NCO is the result of software needs that arose while I worked
on projects funded by NCAR, NASA, and ARM.
Thinking they might prove useful as tools or templates to others,
it is my pleasure to provide them freely to the scientific community.
Many users (most of whom I have never met) have encouraged the
development of NCO.
Thanks espcially to Jan Polcher, Keith Lindsay, Arlindo da Silva, John
Sheldon, and William Weibel for stimulating suggestions and
correspondence.
Your encouragment motivated me to complete the NCO User's Guide.
So if you like NCO, send me a note!
I should mention that NCO is not connected to or
officially endorsed by Unidata, ACD, ASP,
CGD, or Nike.
Charlie Zender
Major feature improvements entitle me to write another Foreword. In the last five years a lot of work has been done refining NCO. NCO is now an open source project and appears to be much healthier for it. The list of illustrious institutions which do not endorse NCO continues to grow, and now includes UCI.
Charlie Zender
The most remarkable advances in NCO capabilities in the last few years are due to contributions from the Open Source community. Especially noteworthy are the contributions of Henry Butowsky and Rorik Peterson.
Charlie Zender
This manual describes NCO, which stands for netCDF Operators. NCO is a suite of programs known as operators. Each operator is a standalone, command line program executed at the shell-level like, e.g., ls or mkdir. The operators take netCDF file(s) (or HDF4 files) as input, perform an operation (e.g., averaging or hyperslabbing), and produce a netCDF file as output. The operators are primarily designed to aid manipulation and analysis of data. The examples in this documentation are typical applications of the operators for processing climate model output. This reflects their origin, but the operators are as general as netCDF itself.
The complete NCO source distribution is currently distributed
as a compressed tarfile from
http://sf.net/projects/nco
and from
http://dust.ess.uci.edu/nco/nco.tar.gz.
The compressed tarfile must be uncompressed and untarred before building
NCO.
Uncompress the file with `gunzip nco.tar.gz'.
Extract the source files from the resulting tarfile with `tar -xvf
nco.tar'.
GNU tar lets you perform both operations in one step
with `tar -xvzf nco.tar.gz'.
The documentation for NCO is called the NCO User's Guide. The User's Guide is available in Postscript, HTML, DVI, TeXinfo, and Info formats. These formats are included in the source distribution in the files nco.ps, nco.html, nco.dvi, nco.texi, and nco.info*, respectively. All the documentation descends from a single source file, nco.texi 1. Hence the documentation in every format is very similar. However, some of the complex mathematical expressions needed to describe ncwa can only be displayed in the Postscript and DVI formats.
If you want to quickly see what the latest improvements in NCO are (without downloading the entire source distribution), visit the NCO homepage at http://nco.sf.net. The HTML version of the User's Guide is also available online through the World Wide Web at URL http://nco.sf.net/nco.html. To build and use NCO, you must have netCDF installed. The netCDF homepage is http://www.unidata.ucar.edu/packages/netcdf.
New NCO releases are announced on the netCDF list and on the
nco-announce mailing list
http://lists.sf.net/mailman/listinfo/nco-announce.
NCO has been successfully ported and tested and is known to work on the following 32 and 64 bit platforms: IBM AIX 4.x, 5.x, FreeBSD 4.x, GNU/Linux 2.x, LinuxPPC, LinuxAlpha, LinuxSparc64, SGI IRIX 5.x and 6.x, MacOS X 10.x, NEC Super-UX 10.x, DEC OSF, Sun SunOS 4.1.x, Solaris 2.x, Cray UNICOS 8.x–10.x, all MS Windows. If you port the code to a new operating system, please send me a note and any patches you required.
The major prerequisite for installing NCO on a particular platform is the successful, prior installation of the netCDF library (and, as of 2003, the UDUnits library). Unidata has shown a commitment to maintaining netCDF and UDUnits on all popular UNIX platforms, and is moving towards full support for the Microsoft Windows operating system (OS). Given this, the only difficulty in implementing NCO on a particular platform is standardization of various C and Fortran interface and system calls. NCO code is tested for ANSI compliance by compiling with C compilers including those from GNU (`gcc -std=c99 -pedantic -D_BSD_SOURCE' -Wall) 2, Comeau Computing (`como --c99'), Cray (`cc'), HP/Compaq/DEC (`cc'), IBM (`xlc -c -qlanglvl=extended'), Intel (`icc'), NEC (`cc'), SGI (`cc -LANG:std'), and Sun (`cc'). NCO (all commands and the libnco library) and the C++ interface to netCDF (called libnco_c++) comply with the ISO C++ standards as implemented by Comeau Computing (`como'), Cray (`CC'), GNU (`g++ -Wall'), HP/Compaq/DEC (`cxx'), IBM (`xlC'), Intel (`icc'), NEC (`c++'), SGI (`CC -LANG:std'), and Sun (`CC -LANG:std'). See nco/bld/Makefile and nco/src/nco_c++/Makefile.old for more details and exact settings.
Until recently (and not even yet), ANSI-compliant has meant
compliance with the 1989 ISO C-standard, usually called C89 (with
minor revisions made in 1994 and 1995).
C89 lacks variable-size arrays, restricted pointers, and some useful
printf formats.
These are valuable features of C99, the 1999 ISO C-standard.
NCO is C99-compliant where possible and C89-compliant where
necessary.
Certain branches in the code are required to satisfy the native
SGI and SunOS C compilers, which are strictly ANSI
C89 compliant, and cannot benefit from C99 features.
However, C99 features are fully supported by modern AIX,
GNU, Intel, NEC, Solaris, and UNICOS
compilers.
NCO requires a C99-compliant compiler as of NCO
version 2.9.8, released in August, 2004.
The most time-intensive portion of NCO execution is spent in
arithmetic operations, e.g., multiplication, averaging, subtraction.
These operations were performed in Fortran by default until August,
1999.
This was a design decision based on the relative speed of Fortran-based
object code vs. C-based object code in late 1994.
C compilers have dramatically improved their vectorization
capabilities since 1994.
We have accordingly replaced all Fortran subroutines with C functions.
This greatly simplifies the task of building NCO on nominally
unsupported platforms.
As of August 1999, NCO built entirely in C by default.
This allowed NCO to compile on any machine with an
ANSI C compiler.
In August 2004, the first C99 feature, the restrict type
qualifier, entered NCO in version 2.9.8.
C compilers can obtain better performance with C99 restricted
pointers since they inform the compiler when it may make Fortran-like
assumptions regarding pointer contents alteration.
Subsequently, NCO requires a C99 compiler to build correctly
3.
Furthermore, NCO automagically takes advantage of extensions
to ANSI C when compiled with the GNU compiler
collection, GCC.
As of July 2000 and NCO version 1.2, NCO no
longer supports performing arithmetic operations in Fortran.
We decided to sacrifice executable speed for code maintainability
Since no objective statistics were ever performed to quantify
the difference in speed between the Fortran and C code,
the performance penalty incurred by this decision is unknown.
Supporting Fortran involves maintaining two sets of routines for every
arithmetic operation.
The USE_FORTRAN_ARITHMETIC flag is still retained in the
Makefile.
The file containing the Fortran code, nco_fortran.F, has been
deprecated but can be resurrected if a volunteer comes forward.
If you would like to volunteer to maintain nco_fortran.F please
contact me.
NCO has been successfully ported and tested on the Microsoft
Windows (95/98/NT/2000/XP) operating systems.
The switches necessary to accomplish this are included in the standard
distribution of NCO.
Using the freely available Cygwin (formerly gnu-win32) development
environment
4, the compilation process is very similar to
installing NCO on a UNIX system.
Set the PVM_ARCH preprocessor token to WIN32.
Note that defining WIN32 has the side effect of disabling
Internet features of NCO (see below).
Unless you have a Fortran compiler (like g77 or f90)
available, no other tokens are required.
Users with fast Fortran compilers may wish to activate the Fortran
arithmetic routines.
To do this, define the preprocessor token USE_FORTRAN_ARITHMETIC
in the makefile which comes with NCO, Makefile, or in
the compilation shell.
The least portable section of the code is the use of standard
UNIX and Internet protocols (e.g., ftp, rcp,
scp, getuid, gethostname, and header files
<arpa/nameser.h> and
<resolv.h>).
Fortunately, these UNIX-y calls are only invoked by the single
NCO subroutine which is responsible for retrieving files
stored on remote systems (see Remote storage).
In order to support NCO on the Microsoft Windows platforms,
this single feature was disabled (on Windows OS only).
This was required by Cygwin 18.x—newer versions of Cygwin may
support these protocols (let me know if this is the case).
The NCO operators should behave identically on Windows and
UNIX platforms in all other respects.
Like all executables, the NCO operators can be built using dynamic linking. This reduces the size of the executable and can result in significant performance enhancements on multiuser systems. Unfortunately, if your library search path (usually the LD_LIBRARY_PATH environment variable) is not set correctly, or if the system libraries have been moved, renamed, or deleted since NCO was installed, it is possible NCO operators will fail with a message that they cannot find a dynamically loaded (aka shared object or `.so') library. This will produce a distinctive error message, such as `ld.so.1: /usr/local/bin/ncea: fatal: libsunmath.so.1: can't open file: errno=2'. If you received an error message like this, ask your system administrator to diagnose whether the library is truly missing 5, or whether you simply need to alter your library search path. As a final remedy, you may re-compile and install NCO with all operators statically linked.
netCDF version 2.x was released in 1993.
NCO (specifically ncks) began soon after this in 1994.
netCDF 3.0 was released in 1996, and we were eager to reap the
performance advantages of the newer netCDF implementation.
One netCDF 3.x interface call (nc_inq_libvers) was added to
NCO in January, 1998, to aid in maintainance and debugging.
In March, 2001, the final conversion of NCO to netCDF 3.x
was completed (coincidentally on the same day netCDF 3.5 was
released).
NCO versions 2.0 and higher are built with the
-DNO_NETCDF_2 flag to ensure no netCDF 2.x interface calls
are used.
However, the ability to compile NCO with only netCDF 2.x
calls is worth maintaining because HDF version 4
6
(available from HDF)
supports only the netCDF 2.x library calls
(see http://hdf.ncsa.uiuc.edu/UG41r3_html/SDS_SD.fm12.html#47784).
Note that there are multiple versions of HDF.
Currently HDF version 4.x supports netCDF 2.x and thus
NCO version 1.2.x.
If NCO version 1.2.x (or earlier) is built with only
netCDF 2.x calls then all NCO operators should work with
HDF4 files as well as netCDF files
7.
The preprocessor token NETCDF2_ONLY exists
in NCO version 1.2.x to eliminate all netCDF 3.x
calls.
Only versions of NCO numbered 1.2.x and earlier have this
capability.
The NCO 1.2.x branch will be maintained with bugfixes only
(no new features) until HDF begins to fully support the
netCDF 3.x interface (which is employed by NCO 2.x).
If, at compilation time, NETCDF2_ONLY is defined, then
NCO version 1.2.x will not use any netCDF 3.x calls
and, if linked properly, the resulting NCO operators will work
with HDF4 files.
The Makefile supplied with NCO 1.2.x is written
to simplify building in this HDF capability.
When NCO is built with make HDF4=Y, the Makefile
sets all required preprocessor flags and library links to build
with the HDF4 libraries (which are assumed to reside under
/usr/local/hdf4, edit the Makefile to suit your
installation).
HDF version 5.x became available in 1999, but did not support netCDF (or, for that matter, Fortran) as of December 1999. By early 2001, HDF version 5.x did support Fortran90. However, support for netCDF 3.x in HDF 5.x is incomplete. Much of the HDF5-netCDF3 interface is complete, however, and it may be separately downloaded from the HDF5-netCDF website. Now that NCO uses only netCDF 3.x system calls we are eager for HDF5 to add complete netCDF 3.x support. This is scheduled to occur sometime in 2005, with the release of netCDF version 4, a collaboration between Unidata and NCSA.
We generally receive three categories of mail from users: help requests, bug reports, and feature requests. Notes saying the equivalent of "Hey, NCO continues to work great and it saves me more time everyday than it took to write this note" are a distant fourth.
There is a different protocol for each type of request. The common procedural etiquette is to communicate with us via NCO Project Forums. Unless your request comes with money or you have damaging information about our personal lives, use the Forums. They preserve a record of the questions and answers so that others might learn from our exchange. Also, should NCO ever be funded (as is our hope), this record will provide program officers with information they need to evaluate us.
Before posting to the NCO forums described below, you might first register your name and email address with SourceForge.net or else all of your postings will be attributed to "nobody". Once registered you may choose to "monitor" any forum and to receive (or not) email when there are any postings including responses to your questions. We usually reply to the forum message, not to the original poster.
If you want us to include a new feature in NCO, check first to see if that feature is already on the TODO list. If it is, why not implement that feature yourself and send us the patch? If the feature is not yet on the list, then send a note to the NCO Discussion forum.
Read the manual before reporting a bug or posting a help request. Sending questions whose answers are not in the manual is the best way to motivate us to write more documentation. We would also like to accentuate the contrapositive of this statement. If you think you have found a real bug the most helpful thing you can do is simplify the problem to a manageable size and then report it. The first thing to do is to make sure you are running the latest publicly released version of NCO.
Once you have read the manual, if you are still unable to get NCO to perform a documented function, write help request. Follow the same procedure as described below for reporting bugs (after all, it might be a bug). That is, describe what you are trying to do, and include the complete commands (run with `-D 5'), error messages, and version of NCO (with `-r'). Post your help request to the NCO Help forum.
If you think you are using the right command, but NCO is misbehaving, then you might have found a bug. Incorrect numerical answers are the highest priority. We usually fix those within one or two days. Core dumps and sementation violations receive lower priority. They are always fixed.
How do you simplify a problem that may be revealing a bug? Cut out extraneous variables, dimensions, and metadata from the offending files and re-run the command until it no longer breaks. Then back up one step and report the problem. Usually the file(s) will be very small, i.e., one variable with one or two small dimensions ought to suffice. Run the operator with `-r' and then run the command with `-D 5' to increase the verbosity of the debugging output. It is very important that your report contain the exact error messages and compile-time environment. Include a copy of your sample input file, or place one on a publically accessible location, of the file(s). Post the full bug report to the NCO Project buglist.
Build failures count as bugs.
Our limited machine access means we cannot fix all build failures.
The information we need to diagnose, and often fix, build failures
are the three files output by GNU build tools,
nco.config.log.${GNU_TRP}.foo,
nco.configure.${GNU_TRP}.foo,
and nco.make.${GNU_TRP}.foo.
The file configure.eg shows how to produce these files.
Here ${GNU_TRP} is the "GNU architecture triplet",
the chip-vendor-OS string returned by config.guess.
Please send us your improvements to the examples supplied in
configure.eg.
The regressions archive at http://dust.ess.uci.edu/nco/rgr
contains the build output from our standard test systems.
You may find you can solve the build problem yourself by examining the
differences between these files and your own.
The main design goal has been to produce operators that can be invoked from the command line to perform useful operations on netCDF files. Many scientists work with models and observations which produce too much data to analyze in tabular format. Thus, it is often natural to reduce and massage this raw or primary level data into summary, or second level data, e.g., temporal or spatial averages. These second level data may become the inputs to graphical and statistical packages, and are often more suitable for archival and dissemination to the scientific community. NCO performs a suite of operations useful in manipulating data from the primary to the second level state. Higher level interpretive languages (e.g., IDL, Yorick, Matlab, NCL, Perl, Python), and lower level compiled languages (e.g., C, Fortran) can always perform any task performed by NCO, but often with more overhead. NCO, on the other hand, is limited to a much smaller set of arithmetic and metadata operations than these full blown languages.
Another goal has been to implement enough command line switches so that frequently used sequences of these operators can be executed from a shell script or batch file. Finally, NCO was written to consume the absolute minimum amount of system memory required to perform a given job. The arithmetic operators are extremely efficient; their exact memory usage is detailed in Memory usage.
