87.nc没有起到作用呢
ncra -d time,11,13 85.nc 86.nc 87.nc 8512_8602.nc ncra -F -d time,12,14 85.nc 86.nc 87.nc 8512_8602.nc
只取时间维的
ncra -F -d time,3,,12 -v temperature 85.nc 86.nc 87.nc 858687_03.nc
EXAMPLES
Given file 85_0112.nc:
netcdf 85_0112 { dimensions: lat = 64 ; lev = 18 ; lon = 128 ; time = UNLIMITED ; // (12 currently) variables: float lat(lat) ; float lev(lev) ; float lon(lon) ; float time(time) ; float scalar_var ; float three_dmn_var(lat, lev, lon) ; float two_dmn_var(lat, lev) ; float mask(lat, lon) ; float gw(lat) ; }
Average all variables in in.nc over all dimensions and store results in out.nc:
ncwa in.nc out.nc
All variables in in.nc are reduced to scalars in out.nc since ncwa averages over all dimensions unless otherwise specified (with ‘-a’).
Store the zonal (longitudinal) mean of in.nc in out.nc:
ncwa -a lon in.nc out1.nc ncwa -a lon -b in.nc out2.nc
The first command turns lon into a scalar and the second retains lon as a degenerate dimension in all variables.
% ncks -C -H -v lon out1.nc lon = 135 % ncks -C -H -v lon out2.nc lon[0] = 135
In either case the tally is simply the size of lon, i.e., 180 for the 85_0112.nc file described by the sample header above.
Compute the meridional (latitudinal) mean, with values weighted by the corresponding element of gw 72:
ncwa -w gw -a lat in.nc out.nc
Here the tally is simply the size of lat, or 64. The sum of the Gaussian weights is 2.0.
Compute the area mean over the tropical Pacific:
ncwa -w gw -a lat,lon -d lat,-20.,20. -d lon,120.,270. in.nc out.nc区域平均
Here the tally is 64 times 128 = 8192.
Compute the area-mean over the globe using only points for which ORO < 0.5 73:
ncwa -B 'ORO < 0.5' -w gw -a lat,lon in.nc out.nc ncwa -m ORO -M 0.5 -T lt -w gw -a lat,lon in.nc out.nc
It is considerably simpler to specify the complete mask_cond with the single string argument to ‘-B’ than with the three separate switches ‘-m’, ‘-T’, and ‘-M’ 74. If in doubt, enclose the mask_cond within quotes since some of the comparators have special meanings to the shell.
Assuming 70% of the gridpoints are maritime, then here the tally is 0.70 times 8192 = 5734.
Compute the global annual mean over the maritime tropical Pacific:
ncwa -B 'ORO < 0.5' -w gw -a lat,lon,time \ -d lat,-20.0,20.0 -d lon,120.0,270.0 in.nc out.nc ncwa -m ORO -M 0.5 -T lt -w gw -a lat,lon,time \ -d lat,-20.0,20.0 -d lon,120.0,270.0 in.nc out.nc
Further examples will use the one-switch specification of mask_cond.
Determine the total area of the maritime tropical Pacific, assuming the variable area contains the area of each gridcell
ncwa -N -v area -B 'ORO < 0.5' -a lat,lon \ -d lat,-20.0,20.0 -d lon,120.0,270.0 in.nc out.nc
Weighting area (e.g., by gw) is not appropriate because area is already area-weighted by definition. Thus the ‘-N’ switch, or, equivalently, the ‘-y ttl’ switch, correctly integrate the cell areas into a total regional area.
Mask a file to contain _FillValue everywhere except where thr_min <= msk_var <= thr_max:
Set masking variable and its scalar thresholds export msk_var='three_dmn_var_dbl' # Masking variable export thr_max='20' # Maximum allowed value export thr_min='10' # Minimum allowed value ncecat -O in.nc out.nc # Wrap out.nc in degenerate "record" dimension ncwa -O -a record -B "
{thr_max}" out.nc out.nc ncecat -O out.nc out.nc # Wrap out.nc in degenerate "record" dimension ncwa -O -a record -B "
{thr_min}" out.nc out.nc
After the first use of ncwa, out.nc contains _FillValue where {thr_max}. The process is then repeated on the remaining data to filter out points where
{thr_min}. The resulting out.nc contains valid data only where thr_min <= msk_var <= thr_max.