NCO was developed at NCAR to aid analysis and manipulation of datasets produced by General Circulation Models (GCMs). Datasets produced by GCMs share many features with all gridded scientific datasets and so provide a useful paradigm for the explication of the NCO operator set. Examples in this manual use a GCM paradigm because latitude, longitude, time, temperature and other fields related to our natural environment are as easy to visualize for the layman as the expert.
NCO operators are designed to be reasonably fault tolerant, so
that if there is a system failure or the user aborts the operation (e.g.,
with C-c), then no data are lost.
The user-specified output-file is only created upon successful
completion of the operation
8.
This is accomplished by performing all operations in a temporary copy
of output-file.
The name of the temporary output file is constructed by appending
.pid<process ID>.<operator name>.tmp to the
user-specified output-file name.
When the operator completes its task with no fatal errors, the temporary
output file is moved to the user-specified output-file.
Note the construction of a temporary output file uses more disk space
than just overwriting existing files “in place” (because there may be
two copies of the same file on disk until the NCO operation
successfully concludes and the temporary output file overwrites the
existing output-file).
Also, note this feature increases the execution time of the operator
by approximately the time it takes to copy the output-file.
Finally, note this feature allows the output-file to be the same
as the input-file without any danger of “overlap”.
Other safeguards exist to protect the user from inadvertently overwriting data. If the output-file specified for a command is a pre-existing file, then the operator will prompt the user whether to overwrite (erase) the existing output-file, attempt to append to it, or abort the operation. However, in processing large amounts of data, too many interactive questions slows productivity. Therefore NCO also implements two ways to override its own safety features, the `-O' and `-A' switches. Specifying `-O' tells the operator to overwrite any existing output-file without prompting the user interactively. Specifying `-A' tells the operator to attempt to append to any existing output-file without prompting the user interactively. These switches are useful in batch environments because they suppress interactive keyboard input.
A frequently useful operation is adding variables from one file to another. This is referred to as appending, although some prefer the terminology merging 9 or pasting. Appending is often confused with what NCO calls concatenation. In NCO, concatenation refers to splicing a variable along the record dimension. Appending, on the other hand, refers to adding variables from one file to another 10. In this sense, ncks can append variables from one file to another file. This capability is invoked by naming two files on the command line, input-file and output-file. When output-file already exists, the user is prompted whether to overwrite, append/replace, or exit from the command. Selecting overwrite tells the operator to erase the existing output-file and replace it with the results of the operation. Selecting exit causes the operator to exit—the output-file will not be touched in this case. Selecting append/replace causes the operator to attempt to place the results of the operation in the existing output-file, See ncks netCDF Kitchen Sink.
The simplest way to create the union of two files is
ncks -A fl_1.nc fl_2.nc
This puts the contents of fl_1.nc into fl_2.nc. The `-A' is optional. On output, fl_2.nc is the union of the input files, regardless of whether they share dimensions and variables, or are completely disjoint. The append fails if the input files have differently named record dimensions (since netCDF supports only one), or have dimensions of the same name but different sizes.
Users comfortable with NCO semantics may find it easier to perform some simple mathematical operations in NCO rather than higher level languages. ncbo (see ncbo netCDF Binary Operator) does file addition, subtraction, multiplication, division, and broadcasting. ncflint (see ncflint netCDF File Interpolator) does file addition, subtraction, multiplication and interpolation. Sequences of these commands can accomplish simple but powerful operations from the command line.
The most frequently used operators of NCO are probably the averagers and concatenators. Because there are so many permutations of averaging (e.g., across files, within a file, over the record dimension, over other dimensions, with or without weights and masks) and of concatenating (across files, along the record dimension, along other dimensions), there are currently no fewer than five operators which tackle these two purposes: ncra, ncea, ncwa, ncrcat, and ncecat. These operators do share many capabilities 11, but each has its unique specialty. Two of these operators, ncrcat and ncecat, are for concatenating hyperslabs across files. The other two operators, ncra and ncea, are for averaging hyperslabs across files 12. First, let's describe the concatenators, then the averagers.
Joining independent files together along a record dimension is called
concatenation.
ncrcat is designed for concatenating record variables, while
ncecat is designed for concatenating fixed length variables.
Consider five files, 85.nc, 86.nc,
... 89.nc each containing a year's worth of data.
Say you wish to create from them a single file, 8589.nc
containing all the data, i.e., spanning all five years.
If the annual files make use of the same record variable, then
ncrcat will do the job nicely with, e.g.,
ncrcat 8?.nc 8589.nc.
The number of records in the input files is arbitrary and can vary from
file to file.
See ncrcat netCDF Record Concatenator, for a complete description of
ncrcat.
However, suppose the annual files have no record variable, and thus
their data are all fixed length.
For example, the files may not be conceptually sequential, but rather
members of the same group, or ensemble.
Members of an ensemble may have no reason to contain a record dimension.
ncecat will create a new record dimension (named record
by default) with which to glue together the individual files into the
single ensemble file.
If ncecat is used on files which contain an existing record
dimension, that record dimension is converted to a fixed-length
dimension of the same name and a new record dimension (named
record) is created.
Consider five realizations, 85a.nc, 85b.nc,
... 85e.nc of 1985 predictions from the same climate
model.
Then ncecat 85?.nc 85_ens.nc glues the individual realizations
together into the single file, 85_ens.nc.
If an input variable was dimensioned [lat,lon], it will
have dimensions [record,lat,lon] in the output file.
A restriction of ncecat is that the hyperslabs of the
processed variables must be the same from file to file.
Normally this means all the input files are the same size, and contain
data on different realizations of the same variables.
See ncecat netCDF Ensemble Concatenator, for a complete description
of ncecat.
ncpdq makes it possible to concatenate files along any
dimension, not just the record dimension.
First, use ncpdq to convert the dimension to be concatenated
(i.e., extended with data from other files) into the record dimension.
Second, use ncrcat to concatenate these files.
Finally, if desirable, use ncpdq to revert to the original
dimensionality.
As a concrete example, say that files x_01.nc, x_02.nc,
... x_10.nc contain time-evolving datasets from spatially
adjacent regions.
The time and spatial coordinates are time and x, respectively.
Initially the record dimension is time.
Our goal is to create a single file that contains joins all the
spatially adjacent regions into one single time-evolving dataset.
for idx in 01 02 03 04 05 06 07 08 09 10; do # Bourne Shell
ncpdq -a x,time x_${idx}.nc foo_${idx}.nc # Make x record dimension
done
ncrcat foo_??.nc out.nc # Concatenate along x
ncpdq -a time,x out.nc out.nc # Revert to time as record dimension
Note that ncrcat will not concatenate fixed-length variables, whereas ncecat concatenates both fixed-length and record variables along a new record variable. To conserve system memory, use ncrcat where possible.
The differences between the averagers ncra and ncea are analogous to the differences between the concatenators. ncra is designed for averaging record variables from at least one file, while ncea 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. ncea 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 ncea can average both fixed-length and record variables. To conserve system memory, use ncra rather than ncea where possible (e.g., if each input-file is one record long). The file output from ncea will have the same dimensions (meaning dimension names as well as sizes) as the input hyperslabs (see ncea netCDF Ensemble Averager, for a complete description of ncea). 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).
ncflint can interpolate data between or two files. Since no other operators have this ability, the description of interpolation is given fully on the ncflint reference page (see ncflint netCDF File Interpolator). Note that this capability also allows ncflint to linearly rescale any data in a netCDF file, e.g., to convert between differing units.
Occasionally one desires to digest (i.e., concatenate or average)
hundreds or thousands of input files.
Unfortunately, data archives (e.g., NASA EOSDIS) may not
name netCDF files in a format understood by the `-n loop'
switch (see Specifying input files) that automagically generates
arbitrary numbers of input filenames.
The `-n loop' switch has the virtue of being concise,
and of minimizing the command line.
This helps keeps output file small since the command line is stored
as metadata in the history attribute
(see History attribute).
However, the `-n loop' switch is useless when there is no
simple, arithmetic pattern to the input filenames (e.g.,
h00001.nc, h00002.nc, ... h90210.nc).
Moreover, filename globbing does not work when the input files are too
numerous or their names are too lengthy (when strung together as a
single argument) to be passed by the calling shell to the NCO
operator
13.
When this occurs, the ANSI C-standard argc-argv
method of passing arguments from the calling shell to a C-program (i.e.,
an NCO operator) breaks down.
There are (at least) three alternative methods of specifying the input
filenames to NCO in environment-limited situations.
The recommended method for sending very large numbers (hundreds or
more, typically) of input filenames to the multi-file operators is
to use the standard input, aka stdin, feature of
UNIX.
# Pipe large numbers of filenames to stdin
/bin/ls | grep ${CASEID}_'......'.nc | ncecat -O -o foo.nc
This method avoids all constraints on command line size imposed by
the operating system.
A drawback to this method is that the history attribute
(see History attribute) does not record the name of any input
files since the names were not passed on the command line.
This makes determining the data provenance at a later date difficult.
To remedy this situation, multi-file operators store the number of
input files in the nco_input_file_number global attribute and the
input file list itself in the nco_input_file_list global attribute
(see Input file list attributes).
Although this does not preserve the exact command used to generate the
file, it does retains all the information required to reconstruct the
command and determine the data provenance.
A second option is to use the UNIX xargs command. This simple example selects as input to xargs all the filenames in the current directory that match a given pattern. For illustration, consider a user trying to average millions of files which each have a six character filename. If the shell buffer can not hold the results of the corresponding globbing operator, ??????.nc, then the filename globbing technique will fail. Instead we express the filename pattern as an extended regular expression, ......\.nc (see Variable subsetting). We use grep to filter the directory listing for this pattern and to pipe the results to xargs which, in turn, passes the matching filenames to an NCO multi-file operator, e.g., ncecat.
# Use xargs to transfer filenames on the command line
/bin/ls | grep ${CASEID}_'......'.nc | xargs -x ncecat -o foo.nc
The single quotes protect the only sensitive parts of the extended
regular expression (the grep argument), and allow shell
interpolation (the ${CASEID} variable substitution) to
proceed unhindered on the rest of the command.
xargs uses the UNIX pipe feature to append the
suitably filtered input file list to the end of the ncecat
command options.
The -o foo.nc switch ensures that the input files supplied by
xargs are not confused with the output file name.
xargs does, unfortunately, have its own limit (usually about
20,000 characters) on the size of command lines it can pass.
Give xargs the `-x' switch to ensure it dies if it
reaches this internal limit.
When this occurs, use either the stdin method above, or the
symbolic link presented next.
Even when its internal limits have not been reached, the xargs technique may not be sophisticated enough to handle all situations. A full scripting language like Perl can handle any level of complexity of filtering input filenames, and any number of filenames. The technique of last resort is write a script that creates symbolic links between the irregular input filenames and a set of regular, arithmetic filenames that `-n loop' switch understands. For example, the following Perl script a monotonically enumerated symbolic link to up to one million .nc files in a directory. If there are 999,999 netCDF files present, the links are named 000001.nc to 999999.nc:
# Create enumerated symbolic links
/bin/ls | grep \.nc | perl -e \
'$idx=1;while(<STDIN>){chop;symlink $_,sprintf("%06d.nc",$idx++);}'
ncecat -O -n 999999,6,1 000001.nc foo.nc
# Remove symbolic links when finished
/bin/rm ??????.nc
The `-n loop' option tells the NCO operator to
automatically generate the filnames of the symbolic links.
This circumvents any OS and shell limits on command line size.
The symbolic links are easily removed once NCO is finished.
One drawback to this method is that the history attribute
(see History attribute) retains the filename list of the symbolic
links, rather than the data files themselves.
This makes it difficult to determine the data provenance at a later date.
Large datasets are those files that are comparable in size to the amount of random access memory (RAM) in your computer. Many users of NCO work with files larger than 100 MB. Files this large not only push the current edge of storage technology, they present special problems for programs which attempt to access the entire file at once, such as ncea and ncecat. If you work with a 300 MB files on a machine with only 32 MB of memory then you will need large amounts of swap space (virtual memory on disk) and NCO will work slowly, or even fail. There is no easy solution for this. The best strategy is to work on a machine with sufficient amounts of memory and swap space. Since about 2004, many users have begun to produce or analyze files exceeding 2 GB in size. These users should familiarize themselves with NCO's Large File Support (LFS) capabilities (see Large File Support). The next section will increase your familiarity with NCO's memory requirements. With this knowledge you may re-design your data reduction approach to divide the problem into pieces solvable in memory-limited situations.
If your local machine has problems working with large files, try running
NCO from a more powerful machine, such as a network server.
Certain machine architectures, e.g., Cray UNICOS, have special
commands which allow one to increase the amount of interactive memory.
On Cray systems, try to increase the available memory with the
ilimit command.
If you get a memory-related core dump
(e.g., `Error exit (core dumped)') on a GNU/Linux system,
try increasing the process-available memory with ulimit.
The speed of the NCO operators also depends on file size.
When processing large files the operators may appear to hang, or do
nothing, for large periods of time.
In order to see what the operator is actually doing, it is useful to
activate a more verbose output mode.
This is accomplished by supplying a number greater than 0 to the
`-D debug-level' (or `--debug-level', or
`--dbg_lvl') switch.
When the debug-level is nonzero, the operators report their
current status to the terminal through the stderr facility.
Using `-D' does not slow the operators down.
Choose a debug-level between 1 and 3 for most situations,
e.g., ncea -D 2 85.nc 86.nc 8586.nc.
A full description of how to estimate the actual amount of memory the
multi-file NCO operators consume is given in
Memory usage.
Many people use NCO on gargantuan files which dwarf the memory available (free RAM plus swap space) even on today's powerful machines. These users will want NCO to consume the absolute minimum peak memory possible so that their scripts do not have to tediously cut files into smaller pieces that fit into memory. We commend these greedy users for pushing NCO to its limits!
This section describes the memory NCO requires during operation. The required memory is based on the underlying algorithms. The description below is the memory usage per thread. Users with shared memory machines may use the threaded NCO operators (see OpenMP threading). The peak and sustained memory usage will scale accordingly, i.e., by the number of threads. Memory consumption patterns of all operators are similar, with the exception of ncap.
The multi-file operators currently comprise the record operators, ncra and ncrcat, and the ensemble operators, ncea and ncecat. The record operators require much less memory than the ensemble operators. This is because the record operators operate on one single record (i.e., time-slice) at a time, wherease the ensemble operators retrieve the entire variable into memory. Let MS be the peak sustained memory demand of an operator, FT be the memory required to store the entire contents of all the variables to be processed in an input file, FR be the memory required to store the entire contents of a single record of each of the variables to be processed in an input file, VR be the memory required to store a single record of the largest record variable to be processed in an input file, VT be the memory required to store the largest variable to be processed in an input file, VI be the memory required to store the largest variable which is not processed, but is copied from the initial file to the output file. All operators require MI = VI during the initial copying of variables from the first input file to the output file. This is the initial (and transient) memory demand. The sustained memory demand is that memory required by the operators during the processing (i.e., averaging, concatenation) phase which lasts until all the input files have been processed. The operators have the following memory requirements: ncrcat requires MS <= VR. ncecat requires MS <= VT. ncra requires MS = 2FR + VR. ncea requires MS = 2FT + VT. ncbo requires MS <= 2VT. ncpdq requires MS <= 2VT. ncflint requires MS <= 2VT. Note that only variables which are processed, i.e., averaged or concatenated, contribute to MS. Memory is never allocated to hold variables which do not appear in the output file (see Variable subsetting).
ncap has unique memory requirements due its ability to process arbitrarily long scripts of any complexity. All script acceptable to ncap are ultimately processed as a sequence of binary or unary operations. ncap requires MS <= 2VT under most conditions. An exception to this is when left hand casting (see Left hand casting) is used to stretch the size of derived variables beyond the size of any input variables. Let VC be the memory required to store the largest variable defined by left hand casting. In this case, MS <= 2VC.
ncap scripts are complete dynamic and may be of arbitrary length. A script that contains many thousands of operations, may uncover a slow memory leak even though each single operation consumes little additional memory. Memory leaks are usually identifiable by their memory usage signature. Leaks cause peak memory usage to increase monotonically with time regardless of script complexity. Slow leaks are very difficult to find. Sometimes a malloc() failure is the only noticeable clue to their existance. If you have good reasons to believe that a malloc() failure is ultimately due to an NCO memory leak (rather than inadequate RAM on your system), then we would be very interested in receiving a detailed bug report.
Many features have been implemented in more than one operator and are described here for brevity. The description of each feature is preceded by a box listing the operators for which the feature is implemented. Command line switches for a given feature are consistent across all operators wherever possible. If no “key switches” are listed for a feature, then that particular feature is automatic and cannot be controlled by the user.
|
Availability: All operators Short options: All Long options: All |
|
Availability: ncbo, ncea, ncpdq,
ncra, ncrcat, ncwa Short options: `-t' Long options: `--thr_nbr', `--threads', `--omp_num_threads' |
OMP_NUM_THREADS environment variable, if present, or from the
OS, if not.
NCO may modify thr_nbr according to its own internal
settings before it requests any threads from the system.
Certain operators contain hard-code limits to the number of threads they
request.
We base these limits on our experience and common sense, and to reduce
potentially wasteful system usage by inexperienced users.
For example, ncrcat is extremely I/O-intensive.
No one has demonstrated that threading improves ncrcat
performance so we restrict thr_nbr <= 1 for ncrcat.
Compute-intensive operators (ncwa and ncpdq)
are expected to benefit the most from threading.
The greatest increases in throughput due to threading will occur on
large dataset where each thread performs millions or more floating
point operations.
Otherwise, the system overhead of setting up threads may outweigh
the theoretical speed enhancements due to SMP parallelism.
However, no one has ever demonstrated that the SMP parallelism
scales well beyone four threads for these operators.
Hence we restrict thr_nbr <= 4 for all operators.
We encourage users to play with these limits (edit file
nco_omp.c) and send us their feedback.
Once the initial thr_nbr has been modified for any operator-specific limits, NCO requests the system to allocate a team of thr_nbr threads for the body of the code. The operating system then decides how many threads to allocate based on this request. Users may keep track of this information by running the operator with dbg_lvl > 0.
By default, operators with thread attach one global attribute to any
file they create or modify.
The nco_openmp_thread_number global attribute contains the
number of threads the operator used to process the input files.
This information helps to verify that the answers with threaded and
non-threaded operators are equal to within machine precision.
This information is also useful for benchmarking.
|
Availability: All operators Short options: All Long options: All |
|
Availability: All operators Short options: All Long options: All |
Extended options, also called long options, are implemented using the system-supplied getopt.h header file, if possible. This provides the getopt_long function to NCO 14.
The syntax of short options (single letter options) is -key value (dash-key-space-value). Here, key is the single letter option name, e.g., `-D 2'.
The syntax of long options (multi-letter options) is --long_name value (dash-dash-key-space-value), e.g., `--dbg_lvl 2' or --long_name=value (dash-dash-key-equal-value), e.g., `--dbg_lvl=2'. Thus the following are all valid for the `-D' (short version) or `--dbg_lvl' (long version) command line option.
ncks -D 3 in.nc # Short option
ncks --dbg_lvl=3 in.nc # Long option, preferred form
ncks --dbg_lvl 3 in.nc # Long option, alternate form
The last example is preferred for two reasons. First, `--dbg_lvl' is more specific and less ambiguous than `-D'. The long option form makes scripts more self documenting and less error prone. Often long options are named after the source code variable whose value they carry. Second, the equals sign = joins the key (i.e., long_name) to the value in an uninterruptible text block. Experience shows that users are less likely to mis-parse commands when restricted to this form.
GNU implements a superset of the POSIX standard which allows any unambiguous truncation of a valid option to be used.
ncks -D 3 in.nc # Short option
ncks --dbg_lvl=3 in.nc # Long option, full form
ncks --dbg=3 in.nc # Long option, unambiguous truncation
ncks --db=3 in.nc # Long option, unambiguous truncation
ncks --d=3 in.nc # Long option, ambiguous truncation
The first four examples are equivalent and will work as expected. The final example will exit with an error since ncks cannot disambiguate whether `--d' is intended as a truncation of `--dbg_lvl', of `--dimension', or of some other long option.
NCO provides many long options for common switches. For example, the debugging level may be set in all operators with any of the switches `-D', `--debug-level', or `--dbg_lvl'. This flexibility allows users to choose their favorite mnemonic. For some, it will be `--debug' (an unambiguous truncation of `--debug-level', and other will prefer `--dbg'. Interactive users usually prefer the minimal amount of typing, i.e., `-D'. We recommend that scripts which are re-usable employ some form of the long options for future maintainability.
This manual generally uses the short option syntax. This is for historical reasons and to conserve space. The remainder of this manual specifies the full long_name of each option. Users are expected to pick the unambiguous truncation of each option name that most suits their taste.
Availability (-n): ncea, ncecat, ncra, ncrcatAvailability ( -p): All operatorsShort options: `-n', `-p' Long options: `--nintap', `--pth', `--path' |
ncra 85.nc 86.nc 87.nc 88.nc 89.nc 8589.nc
ncra 8[56789].nc 8589.nc
ncra -p input-path 85.nc 86.nc 87.nc 88.nc 89.nc 8589.nc
ncra -n 5,2,1 85.nc 8589.nc
The first method (explicitly specifying all filenames) works by brute
force.
The second method relies on the operating system shell to glob
(expand) the regular expression 8[56789].nc.
The shell passes valid filenames which match the expansion to
ncra.
The third method uses the `-p input-path' argument to specify
the directory where all the input files reside.
NCO prepends input-path (e.g.,
/data/usrname/model) to all input-files (but not to
output-file).
Thus, using `-p', the path to any number of input files need only
be specified once.
Note input-path need not end with `/'; the `/' is
automatically generated if necessary.
The last method passes (with `-n') syntax concisely describing the entire set of filenames 15. This option is only available with the multi-file operators: ncra, ncrcat, ncea, and ncecat. By definition, multi-file operators are able to process an arbitrary number of input-files. This option is very useful for abbreviating lists of filenames representable as alphanumeric_prefix+numeric_suffix+.+filetype where alphanumeric_prefix is a string of arbitrary length and composition, numeric_suffix is a fixed width field of digits, and filetype is a standard filetype indicator. For example, in the file ccm3_h0001.nc, we have alphanumeric_prefix = ccm3_h, numeric_suffix = 0001, and filetype = nc.
NCO is able to decode lists of such filenames encoded using the
`-n' option.
The simpler (3-argument) `-n' usage takes the form
-n file_number,digit_number,numeric_increment
where file_number is the number of files, digit_number is
the fixed number of numeric digits comprising the numeric_suffix,
and numeric_increment is the constant, integer-valued difference
between the numeric_suffix of any two consecutive files.
The value of alphanumeric_prefix is taken from the input file,
which serves as a template for decoding the filenames.
In the example above, the encoding -n 5,2,1 along with the input
file name 85.nc tells NCO to
construct five (5) filenames identical to the template 85.nc
except that the final two (2) digits are a numeric suffix to be
incremented by one (1) for each successive file.
Currently filetype may be either be empty, nc,
cdf, hdf, or hd5.
If present, these filetype suffixes (and the preceding .)
are ignored by NCO as it uses the `-n' arguments to
locate, evaluate, and compute the numeric_suffix component of
filenames.
Recently the `-n' option has been extended to allow convenient
specification of filenames with “circular” characteristics.
This means it is now possible for NCO to automatically
generate filenames which increment regularly until a specified maximum
value, and then wrap back to begin again at a specified minimum value.
The corresponding `-n' usage becomes more complex, taking one or
two additional arguments for a total of four or five, respectively:
-n
file_number,digit_number,numeric_increment[,numeric_max[,numeric_min]]
where numeric_max, if present, is the maximum integer-value of
numeric_suffix and numeric_min, if present, is the minimum
integer-value of numeric_suffix.
Consider, for example, the problem of specifying non-consecutive input
files where the filename suffixes end with the month index.
In climate modeling it is common to create summertime and wintertime
averages which contain the averages of the months June–July–August,
and December–January–February, respectively:
ncra -n 3,2,1 85_06.nc 85_0608.nc
ncra -n 3,2,1,12 85_12.nc 85_1202.nc
ncra -n 3,2,1,12,1 85_12.nc 85_1202.nc
The first example shows that three arguments to the `-n' option
suffice to specify consecutive months (06, 07, 08) which do not
“wrap” back to a minimum value.
The second example shows how to use the optional fourth and fifth
elements of the `-n' option to specify a wrap value to NCO.
The fourth argument to `-n', if present, specifies the maximum
integer value of numeric_suffix.
In this case the maximum value is 12, and will be formatted as
12 in the filename string.
The fifth argument to `-n', if present, specifies the minimum
integer value of numeric_suffix.
The default minimum filename suffix is 1, which is formatted as
01 in this case.
Thus the second and third examples have the same effect, that is, they
automatically generate, in order, the filenames 85_12.nc,
85_01.nc, and 85_02.nc as input to NCO.
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Availability: All operators Short options: `-o' Long options: `--fl_out', `--output' |
Specifying fl_out with a switch, rather than as a positional argument, allows fl_out to precede input files in the argument list. This is particularly useful with multi-file operators for three reasons. Multi-file operators may be invoked with hundreds (or more) filenames. Visual or automatic location of fl_out in such a list is difficult when the only syntactic distinction between input and output files is their position. Second, specification of a long list of input files may be difficult (see Large numbers of input files). Making the input file list the final argument to an operator facilitates using xargs for this purpose. Some alternatives to xargs are very ugly and undesirable. Finally, many users are more comfortable specifying output files with `-o fl_out' near the beginning of an argument list. Compilers and linkers are usually invoked this way.
|
Availability: All operators Short options: `-p', `-l' Long options: `--pth', `--path', `--lcl', `--local' |
To access a file on NCAR's MSS, specify the full MSS pathname of the
remote file.
NCO will attempt to detect whether the local machine has direct
(synchronous) MSS access.
In this case, NCO attempts to use the NCAR
msrcp command
16, or, failing that, /usr/local/bin/msread.
Otherwise NCO attempts to retrieve the MSS file
through the (asynchronous) Masnet Interface Gateway System
(MIGS) using the nrnet command.
The following examples show how one might analyze files stored on remote systems.
ncks -l ./ ftp://dust.ess.uci.edu/pub/zender/nco/in.nc
ncks -l ./ dust.ess.uci.edu:/home/zender/nco/in.nc
ncks -l ./ /ZENDER/nco/in.nc
ncks -l ./ mss:/ZENDER/nco/in.nc
ncks -l ./ -p http://www.cdc.noaa.gov/cgi-bin/nph-nc/Datasets/\
ncep.reanalysis.dailyavgs/surface air.sig995.1975.nc
The first example will work verbatim on your system if your system is
connected to the Internet and is not behind a firewall.
The second example will work on your system if you have rcp
or scp access to the machine dust.ess.uci.edu.
The third example will work from NCAR computers with local
access to the msrcp, msread, or nrnet
commands.
The fourth command will work if your local version of NCO was
built with DODS/OPeNDAP capability (see DODS/OPeNDAP).
The above commands can be rewritten using the `-p input-path'
option as follows:
ncks -p ftp://dust.ess.uci.edu/pub/zender/nco -l ./ in.nc
ncks -p dust.ess.uci.edu:/home/zender/nco -l ./ in.nc
ncks -p /ZENDER/nco -l ./ in.nc
ncks -p mss:/ZENDER/nco -l ./ in.nc
Using `-p' is recommended because it clearly separates the input-path from the filename itself, sometimes called the stub. When input-path is not explicitly specified using `-p', NCO internally generates an input-path from the first input filename. The automatically generated input-path is constructed by stripping the input filename of everything following the final `/' character (i.e., removing the stub). The `-l output-path' option tells NCO where to store the remotely retrieved file and the output file. Often the path to a remotely retrieved file is quite different than the path on the local machine where you would like to store the file. If `-l' is not specified then NCO internally generates an output-path by simply setting output-path equal to input-path stripped of any machine names. If `-l' is not specified and the remote file resides on the NCAR MSS system, then the leading character of input-path, `/', is also stripped from output-path. Specifying output-path as `-l ./' tells NCO to store the remotely retrieved file and the output file in the current directory. Note that `-l .' is equivalent to `-l ./' though the latter is recommended as it is syntactically more clear.
The Distributed Oceanographic Data System (DODS) provides useful replacements for common data interface libraries like netCDF. The DODS versions of these libraries implement network transparent access to data via a client-server data access protocol that uses the HTTP protocol for communication. Although DODS-technology originated with oceanography data, it applyies to virtually all scientific data. In recognition of this, the data access protocol underlying DODS (which is what NCO cares about) has been renamed the Open-source Project for a Network Data Access Protocol, OPeNDAP. We use the terms DODS and OPeNDAP interchangeably, and often write DODS/OPeNDAP for now. In the future we will deprecate DODS in favor of OPeNDAP 17.
NCO may be DODS/OPeNDAP-enabled by linking
NCO to the DODS/OPeNDAP libraries.
This is described in the DODS/OPeNDAP documentation and
automagically implemented in NCO build mechanisms
18.
The ./configure mechanism automatically enables NCO as
DODS/OPeNDAP clients if it can find the required
DODS/OPeNDAP libraries
19.
in the usual locations.
The $DODS_ROOT environment variable may be used to override the
default DODS/OPeNDAP library location at NCO
compile-time.
Building NCO with bld/Makefile and the command
make DODS=Y adds the (non-intuitive) commands to link to the
DODS/OPeNDAP libraries installed in the $DODS_ROOT
directory.
The file doc/dods.sh contains a generic script intended to help
users install DODS/OPeNDAP before building NCO.
The documentation at the
DODS Homepage
is voluminous.
Check there and on the
DODS mail lists.
to learn more about the extensive capabilities of DODS/OPeNDAP
20.
Once NCO is DODS/OPeNDAP-enabled the operators are DODS/OPeNDAP clients. All DODS/OPeNDAP clients have network transparent access to any files controlled by a DODS/OPeNDAP server. Simply specify the input file path(s) in URL notation and all NCO operations may be performed on remote files made accessible by a DODS/OPeNDAP server. For example, this extracts (remotely) an equatorial hyperslab, from NCEP daily reanalyses data of the year 1969 made freely available by a NOAA DODS/OPeNDAP server. Then it sends the hyperslab to the local ncwa client which computes and stores (locally) the regional mean surface pressure (in Pa).
ncwa -O -C -a lat,lon,time -d lon,-10.,10. -d lat,-10.,10. -l ./ -p \
http://www.cdc.noaa.gov/cgi-bin/nph-nc/Datasets/ncep.reanalysis.dailyavgs/surface \
pres.sfc.1969.nc foo.nc
All with one command! The data in this particular input file also happen to be packed (see Intrinsic functions), although this is completely transparent to the user since NCO automatically unpacks them before attempting arithmetic.
NCO obtains remote files from the DODS/OPeNDAP server (e.g., www.cdc.noaa.gov) rather than the local machine. Input files are first copied to the local machine, then processed. The DODS/OPeNDAP server performs data access, hyperslabbing, and transfer to the local machine. This allows the I/O to appear to NCO as if the input files were local. The local machine performs all arithmetic operations. Only the hyperslabbed output data are transferred over the network (to the local machine) for the number-crunching to begin. The advantages of this are obvious if you are examining small parts of large files stored at remote locations.
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Availability: All operators Short options: `-R' Long options: `--rtn', `--retain' |
Note that the remote retrieval features of NCO can always be used to retrieve any file, including non-netCDF files, via SSH, anonymous FTP, or msrcp. Often this method is quicker than using a browser, or running an FTP session from a shell window yourself. For example, say you want to obtain a JPEG file from a weather server.
ncks -R -p ftp://weather.edu/pub/pix/jpeg -l ./ storm.jpg
In this example, ncks automatically performs an anonymous FTP login to the remote machine and retrieves the specified file. When ncks attempts to read the local copy of storm.jpg as a netCDF file, it fails and exits, leaving storm.jpg in the current directory.
If your NCO is DODS-enabled (see DODS/OPeNDAP), then you may use NCO to retrieve any files (including netCDF, HDF, etc.) served by a DODS server to your local machine. For example,
ncks -R -l ./ -p \
http://www.cdc.noaa.gov/cgi-bin/nph-nc/Datasets/ncep.reanalysis.dailyavgs/surface \
pres.sfc.1969.nc
Note that NCO is never the preffered way to transport files from remote machines. For large jobs, that is best handled by FTP, SSH, or wget. It may occasionally be useful to use NCO to transfer files when your other preferred methods are not available locally.
|
Availability: (ncap), ncbo, ncea,
ncecat, ncflint, ncks, ncpdq,
ncra, ncrcat, ncwa Short options: `-v', `-x' Long options: `--variable', `--exclude' or `--xcl' |
As of NCO 2.8.1 (August, 2003), variable name arguments of the `-v' switch may contain extended regular expressions. For example, `-v '^DST'' selects all variables beginning with the string `DST'. Extended regular expressions are defined by the GNU egrep command. The meta-characters used to express pattern matching operations are `^$+?.*[]{}|'. If the regular expression pattern matches any part of a variable name then that variable is selected. This capability is called wildcarding, and is very useful for sub-setting large data files.
Because of its wide availability, NCO uses the POSIX
regular expression library regex.
Regular expressions of arbitary complexity may be used.
Since netCDF variable names are relatively simple constructs, only a
few varieties of variable wildcards are likely to be useful.
For convenience, we define the most useful pattern matching operators
here:
Q, Q01–Q99,
Q100, QAA–QZZ, Q_H2O, X_H2O,
Q_CO2, X_CO2.
ncks -v 'Q+' in.nc # Select variables that start with Q
ncks -v '^Q+.?.' in.nc # Select Q, Q01--Q99, QAA--QZZ, etc.
ncks -v '^Q..' in.nc # Select Q01--Q99, QAA--QZZ, etc.
ncks -v '^Q[0-9][0-9]' in.nc # Select Q01--Q99
ncks -v '^Q[[:digit:]]{2}' in.nc # Select Q01--Q99
ncks -v 'H2O$' in.nc # Select Q_H2O, X_H2O
ncks -v 'H2O$|CO2$' in.nc # Select Q_H2O, X_H2O, Q_CO2, X_CO2
ncks -v '^Q[0-9][0-9]' in.nc # Select Q01--Q99, Q100
ncks -v '^Q[0-9][0-9]$' in.nc # Select Q01--Q99
ncks -v '^[a-z]_[a-z]{3}$' in.nc # Select Q_H2O, X_H2O, Q_CO2, X_CO2
Beware—two of the most frequently used repetition pattern matching operators, `*' and `?', are also valid pattern matching operators for filename expansion (globbing) at the shell-level. Confusingly, they have different meanings in extended regular expressions than in shell-level filename expansion. In an extended regular expression, `*' matches zero or more occurences of the preceding regular expression. Thus `Q*' selects all variables, and `Q+.*' selects all variables containing `Q' (the `+' ensures the preceding item matches at least once). To match zero or one occurence of the preceding regular expression, use `?'. Thus `Q?' selects all variables, `Q+.?' selects all Documentation for the UNIX egrep command details the extended regular expressions that NCO supports.
One must be careful to protect any special characters in the regular expression specification from being interpreted (globbed) by the shell. This is accomplish by enclosing special characters within single or double quotes
ncra -v Q?? in.nc out.nc # Error: Shell attempts to glob wildcards
ncra -v '^Q+..' in.nc out.nc # Correct: NCO interprets wildcards
ncra -v '^Q+..' in*.nc out.nc
The final example shows that commands may use a combination of variable wildcarding and shell filename expansion (globbing). For globbing, `*' and `?' have nothing to do with the preceding regular expression! In shell-level filename expansion, `*' matches any string, including the null string and `?' matches any single character. Documentation for bash and csh describe the rules of filename expansion (globbing).
|
Availability: ncap, ncbo, ncea,
ncecat, ncflint, ncks, ncpdq,
ncra, ncrcat, ncwa Short options: `-C', `-c' Long options: `--no-coords', `--no-crd', `--crd', `--coords' |
lat always carry the
values of lat with them into the output-file.
This feature can be disabled with `-C', which causes NCO
to not automatically add coordinates to the variables appearing in the
output-file.
However, using `-C' does not preclude the user from including some
coordinates in the output files simply by explicitly selecting the
coordinates with the -v option.
The `-c' option, on the other hand, is a shorthand way of
automatically specifying that all coordinate variables in the
input-files should appear in the output-file.
Thus `-c' allows the user to select all the coordinate variables
without having to know their names.
|
Availability: ncbo, ncea, ncecat,
ncflint, ncks, ncpdq, ncra,
ncrcat, ncwa Short options: `-F' Long options: `--fortran' |
Consider a file 85.nc containing 12 months of data in the
record dimension time.
The following hyperslab operations produce identical results, a
June-July-August average of the data:
ncra -d time,5,7 85.nc 85_JJA.nc
ncra -F -d time,6,8 85.nc 85_JJA.nc
Printing variable three_dmn_var in file in.nc first with C indexing conventions, then with Fortran indexing conventions results in the following output formats:
% ncks -v three_dmn_var in.nc
lat[0]=-90 lev[0]=1000 lon[0]=-180 three_dmn_var[0]=0
...
% ncks -F -v three_dmn_var in.nc
lon(1)=0 lev(1)=100 lat(1)=-90 three_dmn_var(1)=0
...
|
Availability: ncbo, ncea, ncecat,
ncflint, ncks, ncpdq, ncra,
ncrcat, ncwa Short options: `-d' Long options: `--dimension', `--dmn' |
-d
dim,[min][,[max]] short option (or with the
`--dimension' or `--dmn' long options).
The bounds of the hyperslab to be extracted are specified by the
associated min and max values.
A half-open range is specified by omitting either the min or
max parameter but including the separating comma.
The unspecified limit is interpreted as the maximum or minimum value in
the unspecified direction.
A cross-section at a specific coordinate is extracted by specifying only
the min limit and omitting a trailing comma.
Dimensions not mentioned are passed with no reduction in range.
The dimensionality of variables is not reduced (in the case of a
cross-section, the size of the constant dimension will be one).
If values of a coordinate-variable are used to specify a range or
cross-section, then the coordinate variable must be monotonic (values
either increasing or decreasing).
In this case, command-line values need not exactly match coordinate
values for the specified dimension.
Ranges are determined by seeking the first coordinate value to occur in
the closed range [min,max] and including all subsequent
values until one falls outside the range.
The coordinate value for a cross-section is the coordinate-variable
value closest to the specified value and must lie within the range or
coordinate-variable values.
Coordinate values should be specified using real notation with a decimal point required in the value, whereas dimension indices are specified using integer notation without a decimal point. This convention serves only to differentiate coordinate values from dimension indices. It is independent of the type of any netCDF coordinate variables. For a given dimension, the specified limits must both be coordinate values (with decimal points) or dimension indices (no decimal points).
User-specified coordinate limits are promoted to double precision values
while searching for the indices which bracket the range.
Thus, hyperslabs on coordinates of type NC_BYTE and
NC_CHAR are computed numerically rather than lexically, so the
results are unpredictable.
The relative magnitude of min and max indicate to the operator whether to expect a wrapped coordinate (see Wrapped coordinates), such as longitude. If min > max, the NCO expects the coordinate to be wrapped, and a warning message will be printed. When this occurs, NCO selects all values outside the domain [max < min], i.e., all the values exclusive of the values which would have been selected if min and max were swapped. If this seems confusing, test your command on just the coordinate variables with ncks, and then examine the output to ensure NCO selected the hyperslab you expected (coordinate wrapping is currently only supported by ncks).
Because of the way wrapped coordinates are interpreted, it is very
important to make sure you always specify hyperslabs in the
monotonically increasing sense, i.e., min < max
(even if the underlying coordinate variable is monotonically
decreasing).
The only exception to this is when you are indeed specifying a wrapped
coordinate.
The distinction is crucial to understand because the points selected by,
e.g., -d longitude,50.,340., are exactly the complement of the
points selected by -d longitude,340.,50..
Not specifying any hyperslab option is equivalent to specifying full
ranges of all dimensions.
This option may be specified more than once in a single command
(each hyperslabed dimension requires its own -d option).
|
Availability: ncks Short options: `-d' Long options: `--dimension', `--dmn' |
A single -d option can only specify a contiguous and/or regularly spaced multi-dimensional array of data. Multislabs are constructed from multiple -d options and may therefore have non-regularly spaced arrays. For example, suppose it is desired to operate on all longitudes from 10.0 to 20.0 and from 80.0 to 90.0 degrees. The combined range of longitudes is not selectable in a single hyperslab specfication of the form `-d lon,min,max' or `-d lon,min,max,stride' because its elements are irregularly spaced in coordinate space (and presumably in index space too). The multislab specification for obtaining these values is simply the union of the hyperslabs specifications that comprise the multislab, i.e.,
ncks -d lon,10.,20. -d lon,80.,90. in.nc out.nc
ncks -d lon,10.,15. -d lon,15.,20. -d lon,80.,90. in.nc out.nc
Any number of hyperslabs specifications may be chained together to specify the multislab. Multislabs are more efficient than the alternative of sequentially performing hyperslab operations and concatenating the results. This is because NCO employs a novel multislab algorithm to minimize the number of I/O operations when retrieving irregularly spaced data from disk.
Users may specify redundant ranges of indices in a multislab, e.g.,
ncks -d lon,0,4 -d lon,2,9,2 in.nc out.nc
This command retrieves the first five longitudes, and then every other longitude value up to the tenth. Elements 0, 2, and 4 are specified by both hyperslab arguments (hence this is redundant) but will count only once if an arithmetic operation is being performed. The NCO multislab algorithm retrieves each element from disk once and only once. Thus users may take some shortcuts in specifying multislabs and the algorithm will obtain the intended values. Specifying redundant ranges is not encouraged, but may be useful on occasion and will not result in unintended consequences.
A final example shows the real power of multislabs. Suppose the Q variable contains three dimensional arrays of distinct chemical constituents in no particular order. We are interested in the NOy species in a certain geographic range. Say that NO, NO2, and N2O5 are elements 0, 1, and 5 of the species dimension of Q. The multislab specification might look something like
ncks -d species,0,1 -d species,5 -d lon,0,4 -d lon,2,9,2 in.nc out.nc
Multislabs are powerful because they may be specified for every dimension at the same time. Thus multislabs obsolete the need to execute multiple ncks commands to gather the desired range of data. We envision adding multislab support to all arithmetic operators in the future.
|
Availability: ncbo, ncea, ncecat,
ncflint, ncks, ncpdq, ncra,
ncrcat, ncwa Short options: `-d' Long options: `--dimension', `--dmn' |
Two examples suffice to demonstrate the power and convenience of UDUnits support. First, consider extraction of a variable containing non-record coordinates with physical dimensions stored in MKS units. In the following example, the user extracts all wavelengths in the visible portion of the spectrum in terms of the units very frequently used in visible spectroscopy, microns:
% ncks -O -C -u -v wvl -d wvl,"0.4 micron","0.7 micron" in.nc
wvl[0]=5e-07 meter
The hyperslab returns the correct values because the wvl variable
is stored on disk with a length dimension that UDUnits recognizes in the
units attribute.
The automagical algorithm that implements this functionality is worth
describing since understanding it helps one avoid some potential
pitfalls.
First, the user includes the physical units of the hyperslab dimensions
she supplies, separated by a simple space from the numerical values of
the hyperslab limits.
She encloses each coordinate specifications in quotes so that the shell
does not break the value-space-unit string into separate
arguments before passing them to NCO.
Double quotes ("foo") or single quotes ('foo') are equally
valid for this purpose.
Second, NCO recognizes that units translation is requested
because each hyperslab argument contains text characters and non-initial
spaces.
Third, NCO determines whether the wvl is dimensioned
with a coordinate variable that has a units attribute.
In this case, wvl itself is a coordinate variable.
The value of its units attribute is meter.
Thus wvl passes this test so UDUnits conversion is attempted.
If the coordinate associated with the variable does not contain a
units attribute, then NCO aborts.
Fourth, NCO passes the specified and desired dimension strings
(microns are specified by the user, meters are required by
NCO) to the UDUnits library.
Fifth, the UDUnits library that these dimension are commensurate
and it returns the appropriate linear scaling factors to convert from
microns to meters to NCO.
If the units are incommensurate (i.e., not expressible in the same
fundamental MKS units), or are not listed in the UDUnits database, then
NCO aborts since it cannot determine the user's intent.
Finally, NCO uses the scaling information to convert the
user-specified hyperslab limits into the same physical dimensions as
those of the corresponding cooridinate variable on disk.
At this point, NCO can perform a coordinate hyperslab using
the same algorithm as if the user had specified the hyperslab without
requesting units conversion.
The translation and dimennterpretation of time coordinates shows a more powerful, and probably more common, application of the UDUnits feature. In this example, the user prints all data between the eighth and ninth of December, 1999, from a variable whose time dimension is hours since the year 1900:
% ncks -O -C -u -v time_udunits -d time_udunits,"1999-12-08 \
12:00:0.0","1999-12-09 00:00:0.0",2 in.nc foo2.nc
% time_udunits[1]=876018 hours since 1900-01-01 00:00:0.0
Here, the user invokes the stride (see Stride) capability to obtain every other timeslice. This is possible because the UDUnits feature is additive, not exclusive—it works in conjunction with all other hyperslabbing (see Hyperslabs) options and in all operators which support hyperslabbing. The following example shows how one might average data in a time period spread across multiple input files
ncra -O -d time,"1939-09-09 12:00:0.0","1945-05-08 00:00:0.0" \
in1.nc in2.nc in3.nc out.nc
Note that there is no excess whitespace before or after the individual
elements of the `-d' argument.
This is important since, as far as the shell knows, `-d' takes
only one command-line argument.
Parsing this argument into its component
dim,[min],[max],stride elements
(see Hyperslabs) is the job of NCO.
When unquoted whitespace is present between these elements, the shell
passes NCO arugment fragments which will not parse as
intended.
The UDUnits package documentation describes the supported formats of time dimensions. Among the metadata conventions which adhere to these formats are the Climate and Forecast (CF) Conventions and the Cooperative Ocean/Atmosphere Research Data Service (COARDS) Conventions. The following `-d arguments' extract the same data using commonly encountered time dimension formats:
-d time,"1918-11-11 11:00:0.0","1939-09-09 00:00:0.0"
All of these formats include at least one dash - in a non-leading character position (a dash in a leading character position is a negative sign). NCO assumes that a non-leading dash in a limit string indicates that a UDUnits date conversion is requested.
netCDF variables should always be stored with MKS (i.e., God's) units, so that application programs may assume MKS dimensions apply to all input variables. The UDUnits feature is intended to alleviate some of the NCO user's pain when handling MKS units. It connects users who think in human-friendly units (e.g., miles, millibars, days) to extract data which are always stored in God's units, MKS (e.g., meters, Pascals, seconds). The feature is not intended to encourage writers to store data in esoteric units (e.g., furlongs, pounds per square inch, fortnights).
|
Availability: ncks Short options: `-d' Long options: `--dimension', `--dmn' |
Assume the domain of the monotonically increasing longitude coordinate
lon is 0 < lon < 360.
ncks will extract a hyperslab which crosses the Greenwich
meridian simply by specifying the westernmost longitude as min and
the easternmost longitude as max.
The following commands extract a hyperslab containing the Saharan desert:
ncks -d lon,340.,50. in.nc out.nc
ncks -d lon,340.,50. -d lat,10.,35. in.nc out.nc
The first example selects data in the same longitude range as the Sahara.
The second example further constrains the data to having the same
latitude as the Sahara.
The coordinate lon in the output-file, out.nc, will
no longer be monotonic!
The values of lon will be, e.g., `340, 350, 0, 10, 20, 30,
40, 50'.
This can have serious implications should you run out.nc through
another operation which expects the lon coordinate to be
monotonically increasing.
Fortunately, the chances of this happening are slim, since lon
has already been hyperslabbed, there should be no reason to hyperslab
lon again.
Should you need to hyperslab lon again, be sure to give
dimensional indices as the hyperslab arguments, rather than coordinate
values (see Hyperslabs).
|
Availability: ncks, ncra, ncrcat Short options: `-d' Long options: `--dimension', `--dmn' |
The stride is specified as the optional fourth argument to the
`-d' hyperslab specification:
-d dim,[min][,[max]][,[stride]].
Specify stride as an integer (i.e., no decimal point) following
the third comma in the `-d' argument.
There is no default value for stride.
Thus using `-d time,,,2' is valid but `-d time,,,2.0' and
`-d time,,,' are not.
When stride is specified but min is not, there is an
ambiguity as to whether the extracted hyperslab should begin with (using
C-style, 0-based indexes) element 0 or element `stride-1'.
NCO must resolve this ambiguity and it chooses element 0
as the first element of the hyperslab when min is not specified.
Thus `-d time,,,stride' is syntactically equivalent to
`-d time,0,,stride'.
This means, for example, that specifying the operation
`-d time,,,2' on the array `1,2,3,4,5' selects the hyperslab
`1,3,5'.
To obtain the hyperslab `2,4' instead, simply explicitly specify
the starting index as 1, i.e., `-d time,1,,2'.
For example, consider a file 8501_8912.nc which contains 60 consecutive months of data. Say you wish to obtain just the March data from this file. Using 0-based subscripts (see Fortran indexing) these data are stored in records 2, 14, ... 50 so the desired stride is 12. Without the stride option, the procedure is very awkward. One could use ncks five times and then use ncrcat to concatenate the resulting files together:
for idx in 02 14 26 38 50; do # Bourne Shell
ncks -d time,${idx} 8501_8912.nc foo.${idx}
done
foreach idx (02 14 26 38 50) # C Shell
ncks -d time,${idx} 8501_8912.nc foo.${idx}
end
ncrcat foo.?? 8589_03.nc
rm foo.??
With the stride option, ncks performs this hyperslab extraction in one operation:
ncks -d time,2,,12 8501_8912.nc 8589_03.nc
See ncks netCDF Kitchen Sink, for more information on ncks.
The stride option is supported by ncra and ncrcat for the record dimension only. This makes it possible, for instance, to average or concatenate regular intervals across multi-file input data sets.
ncra -F -d time,3,,12 85.nc 86.nc 87.nc 88.nc 89.nc 8589_03.nc
ncrcat -F -d time,3,,12 85.nc 86.nc 87.nc 88.nc 89.nc 8503_8903.nc
|
Availability: ncap, ncbo, ncea,
ncflint, ncpdq, ncra, ncwa Short options: None |
The phrase missing data refers to data points that are missing, invalid, or for any reason not intended to be arithmetically processed in the same fashion as valid data. The NCO arithmetic operators attempt to handle missing data in an intelligent fashion. There are four steps in the NCO treatment of missing data:
NCO follows the convention that missing data should be stored
with the missing_value specified in the variable's
missing_value attribute.
The only way NCO recognizes that a variable may
contain missing data is if the variable has a missing_value
attribute.
In this case, any elements of the variable which are numerically equal
to the missing_value are treated as missing data.
Consider a variable var of type var_type with a
missing_value attribute of type att_type containing the
value missing_value.
As a guideline, the type of the missing_value attribute should be
the same as the type of the variable it is attached to.
If var_type equals att_type then NCO
straightforwardly compares each value of var to
missing_value to determine which elements of var are to be
treated as missing data.
If not, then NCO converts missing_value from
att_type to var_type by using the implicit conversion rules
of C, or, if att_type is NC_CHAR
21, by typecasting the results of the C function
strtod(missing_value).
You may use the NCO operator ncatted to change the
missing_value attribute and all data whose data is
missing_value to a new value
(see ncatted netCDF Attribute Editor).
When an NCO arithmetic operator processes a variable var
with a missing_value attribute, it compares each value of
var to missing_value before performing an operation.
Note the missing_value comparison inflicts a performance penalty
on the operator.
Arithmetic processing of variables which contain the
missing_value attribute always incurs this penalty, even when
none of the data are missing.
Conversely, arithmetic processing of variables which do not contain the
missing_value attribute never incurs this penalty.
In other words, do not attach a missing_value attribute to a
variable which does not contain missing data.
This exhortation can usually be obeyed for model generated data, but it
may be harder to know in advance whether all observational data will be
valid or not.
NCO averagers (ncra, ncea, ncwa) do not count any element with the value missing_value towards the average. ncbo and ncflint define a missing_value result when either of the input values is a missing_value. Sometimes the missing_value may change from file to file in a multi-file operator, e.g., ncra. NCO is written to account for this (it always compares a variable to the missing_value assigned to that variable in the current file). Suffice it to say that, in all known cases, NCO does “the right thing”.
It is impossible to determine and store the correct result of a binary operation in a single variable. One such corner case occurs when both operands have differing missing_value attributes, i.e., attributes with different numerical values. Since the output (result) of the operation can only have one missing_value, some information may be lost. In this case, NCO always defines the output variable to have the same missing_value as the first input variable. Prior to performing the arithmetic operation, all values of the second operand equal to the second missing_value are replaced with the first missing_value. Then the arithmetic operation proceeds as normal, comparing each element of each operand to a single missing_value. Comparing each element to two distinct missing_value's would be much slower and would be no likelier to yield a more satisfactory answer. In practice, judicious choice of missing_value values prevents any important information from being lost.
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Availability: ncra, ncea, ncwa Short options: `-y' Long options: `--operation', `--op_typ' |
avgsqravgavgsqrmaxminrmsrmssdnsqrtttl|
Note for HTML users:
|
The definitions of some of these operations are not universally useful. Mostly they were chosen to facilitate standard statistical computations within the NCO framework. We are open to redefining and or adding to the above. If you are interested in having other statistical quantities defined in NCO please contact the NCO project (see Help and Bug reports).
EXAMPLES
Suppose you wish to examine the variable prs_sfc(time,lat,lon)
which contains a time series of the surface pressure as a function of
latitude and longitude.
Find the minimium value of prs_sfc over all dimensions:
ncwa -y min -v prs_sfc in.nc foo.nc
Find the maximum value of prs_sfc at each time interval for each
latitude:
ncwa -y max -v prs_sfc -a lon in.nc foo.nc
Find the root-mean-square value of the time-series of prs_sfc at
every gridpoint:
ncra -y rms -v prs_sfc in.nc foo.nc
ncwa -y rms -v prs_sfc -a time in.nc foo.nc
The previous two commands give the same answer but ncra is
preferred because it has a smaller memory footprint.
Also, ncra leaves the (degenerate) time dimension in the
output file (which is usually useful) whereas ncwa removes the
time dimension.
These operations work as expected in multi-file operators.
Suppose that prs_sfc is stored in multiple timesteps per file
across multiple files, say jan.nc, feb.nc,
march.nc.
We can now find the three month maximium surface pressure at every point.
ncea -y max -v prs_sfc jan.nc feb.nc march.nc out.nc
It is possible to use a combination of these operations to compute the variance and standard deviation of a field stored in a single file or across multiple files. The procedure to compute the temporal standard deviation of the surface pressure at all points in a single file in.nc involves three steps.
ncwa -O -v prs_sfc -a time in.nc out.nc
ncbo -O --op_typ=sub -v prs_sfc in.nc out.nc out.nc
ncra -O -y rmssdn out.nc out.nc
First the output file out.nc is contructed containing the
temporal mean of prs_sfc.
Next out.nc is overwritten with the deviation from the mean.
Finally out.nc is overwritten with the root-mean-square of
itself.
Note the use of `-y rmssdn' (rather than `-y rms') in the
final step.
This ensures the standard deviation is correctly normalized by one fewer
than the number of time samples.
The procedure to compute the variance is identical except for the use of
`-y var' instead of `-y rmssdn' in the final step.
The procedure to compute the spatial standard deviation of a field in a single file in.nc involves three steps.
ncwa -O -v prs_sfc,gw -a lat,lon -w gw in.nc out.nc
ncbo -O --op_typ=sub -v prs_sfc,gw in.nc out.nc out.nc
ncwa -O -y rmssdn -v prs_sfc -a lat,lon -w gw out.nc out.nc
First the appropriately weighted (with `-w gw') spatial mean values are written to the output file. This example includes the use of a weighted variable specified with `-w gw'. When using weights to compute standard deviations one must remember to include the weights in the initial output files so that they may be used again in the final step. The initial output file is then overwritten with the gridpoint deviations from the spatial mean. Finally the root-mean-square of the appropriately weighted spatial deviations is taken.
The procedure to compute the standard deviation of a time-series across multiple files involves one extra step since all the input must first be collected into one file.
ncrcat -O -v tpt in.nc in.nc foo1.nc
ncwa -O -a time foo1.nc foo2.nc
ncbo -O --op_typ=sub -v tpt foo1.nc foo2.nc foo2.nc
ncra -O -y rmssdn foo2.nc out.nc
The first step assembles all the data into a single file. This may require a lot of temporary disk space, but is more or less required by the ncbo operation in the third step.
|
Availability: ncap, ncbo, ncea,
ncra, ncwa Short options: None |
NC_SHORT (two bytes) to NC_DOUBLE (eight bytes).
Type conversion is automatic when the language carries out this
promotion according to an internal set of rules without explicit user
intervention.
In contrast, manual type conversion refers to explicit user commands to
change the type of a variable or attribute.
Most type conversion happens automatically, yet there are situations in
which manual type conversion is advantageous.
As a general rule, automatic type conversions should be avoided for at
least two reasons.
First, type conversions are expensive since they require creating
(temporary) buffers and casting each element of a variable from
the type it was stored at to some other type.
Second, the dataset's creator probably had a good reason
for storing data as, say, NC_FLOAT rather than NC_DOUBLE.
In a scientific framework there is no reason to store data with more
precision than the observations were made.
Thus NCO tries to avoid performing automatic type conversions
when performing arithmetic.
Automatic type conversion during arithmetic in the languages C and
Fortran is performed only when necessary.
All operands in an operation are converted to the most precise type
before the operation takes place.
However, following this parsimonious conversion rule dogmatically
results in numerous headaches.
For example, the average of the two NC_SHORTs 17000s and
17000s results in garbage since the intermediate value which
holds their sum is also of type NC_SHORT and thus cannot
represent values greater than 32,767
22.
There are valid reasons for expecting this operation to succeed and
the NCO philosophy is to make operators do what you want, not
what is most pure.
Thus, unlike C and Fortran, but like many other higher level interpreted
languages, NCO arithmetic operators will perform automatic type
conversion when all the following conditions are met
23:
NC_BYTE, NC_CHAR,
NC_SHORT, or NC_INT.
Type NC_DOUBLE is not type converted because there is no type of
higher precision to convert to.
Type NC_FLOAT is not type converted because, in our judgement,
the performance penalty of always doing so would outweigh the (extremely
rare) potential benefits.
When these criteria are all met, the operator promotes the variable in
question to type NC_DOUBLE, performs all the arithmetic
operations, casts the NC_DOUBLE type back to the original type,
and finally writes the result to disk.
The result written to disk may not be what you expect, because of
incommensurate ranges represented by different types, and because of
(lack of) rounding.
First, continuing the above example, the average (e.g., `-y avg')
of 17000s and 17000s is written to disk as 17000s.
The type conversion feature of NCO makes this possible since
the arithmetic and intermediate values are stored as NC_DOUBLEs,
i.e., 34000.0d and only the final result must be represented
as an NC_SHORT.
Without the type conversion feature of NCO, the average would
have been garbage (albeit predictable garbage near -15768s).
Similarly, the total (e.g., `-y ttl') of 17000s and
17000s written to disk is garbage (actually -31536s) since
the final result (the true total) of 34000 is outside the range
of type NC_SHORT.
Type conversions use the floor function to convert floating point
number to integers.
Type conversions do not attempt to round floating point numbers to the
nearest integer.
Thus the average of 1s and 2s is computed in double
precisions arithmetic as
(1.0d + 1.5d)/2) = 1.5d.
This result is converted to NC_SHORT and stored on disk as
floor(1.5d) = 1s
24.
Thus no "rounding up" is performed.
The type conversion rules of C can be stated as follows:
If n is an integer then any floating point value x
satisfying
n <= x < n+1
will have the value n when converted to an integer.
ncap provides intrinsic functions for performing manual type
conversions.
This, for example, converts variable tpt to external type
NC_SHORT (a C-type short), and variable prs to
external type NC_DOUBLE (a C-type double).
ncap -O -s "tpt=short(tpt);prs=double(prs);" in.nc out.nc
See ncap netCDF Arithmetic Processor, for more details.
|
Availability: All operators Short options: `-O', `-A' Long options: `--ovr', `--overwrite', `--apn', `--append' |
|
Availability: All operators Short options: `-h' Long options: `--hst', `--history' |
history global attribute to
any file they create or modify.
The history attribute consists of a timestamp and the full string
of the invocation command to the operator, e.g., `Mon May 26 20:10:24
1997: ncks in.nc foo.nc'.
The full contents of an existing history attribute are copied
from the first input-file to the output-file.
The timestamps appear in reverse chronological order, with the most
recent timestamp appearing first in the history attribute.
Since NCO and many other netCDF operators adhere to the
history convention, the entire data processing path of a given
netCDF file may often be deduced from examination of its history
attribute.
As of May, 2002, NCO is case-insensitive to the spelling
of the history attribute name.
Thus attributes named History or HISTORY (which are
non-standard and not recommended) will be treated as valid history
attributes.
When more than one global attribute fits the case-insensitive search
for "history", the first one found will be used.
history attribute
To avoid information overkill, all operators have an optional switch
(`-h', `--hst', or `--history') to override
automatically appending the history attribute
(see ncatted netCDF Attribute Editor).
Note that the `-h' switch also turns off writing the
nco_input_file_list attribute for multi-file operators
(see Input file list attributes).
|
Availability: ncea, ncecat, ncra, ncrcat Short options: `-H' Long options: `--fl_lst_in', `--file_list' |
history
attribute no longer contains the exact command by which the file
was created.
NCO solves this dilemma by archiving input file list
attributes.
When the input file list to a multi-file operator is specified
via stdin, the operator, by default, attaches two global
attributes to any file they create or modify.
The nco_input_file_number global attribute contains the number of
input files, and nco_input_file_list contains the file names,
specified as standard input to the multi-file operator.
This information helps to verify that all input files the user thinks
were piped through stdin actually arrived.
Without the nco_input_file_list attribute, the information is lost
forever and the “chain of evidence” would be broken.
The `-H' switch overrides (turns off) the default behavior of
writing the input file list global attributes when input is from
stdin.
The `-h' switch does this too, and turns off the history
attribute as well (see History attribute).
Hence both switches allows space-conscious users to avoid storing what
may amount to many thousands of filenames in a metadata attribute.
|
Availability: ncbo, ncea, ncecat,
ncflint, ncra, ncwa Short options: None |
Currently, NCO determines whether a datafile is a
CCSM output datafile simply by checking whether value of the
global attribute convention (if it exists) equals
`NCAR-CSM'.
Should convention equal `NCAR-CSM' in the (first)
input-file, NCO will attempt to treat certain variables
specially, because of their meaning in CCSM files.
NCO will not average the following variables often found in
CCSM files:
ntrm, ntrn, ntrk, ndbase, nsbase,
nbdate, nbsec, mdt, mhisf.
These variables contain scalar metadata such as the resolution of the
host CCSM model and it makes no sense to change their values.
Furthermore, the ncbo operator does not operate on (i.e., add,
subtract, etc.) the following variables:
gw, ORO, date, datesec, hyam,
hybm, hyai, hybi.
These variables represent the Gaussian weights, the orography field,
time fields, and hybrid pressure coefficients.
These are fields which you virtually always want to remain unaltered in
the output file.
If you decide you would like any of the above CCSM fields
processed, you must spoof NCO.
For example rename the variables first with ncrename,
or alter the convention attribute.
|
Availability: ncrcat Short options: None |
base_time, and a record variable, time_offset.
Subtle but serious problems can arise when these type of files are
just blindly concatenated.
Therefore ncrcat has been specially programmed to be able to
chain together consecutive ARM input-files and produce
and an output-file which contains the correct time information.
Currently, ncrcat determines whether a datafile is an
ARM datafile simply by testing for the existence of the
variables base_time, time_offset, and the dimension
time.
If these are found in the input-file then ncrcat will
automatically perform two non-standard, but hopefully useful,
procedures.
First, ncrcat will ensure that values of time_offset
appearing in the output-file are relative to the base_time
appearing in the first input-file (and presumably, though not
necessarily, also appearing in the output-file).
Second, if a coordinate variable named time is not found in the
input-files, then ncrcat automatically creates the
time coordinate in the output-file.
The values of time are defined by the ARM convention
time = base_time + time_offset.
Thus, if output-file contains the time_offset
variable, it will also contain the time coordinate.
A short message is added to the history global attribute
whenever these ARM-specific procedures are executed.
|
Availability: All operators Short options: `-r' Long options: `--revision', `--version', or `--vrs' |
1.2.
However using `-r' on, say, ncks, will produce something
like `NCO netCDF Operators version 1.2
Copyright (C) 1995--2000 Charlie Zender
ncks version 1.30 (2000/07/31) "Bolivia"'.
This tells you ncks contains all patches up to version
1.30, which dates from July 31, 2000.
This chapter presents reference pages for each of the operators individually. The operators are presented in alphabetical order. All valid command line switches are included in the syntax statement. Recall that descriptions of many of these command line switches are provided only in Common features, to avoid redundancy. Only options specific to, or most useful with, a particular operator are described in any detail in the sections below.
ncap [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]][,[stride]]] [-F] [-f]
[-l path] [-O] [-o output-file] [-p path] [-R] [-r]
[-s algebra] [-S fl.nco] [-v]
input-file [output-file]
DESCRIPTION
ncap arithmetically processes a netCDF file. The processing instructions are contained either in the NCO script file fl.nco or in a sequence of command line arguments. The options `-s' (or long options `--spt' or `--script') are used for in-line scripts and `-S' (or long options `--fl_spt' or `--script-file') are used to provide the filename where (usually multiple) scripting commands are pre-stored. ncap was written to perform arbitrary albebraic transformations of data and archive the results as easily as possible. See Missing values, for treatment of missing values. The results of the algebraic manipulations are called derived fields.
Unlike the other operators, ncap does not accept a list of variables to be operated on as an argument to `-v' (see Variable subsetting). Rather, the `-v' switch takes no arguments and indicates that ncap should output only user-defined variables. ncap does not accept or understand the -x switch.
The following examples demonstrate the utility of the left hand casting ability of ncap. Consider first this simple, artificial, example. If lat and lon are one dimensional coordinates of dimensions lat and lon, respectively, then addition of these two one-dimensional arrays is intrinsically ill-defined because whether lat_lon should be dimensioned lat by lon or lon by lat is ambiguous (assuming that addition is to remain a commutative procedure, i.e., one that does not depend on the order of its arguments). Differing dimensions are said to be orthogonal to one another, and sets of dimensions which are mutually exclusive are orthogonal as a set and any arithmetic operation between variables in orthogonal dimensional spaces is ambiguous without further information.
The ambiguity may be resolved by enumerating the desired dimension ordering of the output expression inside square brackets on the left hand side (LHS) of the equals sign. This is called left hand casting because the user resolves the dimensional ordering of the RHS of the expression by specifying the desired ordering on the LHS.
ncap -O -s "lat_lon[lat,lon]=lat+lon" in.nc out.nc
ncap -O -s "lon_lat[lon,lat]=lat+lon" in.nc out.nc
The explicit list of dimensions on the LHS, [lat,lon]
resolves the otherwise ambiguous ordering of dimensions in
lat_lon.
In effect, the LHS casts its rank properties onto the
RHS.
Without LHS casting, the dimensional ordering of lat_lon
would be undefined and, hopefully, ncap would print an error
message.
Consider now a slightly more complex example.
In geophysical models, a coordinate system based on
a blend of terrain-following and density-following surfaces is
called a hybrid coordinate system.
In this coordinate system, four variables must be manipulated to
obtain the pressure of the vertical coordinate:
PO is the domain-mean surface pressure offset (a scalar),
PS is the local (time-varying) surface pressure (usually two
horizontal spatial dimensions, i.e, latitude by longitude), hyam
is the weight given to surfaces of constant density (one spatial
dimension, pressure, which is orthogonal to the horizontal
dimensions), and hybm is the weight given to surfaces of
constant elevation (also one spatial dimension).
This command constructs a four-dimensional pressure prs_mdp
from the four input variables of mixed rank and orthogonality:
ncap -O -s "prs_mdp[time,lat,lon,lev]=P0*hyam+PS*hybm" in.nc out.nc
Manipulating the four fields which define the pressure in a hybrid coordinate system is easy with left hand casting.
Mastering ncap is relatively simple. Each valid statement statement consists of standard forward algebraic expression. The fl.nco, if present, is simply a list of such statements, whitespace, and comments. The syntax of statements is most like the computer language C. The following characteristics of C are preserved:
[] characters;
/* */ characters.
Single line comments are preceded by // characters.
#include script.
Note that the #include command is not followed by a semi-colon
because it is a pre-processor directive, not an assignment statement.
The filename script is interpreted relative to the run directory.
@ is used to delineate an attribute name from a
variable name.
ncap contains a small (and growing) library of intrinsic functions. In addition to the standard mathematical functions (see Intrinsic mathematical functions), ncap currently supports packing and unpacking.
pack(x)NC_SHORT
with the two attributes required to unpack the variable,
scale_factor and add_offset, stored at the original
(unpacked) precision of the variable
27.
Let min and max be the minimum and maximum values
of x.
scale_factor = (max-min)/ndrv
where ndrv is the number of discrete representable values for
given type of packed variable.
The theoretical maximum value for ndrv is two raised to the
number of bits used to store the packed variable.
Thus if the variable is packed into type NC_SHORT, a two-byte
datatype, then there are at most 2^16 = 65536 distinct values
representible.
In practice, the number of discretely representible values is taken
to be one less than the theoretical maximum.
This leaves extra space and solves potential problems with rounding
which can occur during the unpacking of the variable.
Thus for NC_SHORT, ndrv = 65536 - 1 = 65535.
Less often, the variable may be packed into type NC_CHAR,
where ndrv = 256 - 1 = 255, or type NC_INT where
where ndrv = 4294967295 - 1 = 4294967294.
unpack(x)scale_factor and add_offset.
If scale_factor is present for a variable, the data are
multiplied by the value scale_factor after the data are read.
If add_offset is present for a variable, then the
add_offset value is added to the data after the data are read.
If both scale_factor and add_offset attributes are
present, the data are first scaled by scale_factor before the
offset add_offset is added.
upk = scale_factor*pck + add_offset = (max-min)*pck/ndrv + 0.5*(min+max)
When scale_factor and add_offset are used for packing, the
associated variable (containing the packed data) is typically of type
byte or short, whereas the unpacked values are intended to
be of type int, float, or double.
An attribute's scale_factor and add_offset and
missing_value, if any, should all be of the type intended for the
unpacked data, i.e., int, float or double.
These intrinsic functions allow ncap to convert variables on disk among the available types supported by netCDF.
byte(x)NC_BYTE
Converts x to external type NC_BYTE, a C-type signed char.
char(x)NC_CHAR
Converts x to external type NC_CHAR, a C-type unsigned char.
double(x)NC_DOUBLE
Converts x to external type NC_DOUBLE, a C-type double.
float(x)NC_FLOAT
Converts x to external type NC_FLOAT, a C-type float.
int(x)NC_INT
Converts x to external type NC_INT, a C-type int.
short(x)NC_SHORT
Converts x to external type NC_SHORT, a C-type short.
ncap supports the standard mathematical functions supplied with most operating systems. Standard calculator notation is used for addition +, subtraction -, multiplication *, division /, exponentiation ^, and modulus %. The available elementary mathematical functions are:
abs(x)acos(x)acosh(x)asin(x)asinh(x)atan(x)atanh(x)ceil(x)cos(x)cosh(x)erf(x)erfc(x)exp(x)floor(x)gamma(x)ln(x)log(x)log10(x)nearbyint(x)pow(x,y)pow function,
integer arguments are promoted (see Type conversion) to type
NC_FLOAT before evaluation.
Example: pow(2,3) = 8
rint(x)round(x)sin(x)sinh(x)sqrt(x)tan(x)tanh(x)trunc(x)NC_FLOAT and NC_DOUBLE.
29
EXAMPLES
Define new attribute new for existing variable one as twice the existing attribute double_att of variable att_var:
ncap -O -s "one@new=2*att_var@double_att" in.nc out.nc
Average variables of mixed types (result is of type double):
ncap -O -s "average=(var_float+var_double+var_int)/3" in.nc out.nc
Multiple commands may be given to ncap in three ways.
First, the commands may be placed in a script which is executed, e.g.,
tst.nco.
Second, the commands may be individually specified with multiple
`-s' arguments to the same ncap invocation.
Third, the commands may be chained together into a single `-s'
argument to ncap.
Assuming the file tst.nco contains the commands
a=3;b=4;c=sqrt(a^2+b^2);, then the following ncap
invocations produce identical results:
ncap -O -v -S tst.nco in.nc out.nc
ncap -O -v -s "a=3" -s "b=4" -s "c=sqrt(a^2+b^2)" in.nc out.nc
ncap -O -v -s "a=3;b=4;c=sqrt(a^2+b^2)" in.nc out.nc
The second and third examples show that ncap does not require that a trailing semi-colon `;' be placed at the end of a `-s' argument, although a trailing semi-colon `;' is always allowed. However, semi-colons are required to separate individual assignment statements chained together as a single `-s' argument.
Imagine you wish to create a binary flag based on the value of
an array.
The flag should have value 1.0 where the array exceeds 1.0,
and value 0.0 elsewhere.
Assume the array named ORO is in in.nc.
The variable ORO_flg in out.nc
# Add degenerate "record" dimension to ORO for averaging
ncecat -O -v ORO in.nc foo.nc
# Average degenerate "record" dimension using ORO as mask
ncwa -a record -O -m ORO -T gt -M 1.0 foo.nc foo.nc
# ORO is either 0.0 or > 1.0 everywhere
# Create ORO_frc in [0.0,1.0) then add 0.99 and convert to int
ncap -O -s "ORO_frc=ORO-int(ORO)" -s "ORO_flg=int(ORO_frc+0.99)" foo.nc out.nc
# ORO_flg now equals 0 or 1
This example uses ncap to compute the covariance of two variables. Let the variables u and v be the horizontal wind components. The covariance of u and v is defined as the time mean product of the deviations of u and v from their respective time means. Symbolically, the covariance
[u'v'] = [uv]-[u][v] where [x] denotes the time-average of x and x'
denotes the deviation from the time-mean.
The covariance tells us how much of the correlation of two signals
arises from the signal fluctuations versus the mean signals.
Sometimes this is called the eddy covariance.
We will store the covariance in the variable uprmvprm.
ncwa -O -a time -v u,v in.nc foo.nc # Compute time mean of u,v
ncrename -O -v u,uavg -v v,vavg foo.nc # Rename to avoid conflict
ncks -A -v uavg,vavg foo.nc in.nc # Place time means with originals
ncap -O -s "uprmvprm=u*v-uavg*vavg" in.nc in.nc # Covariance
ncra -O -v uprmvprm in.nc foo.nc # Time-mean covariance
The mathmatically inclined will note that the same covariance would be obtained by replacing the step involving ncap with
ncap -O -s "uprmvprm=(u-uavg)*(v-vavg)" foo.nc foo.nc # Covariance
Whether a degenerate record dimension is a desirable or undesirable
feature depends on the application.
Often a degenerate time dimension is useful, e.g., for
concatentating, but it may cause problems with arithmetic.
Such is the case in the above example, where the first step employs
ncwa rather than ncra for the time-averaging.
Of course the numerical results are the same with both operators.
The difference is that ncwa writes no time dimension to
the output file, while ncra would write a degenerate
(size 1) dimension.
Appending u and v to the output file would cause
ncks to try to expand the degenerate time axis of uavg
and vavg to the size of the non-degenerate time dimension
in the input file.
Thus the append (ncks -A) command would be undefined (and
should fail) in this case.
Equally important is the `-C' argument (see Coordinate variables) to ncwa to prevent any scalar time variable
from being written to the output file.
Knowing when to use ncwa -a time rather than the default
ncra for time-averaging takes, well, time.
ncatted [-a att_dsc] [-a ...] [-D dbg] [-h]
[-l path] [-O] [-o output-file] [-p path] [-R] [-r]
input-file [[output-file]]
DESCRIPTION
ncatted edits attributes in a netCDF file.
If you are editing attributes then you are spending too much time in the
world of metadata, and ncatted was written to get you back out as
quickly and painlessly as possible.
ncatted can append, create, delete,
modify, and overwrite attributes (all explained below).
Furthermore, ncatted allows each editing operation to be applied
to every variable in a file.
This saves time when changing attribute conventions throughout a file.
Note that ncatted interprets character attributes
(i.e., attributes of type NC_CHAR) as strings.
Because repeated use of ncatted can considerably increase the size
of the history global attribute (see History attribute), the
`-h' switch is provided to override automatically appending the
command to the history global attribute in the output-file.
When ncatted is used to change the missing_value attribute,
it changes the associated missing data self-consistently.
If the internal floating point representation of a missing value,
e.g., 1.0e36, differs between two machines then netCDF files produced
on those machines will have incompatible missing values.
This allows ncatted to change the missing values in files from
different machines to a single value so that the files may then be
concatenated together, e.g., by ncrcat, without losing any
information.
See Missing values, for more information.
The key to mastering ncatted is understanding the meaning of the
structure describing the attribute modification, att_dsc specified by the required option `-a' or `--attribute'.
Each att_dsc contains five elements, which makes using
ncatted somewhat complicated, but powerful.
The att_dsc argument structure contains five arguments in the
following order:
att_dsc = att_nm, var_nm, mode, att_type,
att_val
units
pressure
a.
See below for complete listing of valid values of mode.
c.
See below for complete listing of valid values of att_type.
pascal.
The value of att_nm is the name of the attribute you want to edit. This meaning of this should be clear to all users of the ncatted operator. If att_nm is omitted (i.e., left blank) and Delete mode is selected, then all attributes associated with the specified variable will be deleted.
The value of var_nm is the name of the variable containing the attribute (named att_nm) that you want to edit. There are two very important and useful exceptions to this rule. The value of var_nm can also be used to direct ncatted to edit global attributes, or to repeat the editing operation for every variable in a file. A value of var_nm of “global” indicates that att_nm refers to a global attribute, rather than a particular variable's attribute. This is the method ncatted supports for editing global attributes. If var_nm is left blank, on the other hand, then ncatted attempts to perform the editing operation on every variable in the file. This option may be convenient to use if you decide to change the conventions you use for describing the data.
The value of mode is a single character abbreviation (a,
c, d, m, or o) standing for one of
five editing modes:
acdmoThe value of att_type is a single character abbreviation (f,
d, l, i, s, c, or b) standing
for one of the seven primitive netCDF data types:
fNC_FLOAT.
dNC_DOUBLE.
iNC_INT.
lNC_LONG.
sNC_SHORT.
cNC_CHAR.
bNC_BYTE.
The value of att_val is what you want to change attribute
att_nm to contain.
The specification of att_val is optional in Delete mode.
Attribute values for all types besides NC_CHAR must have an attribute
length of at least one.
Thus att_val may be a single value or one-dimensional array of
elements of type att_type.
If the att_val is not set or is set to empty space,
and the att_type is NC_CHAR, e.g., -a units,T,o,c,"" or
-a units,T,o,c,, then the corresponding attribute is set to
have zero length.
When specifying an array of values, it is safest to enclose
att_val in single or double quotes, e.g.,
-a levels,T,o,s,"1,2,3,4" or
-a levels,T,o,s,'1,2,3,4'.
The quotes are strictly unnecessary around att_val except
when att_val contains characters which would confuse the calling
shell, such as spaces, commas, and wildcard characters.
NCO processing of NC_CHAR attributes is a bit like Perl in
that it attempts to do what you want by default (but this sometimes
causes unexpected results if you want unusual data storage).
If the att_type is NC_CHAR then the argument is interpreted as a
string and it may contain C-language escape sequences, e.g., \n,
which NCO will interpret before writing anything to disk.
NCO translates valid escape sequences and stores the
appropriate ASCII code instead.
Since two byte escape sequences, e.g., \n, represent one-byte
ASCII codes, e.g., ASCII 10 (decimal), the stored
string attribute is one byte shorter than the input string length for
each embedded escape sequence.
The most frequently used C-language escape sequences are \n (for
linefeed) and \t (for horizontal tab).
These sequences in particular allow convenient editing of formatted text
attributes.
The other valid ASCII codes are \a, \b, \f,
\r, \v, and \\.
See ncks netCDF Kitchen Sink, for more examples of string formatting
(with the ncks `-s' option) with special characters.
Analogous to printf, other special characters are also allowed by
ncatted if they are "protected" by a backslash.
The characters ", ', ?, and \ may be
input to the shell as \", \', \?, and \\.
NCO simply strips away the leading backslash from these
characters before editing the attribute.
No other characters require protection by a backslash.
Backslashes which precede any other character (e.g., 3, m,
$, |, &, @, %, {, and
}) will not be filtered and will be included in the attribute.
Note that the NUL character \0 which terminates C language
strings is assumed and need not be explicitly specified.
If \0 is input, it will not be translated (because it would
terminate the string in an additional location).
Because of these context-sensitive rules, if wish to use an attribute of
type NC_CHAR to store data, rather than text strings, you should use
ncatted with care.
EXAMPLES
Append the string "Data version 2.0.\n" to the global attribute
history:
ncatted -O -a history,global,a,c,"Data version 2.0\n" in.nc
Note the use of embedded C language printf()-style escape
sequences.
Change the value of the long_name attribute for variable T
from whatever it currently is to "temperature":
ncatted -O -a long_name,T,o,c,temperature in.nc
Delete all existing units attributes:
ncatted -O -a units,,d,, in.nc
The value of var_nm was left blank in order to select all variables in the file. The values of att_type and att_val were left blank because they are superfluous in Delete mode.
Delete all attributes associated with the tpt variable:
ncatted -O -a ,tpt,d,, in.nc
The value of att_nm was left blank in order to select all
attributes associated with the variable.
To delete all global attributes, simply replace tpt with
global in the above.
Modify all existing units attributes to "meter second-1"
ncatted -O -a units,,m,c,"meter second-1" in.nc
Overwrite the quanta attribute of variable
energy to an array of four integers.
ncatted -O -a quanta,energy,o,s,"010,101,111,121" in.nc
Demonstrate input of C-language escape sequences (e.g., \n) and
other special characters (e.g., \")
ncatted -h -a special,global,o,c,
'\nDouble quote: \"\nTwo consecutive double quotes: \"\"\n
Single quote: Beyond my shell abilities!\nBackslash: \\\n
Two consecutive backslashes: \\\\\nQuestion mark: \?\n' in.nc
Note that the entire attribute is protected from the shell by single quotes. These outer single quotes are necessary for interactive use, but may be omitted in batch scripts.
ncbo [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h]
[-l path] [-O] [-o file_3] [-p path] [-R] [-r]
[-t thr_nbr] [-v var[,...]] [-x] [-y op_typ]
file_1 file_2 [file_3]
DESCRIPTION
ncbo performs binary operations on variables in file_1 and the corresponding variables (those with the same name) in file_2 and stores the results in file_3. The binary operation operates on the entire files (modulo any excluded variables). See Missing values, for treatment of missing values. One of the four standard arithmetic binary operations currently supported must be selected with the `-y op_typ' switch (or long options `--op_typ' or `--operation'). The valid binary operations for ncbo, their definitions, corresponding values of the op_typ key, and alternate invocations are:
ncbo --op_typ=* 1.nc 2.nc 3.nc # Dangerous (shell may try to glob)
ncbo --op_typ='*' 1.nc 2.nc 3.nc # Safe ('*' protected from shell)
ncbo --op_typ="*" 1.nc 2.nc 3.nc # Safe ('*' protected from shell)
ncbo --op_typ=mlt 1.nc 2.nc 3.nc
ncbo --op_typ=mult 1.nc 2.nc 3.nc
ncbo --op_typ=multiply 1.nc 2.nc 3.nc
ncbo --op_typ=multiplication 1.nc 2.nc 3.nc
ncmult 1.nc 2.nc 3.nc # First do 'ln -s ncbo ncmult'
ncmultiply 1.nc 2.nc 3.nc # First do 'ln -s ncbo ncmultiply'
No particular argument or invocation form is preferred. Users are encouraged to use the forms which are most intuitive to them.
Normally, ncbo will fail unless an operation type is specified with `-y' (equivalent to `--op_typ'). You may create exceptions to this rule to suit your particular tastes, in conformance with your site's policy on symbolic links to executables (files of a different name point to the actual executable). For many years, ncdiff was the main binary file operator. As a result, many users prefer to continue invoking ncdiff rather than memorizing a new command (`ncbo -y sbt') which behaves identically to the original ncdiff command. However, from a software maintenance standpoint, maintaining a distinct executable for each binary operation (e.g., ncadd) is untenable, and a single executable, ncbo, is desirable. To maintain backward compatibility, therefore, NCO automatically creates a symbolic link from ncbo to ncdiff. Thus ncdiff is called an alternate invocation of ncbo. ncbo supports many additional alternate invocations which must be manually activated. Should users or system adminitrators decide to activate them, the procedure is simple. For example, to use `ncadd' instead of `ncbo --op_typ=add', simply create a symbolic link from ncbo to ncadd 32. The alternatate invocations supported for each operation type are listed above. Alternatively, users may always define `ncadd' as an alias to `ncbo --op_typ=add' 33.
It is important to maintain portability in NCO scripts. Therefore we recommend that site-specfic invocations (e.g., `ncadd') be used only in interactive sessions from the command-line. For scripts, we recommend using the full invocation (e.g., `ncbo --op_typ=add'). This ensures portability of scripts between users and sites.
ncbo operates (e.g., adds) variables in file_2 with 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, but the reverse is
not true.
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.
In the future, we will broadcast variables in file_1, if necessary
to conform to their counterparts in file_2.
Thus, presently, 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 initially the same dimensions as file_1 (often 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
34.
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 occuring, use ncwa to remove the
time dimension from file_2.
See the example below.
ncbo never operates on 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 CCSM fields
(e.g., ORO).
See NCAR CCSM Conventions for a complete description.
Finally, we note that ncflint (see ncflint netCDF File Interpolator) is designed for file interpolation.
As such, it also performs file subtraction, addition, multiplication,
albeit in a more convoluted way than ncbo.
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 -op_typ=sub 86_0112.nc 85_0112.nc 86m85_0112.nc
ncdiff 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:
ncdiff -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 85_x.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 85_x.nc
ncdiff 85_0112.nc 85_x.nc tx_anm_85_0112.nc
This examples works assuming 85_0112.nc has dimensions
time and lon, and that 85_x.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 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:
for idx in {01..12}; do # Bash Shell (version 3.0+, beware ordering!)
ncks -F -d time,${idx},,12 t_anm_8501_8912.nc foo.${idx}
ncra foo.${idx} t_anm_8589_${idx}.nc
done
for idx in 01 02 03 04 05 06 07 08 09 10 11 12; do # Bourne Shell
ncks -F -d time,${idx},,12 t_anm_8501_8912.nc foo.${idx}
ncra foo.${idx} t_anm_8589_${idx}.nc
done
foreach idx (01 02 03 04 05 06 07 08 09 10 11 12) # C Shell
ncks -F -d time,${idx},,12 t_anm_8501_8912.nc foo.${idx}
ncra foo.${idx} t_anm_8589_${idx}.nc
end
Note that ncra understands the stride argument so the
two commands inside the loop may be combined into the single command
ncra -F -d time,${idx},,12 t_anm_8501_8912.nc foo.${idx}
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
ncea [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h] [-l path]
[-n loop] [-O] [-o output-file] [-p path] [-R] [-r]
[-t thr_nbr] [-v var[,...]] [-x] [-y op_typ]
[input-files] [output-file]
DESCRIPTION
ncea 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.
ncea averages entire files, and weights each file evenly.
This is distinct from ncra, which only averages over the
record dimension (e.g., time), and weights each record in the record
dimension evenly,
All dimensions, including the record dimension, are treated identically
and preserved in the output-file.
See Averaging vs. Concatenating, for a description of the
distinctions between the various averagers and concatenators.
As a multi-file operator, ncea will read the list of
input-files from stdin if they are not specified
as positional arguments on the command line
(see Large numbers of input files).
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 ncea is the operator to use. ncea assumes coordinate variable are properties common to all of the experiments and so does not average them across files. Instead, ncea copies the values of the coordinate variables from the first input file to the output file.
EXAMPLES
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):
ncea 85_01.nc 85_02.nc 85_03.nc 85_04.nc 85_05.nc 85.nc
ncea 85_0[1-5].nc 85.nc
ncea -n 5,2,1 85_01.nc 85.nc
These three commands produce identical answers. See Specifying input files, for an explanation of the distinctions between these methods. The output file, 85.nc, is the same size as the inputs files. It contains 12 months of data (which might or might not be stored in the record dimension, depending on the input files), but each value in the output file is the average of the five values in the input files.
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.,
ncea -d time,0,2 -d lat,-23.5,23.5 85_??.nc 85.nc
In this case the output file would contain only three slices of data in the time dimension. These three slices are the average of the first three slices from the input files. Additionally, only data inside the tropics is included.
ncecat [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h] [-l path]
[-n loop] [-O] [-o output-file] [-p path] [-R] [-r]
[-v var[,...]] [-x] [input-files] [output-file]
DESCRIPTION
ncecat concatenates an arbitrary number of input files into a
single output file.
A new record dimension acts as the glue to bind the input files data
together.
Each variable in each input file becomes one record in the same variable
in the output file.
All input-files must contain all extracted variables (or else
there would be "gaps" in the output file).
Each extracted variable must be constant in size and rank across all
input-files.
The input-files are stored consecutively as a single record in
output file.
Thus, the output file size is the sum of the sizes of the
extracted variable in the input files.
See Averaging vs. Concatenating, for a description of the
distinctions between the various averagers and concatenators.
As a multi-file operator, ncecat will read the list of
input-files from stdin if they are not specified
as positional arguments on the command line
(see Large numbers of input files).
Consider five realizations, 85a.nc, 85b.nc,
... 85e.nc of 1985 predictions from the same climate
model.
Then ncecat 85?.nc 85_ens.nc glues the individual realizations
together into the single file, 85_ens.nc.
If an input variable was dimensioned [lat,lon], it will
have dimensions [record,lat,lon] in the output
file.
A restriction of ncecat is that the hyperslabs of the
processed variables must be the same from file to file.
Normally this means all the input files are the same size, and contain
data on different realizations of the same variables.
EXAMPLES
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 all the seasonal cycles. Here the numeric filename suffix denotes the experiment number (not the month):
ncecat 85_01.nc 85_02.nc 85_03.nc 85_04.nc 85_05.nc 85.nc
ncecat 85_0[1-5].nc 85.nc
ncecat -n 5,2,1 85_01.nc 85.nc
These three commands produce identical answers. See Specifying input files, for an explanation of the distinctions between these methods. The output file, 85.nc, is five times the size as a single input-file. It contains 60 months of data (which might or might not be stored in the record dimension, depending on the input files).
Consider a file with an existing record dimension named time.
and suppose the user wishes to convert time from a record
dimension to a non-record dimension.
This may be useful, for example, when the user has another use for the
record variable.
The procedure is to use ncecat followed by ncwa
ncecat in.nc out.nc # Convert time to non-record dimension
ncwa -a record in.nc out.nc # Remove new degenerate record dimension
The second step removes the degenerate record dimension. See ncpdq netCDF Permute Dimensions Quickly for other methods changing variable dimensionality, including the record dimension.
ncflint [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h] [-i var,val3]
[-l path] [-O] [-o file_3] [-p path] [-R] [-r]
[-v var[,...]] [-w wgt1[,wgt2]] [-x]
file_1 file_2 [file_3]
DESCRIPTION
ncflint creates an output file that is a linear combination of the input files. This linear combination is a weighted average, a normalized weighted average, or an interpolation of the input files. Coordinate variables are not acted upon in any case, they are simply copied from file_1.
There are two conceptually distinct methods of using ncflint. The first method is to specify the weight each input file contributes to the output file. In this method, the value val3 of a variable in the output file file_3 is determined from its values val1 and val2 in the two input files according to
val3 = wgt1*val1 + wgt2*val2
. Here at least wgt1, and, optionally, wgt2, are specified on the command line with the `-w' (or `--weight' or `--wgt_var') switch. If only wgt1 is specified then wgt2 is automatically computed as wgt2 = 1 − wgt1. Note that weights larger than 1 are allowed. Thus it is possible to specify wgt1 = 2 and wgt2 = -3. One can use this functionality to multiply all the values in a given file by a constant.
The second method of using ncflint is to specify the interpolation option with `-i' (or with the `--ntp' or `--interpolate' long options). This is really the inverse of the first method in the following sense. When the user specifies the weights directly, ncflint has no work to do besides multiplying the input values by their respective weights and adding the results together to produce the output values. It makes sense to use this when the weights are known a priori.
Another class of problems has the arrival value (i.e., val3) of a particular variable var known a priori. In this case, the implied weights can always be inferred by examining the values of var in the input files. This results in one equation in two unknowns, wgt1 and wgt2:
val3 = wgt1*val1 + wgt2*val2
. Unique determination of the weights requires imposing the additional constraint of normalization on the weights: wgt1 + wgt2 = 1. Thus, to use the interpolation option, the user specifies var and val3 with the `-i' option. ncflint then computes wgt1 and wgt2, and uses these weights on all variables to generate the output file. Although var may have any number of dimensions in the input files, it must represent a single, scalar value. Thus any dimensions associated with var must be degenerate, i.e., of size one.
If neither `-i' nor `-w' is specified on the command line, ncflint defaults to weighting each input file equally in the output file. This is equivalent to specifying `-w 0.5' or `-w 0.5,0.5'. Attempting to specify both `-i' and `-w' methods in the same command is an error.
ncflint does not interpolate variables of type NC_CHAR
and NC_BYTE.
This behavior is hardcoded.
Depending on your intuition, ncflint may treat missing values unexpectedly. Consider a point where the value in one input file, say val1, equals the missing value mss_val_1 and, at the same point, the corresponding value in the other input file val2 is not misssing (i.e., does not equal mss_val_2). There are three plausible answers, and this creates ambiguity.
Option one is to set val3 = mss_val_1. The rationale is that ncflint is, at heart, an interpolator and interpolation involving a missing value is intrinsically undefined. ncflint currently implements this behavior since it is the most conservative and least likely to lead to misinterpretation.
Option two is to output the weighted valid data point, i.e.,
val3 = wgt2*val2
. The rationale for this behavior is that interpolation is really a weighted average of known points, so ncflint should weight the valid point.
Option three is to return the unweighted valid point, i.e., val3 = val2. This behavior would appeal to those who use ncflint to estimate data using the closest available data. When a point is not bracketed by valid data on both sides, it is better to return the known datum than no datum at all.
The current implementation uses the first approach, Option one. If you have strong opinions on this matter, let us know, since we are willing to implement the other approaches as options if there is enough interest.
EXAMPLES
Although it has other uses, the interpolation feature was designed
to interpolate file_3 to a time between existing files.
Consider input files 85.nc and 87.nc containing variables
describing the state of a physical system at times time =
85 and time = 87.
Assume each file contains its timestamp in the scalar variable
time.
Then, to linearly interpolate to a file 86.nc which describes
the state of the system at time at time = 86, we would use
ncflint -i time,86 85.nc 87.nc 86.nc
Say you have observational data covering January and April 1985 in two files named 85_01.nc and 85_04.nc, respectively. Then you can estimate the values for February and March by interpolating the existing data as follows. Combine 85_01.nc and 85_04.nc in a 2:1 ratio to make 85_02.nc:
ncflint -w 0.667 85_01.nc 85_04.nc 85_02.nc
ncflint -w 0.667,0.333 85_01.nc 85_04.nc 85_02.nc
Multiply 85.nc by 3 and by −2 and add them together to make tst.nc:
ncflint -w 3,-2 85.nc 85.nc tst.nc
This is an example of a null operation, so tst.nc should be identical (within machine precision) to 85.nc.
Add 85.nc to 86.nc to obtain 85p86.nc, then subtract 86.nc from 85.nc to obtain 85m86.nc
ncflint -w 1,1 85.nc 86.nc 85p86.nc
ncflint -w 1,-1 85.nc 86.nc 85m86.nc
ncdiff 85.nc 86.nc 85m86.nc
Thus ncflint can be used to mimic some ncbo operations. However this is not a good idea in practice because ncflint does not broadcast (see ncbo netCDF Binary Operator) conforming variables during arithmetic. Thus the final two commands would produce identical results except that ncflint would fail if any variables needed to be broadcast.
Rescale the dimensional units of the surface pressure prs_sfc
from Pascals to hectopascals (millibars)
ncflint -O -C -v prs_sfc -w 0.01,0.0 in.nc in.nc out.nc
ncatted -O -a units,prs_sfc,o,c,millibar out.nc
ncks [-A] [-a] [-B] [-b binary-file] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]][,[stride]]]
[-F] [-H] [-h] [-l path] [-M] [-m] [-O] [-o output-file]
[-p path] [-q] [-R] [-r] [-s format] [-u]
[-v var[,...]] [-x] input-file [[output-file]]
DESCRIPTION
ncks combines selected features of ncdump, ncextr, and the nccut and ncpaste specifications into one versatile utility. ncks extracts a subset of the data from input-file and prints it as ASCII text to stdout, writes it in flat binary format to binary-file, and writes (or pastes) it in netCDF format to output-file.
ncks will print netCDF data in ASCII format to
stdout, like ncdump, but with these differences:
ncks prints data in a tabular format intended to be easy to
search for the data you want, one datum per screen line, with all
dimension subscripts and coordinate values (if any) preceding the datum.
Option `-s' (or lon options `--sng', `--string',
`--fmt', or `--format') allows the user the format the data
using C-style format strings.
Options `-a', `-F' , `-H', `-M', `-m', `-q', `-s', and `-u' (and their long option counterparts) control the formatted appearance of the data.
ncks extracts (and optionally creates a new netCDF file comprised of) only selected variables from the input file (similar to the old ncextr specification). Only variables and coordinates may be specifically included or excluded—all global attributes and any attribute associated with an extracted variable are copied to the screen and/or output netCDF file. Options `-c', `-C', `-v', and `-x' (and their long option synonyms) control which variables are extracted.
ncks extracts hyperslabs from the specified variables (ncks implements the original nccut specification). Option `-d' controls the hyperslab specification. Input dimensions that are not associated with any output variable do not appear in the output netCDF. This feature removes superfluous dimensions from netCDF files.
ncks will append variables and attributes from the input-file to output-file if output-file is a pre-existing netCDF file whose relevant dimensions conform to dimension sizes of input-file. The append features of ncks are intended to provide a rudimentary means of adding data from one netCDF file to another, conforming, netCDF file. If naming conflicts exist between the two files, data in output-file is usually overwritten by the corresponding data from input-file. Thus, when appending, the user should backup output-file in case valuable data are inadvertantly overwritten.
If output-file exists, the user will be queried whether to overwrite, append, or exit the ncks call completely. Choosing overwrite destroys the existing output-file and create an entirely new one from the output of the ncks call. Append has differing effects depending on the uniqueness of the variables and attributes output by ncks: If a variable or attribute extracted from input-file does not have a name conflict with the members of output-file then it will be added to output-file without overwriting any of the existing contents of output-file. In this case the relevant dimensions must agree (conform) between the two files; new dimensions are created in output-file as required. When a name conflict occurs, a global attribute from input-file will overwrite the corresponding global attribute from output-file. If the name conflict occurs for a non-record variable, then the dimensions and type of the variable (and of its coordinate dimensions, if any) must agree (conform) in both files. Then the variable values (and any coordinate dimension values) from input-file will overwrite the corresponding variable values (and coordinate dimension values, if any) in output-file 35.
Since there can only be one record dimension in a file, the record dimension must have the same name (but not necessarily the same size) in both files if a record dimension variable is to be appended. If the record dimensions are of differing sizes, the record dimension of output-file will become the greater of the two record dimension sizes, the record variable from input-file will overwrite any counterpart in output-file and fill values will be written to any gaps left in the rest of the record variables (I think). In all cases variable attributes in output-file are superseded by attributes of the same name from input-file, and left alone if there is no name conflict.
Some users may wish to avoid interactive ncks queries about whether to overwrite existing data. For example, batch scripts will fail if ncks does not receive responses to its queries. Options `-O' and `-A' are available to force overwriting existing files and variables, respectively.
The following list provides a short summary of the features unique to ncks. Features common to many operators are described in Common features.
-a results in the variables being extracted, printed,
and written to disk in the order in which they were saved in the input
file.
Thus -a retains the original ordering of the variables.
Also `--abc' and `--alphabetize'.
-B switch is redundant when the -b file
option is specified, and native binary output will be directed to the
binary file file.
Also `--bnr' and `--binary'.
Writing packed variables in binary format is not supported.
-s), each element of the data
hyperslab is printed on a separate line containing the names, indices,
and, values, if any, of all of the variables dimensions.
The dimension and variable indices refer to the location of the
corresponding data element with respect to the variable as stored on
disk (i.e., not the hyperslab).
% ncks -C -v three_dmn_var in.nc
lat[0]=-90 lev[0]=100 lon[0]=0 three_dmn_var[0]=0
lat[0]=-90 lev[0]=100 lon[1]=90 three_dmn_var[1]=1
lat[0]=-90 lev[0]=100 lon[2]=180 three_dmn_var[2]=2
...
lat[1]=90 lev[2]=1000 lon[1]=90 three_dmn_var[21]=21
lat[1]=90 lev[2]=1000 lon[2]=180 three_dmn_var[22]=22
lat[1]=90 lev[2]=1000 lon[3]=270 three_dmn_var[23]=23
Printing the same variable with the `-F' option shows the same variable indexed with Fortran conventions
% ncks -F -C -v three_dmn_var in.nc
lon(1)=0 lev(1)=100 lat(1)=-90 three_dmn_var(1)=0
lon(2)=90 lev(1)=100 lat(1)=-90 three_dmn_var(2)=1
lon(3)=180 lev(1)=100 lat(1)=-90 three_dmn_var(3)=2
...
Printing a hyperslab does not affect the variable or dimension indices since these indices are relative to the full variable (as stored in the input file), and the input file has not changed. However, if the hypserslab is saved to an output file and those values are printed, the indices will change:
% ncks -O -H -d lat,90.0 -d lev,1000.0 -v three_dmn_var in.nc out.nc
...
lat[1]=90 lev[2]=1000 lon[0]=0 three_dmn_var[20]=20
lat[1]=90 lev[2]=1000 lon[1]=90 three_dmn_var[21]=21
lat[1]=90 lev[2]=1000 lon[2]=180 three_dmn_var[22]=22
lat[1]=90 lev[2]=1000 lon[3]=270 three_dmn_var[23]=23
% ncks -C -v three_dmn_var out.nc
lat[0]=90 lev[0]=1000 lon[0]=0 three_dmn_var[0]=20
lat[0]=90 lev[0]=1000 lon[1]=90 three_dmn_var[1]=21
lat[0]=90 lev[0]=1000 lon[2]=180 three_dmn_var[2]=22
lat[0]=90 lev[0]=1000 lon[3]=270 three_dmn_var[3]=23
printf() formats.
Also `--string', `--format', and `--fmt'.
units
attribute, if any.
Also `--units'.
EXAMPLES
View all data in netCDF in.nc, printed with Fortran indexing conventions:
ncks -F in.nc
Copy the netCDF file in.nc to file out.nc.
ncks -O in.nc out.nc
Now the file out.nc contains all the data from in.nc.
There are, however, two differences between in.nc and
out.nc.
First, the history global attribute (see History attribute)
will contain the command used to create out.nc.
Second, the variables in out.nc will be defined in alphabetical
order.
Of course the internal storage of variable in a netCDF file should be
transparent to the user, but there are cases when alphabetizing a file
is useful (see description of -a switch).
Print variable three_dmn_var from file in.nc with
default notations.
Next print three_dmn_var as an un-annotated text column.
Then print three_dmn_var signed with very high precision.
Finally, print three_dmn_var as a comma-separated list.
% ncks -C -v three_dmn_var in.nc
lat[0]=-90 lev[0]=100 lon[0]=0 three_dmn_var[0]=0
lat[0]=-90 lev[0]=100 lon[1]=90 three_dmn_var[1]=1
...
lat[1]=90 lev[2]=1000 lon[3]=270 three_dmn_var[23]=23
% ncks -s "%f\n" -C -v three_dmn_var in.nc
0.000000
1.000000
...
23.000000
% ncks -s "%+16.10f\n" -C -v three_dmn_var in.nc
+0.0000000000
+1.0000000000
...
+23.0000000000
% ncks -s "%f, " -C -v three_dmn_var in.nc
0.000000, 1.000000, ..., 23.000000,
The second and third options are useful when pasting data into text files like reports or papers. See ncatted netCDF Attribute Editor, for more details on string formatting and special characters.
One dimensional arrays of characters stored as netCDF variables are automatically printed as strings, whether or not they are NUL-terminated, e.g.,
ncks -v fl_nm in.nc
The %c formatting code is useful for printing
multidimensional arrays of characters representing fixed length strings
ncks -s "%c" -v fl_nm_arr in.nc
Using the %s format code on strings which are not NUL-terminated
(and thus not technically strings) is likely to result in a core dump.
Create netCDF out.nc containing all variables, and any associated
coordinates, except variable time, from netCDF in.nc:
ncks -x -v time in.nc out.nc
Extract variables time and pressure from netCDF
in.nc.
If out.nc does not exist it will be created.
Otherwise the you will be prompted whether to append to or to
overwrite out.nc:
ncks -v time,pressure in.nc out.nc
ncks -C -v time,pressure in.nc out.nc
The first version of the command creates an out.nc which contains
time, pressure, and any coordinate variables associated
with pressure.
The out.nc from the second version is guaranteed to contain only
two variables time and pressure.
Create netCDF out.nc containing all variables from file
in.nc.
Restrict the dimensions of these variables to a hyperslab.
Print (with -H) the hyperslabs to the screen for good measure.
The specified hyperslab is: the fifth value in dimension time;
the
half-open range lat > 0. in coordinate lat; the
half-open range lon < 330. in coordinate lon; the
closed interval 0.3 < band < 0.5 in coordinate band;
and cross-section closest to 1000. in coordinate lev.
Note that limits applied to coordinate values are specified with a
decimal point, and limits applied to dimension indices do not have a
decimal point See Hyperslabs.
ncks -H -d time,5 -d lat,,0.0 -d lon,330.0, -d band,0.3,0.5
-d lev,1000.0 in.nc out.nc
Assume the domain of the monotonically increasing longitude coordinate
lon is 0 < lon < 360.
Here, lon is an example of a wrapped coordinate.
ncks will extract a hyperslab which crosses the Greenwich
meridian simply by specifying the westernmost longitude as min and
the easternmost longitude as max, as follows:
ncks -d lon,260.0,45.0 in.nc out.nc
For more details See Wrapped coordinates.
ncpdq [-A] [-a [-]dim[,...]] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h] [-l path]
[-M pck_map] [-O] [-o output-file] [-P pck_plc] [-p path]
[-R] [-r] [-t thr_nbr] [-U] [-v var[,...]] [-x]
input-file [output-file]
DESCRIPTION
ncpdq performs one of two distinct functions, packing or dimension permutation, but not both, when invoked. ncpdq is optimized to perform these actions in a parallel fashion with a minimum of time and memory. The pdq may stand for “Permute Dimensions Quickly”, “Pack Data Quietly”, “Pillory Dan Quayle”, or other silly uses.
The ncpdq packing (and unpacking) algorithms are described
in Intrinsic functions, and are also implemented in
ncap.
ncpdq extends the functionality of these algorithms by
providing high level control of the packing policy so that
users can pack (and unpack) entire files consistently with one command.
The user specifies the desired packing policy with the `-P' switch
(or its long option equivalents, `--pck_plc' and
`--pack_policy') and its pck_plc argument.
Four packing policies are currently implemented:
ncpackncunpackTo reduce required memorization of these complex policy switches, ncpdq may also be invoked via a synonym or with switches that imply a particular policy. ncpack is a synonym for ncpdq and behaves the same in all respects. Both ncpdq and ncpack assume a default packing policy request of `all_new'. Hence ncpack may be invoked without any `-P' switch, unlike ncpdq. Similarly, ncunpack is a synonym for ncpdq except that ncpack implicitly assumes a request to unpack, i.e., `-P pck_upk'. Finally, the ncpdq `-U' switch (or its long option equivalents, `--upk' and `--unpack') requires no argument. It simply requests unpacking.
Given the menagerie of synonyms, equivalent options, and implied
options, a short list of some equivalent commands is appropriate.
The following commands are equivalent for packing:
ncpdq -P all_new, ncpdq --pck_plc=all_new, and
ncpack.
The following commands are equivalent for unpacking:
ncpdq -P upk, ncpdq -U, ncpdq --pck_plc=unpack,
and ncunpack.
Equivalent commands for other packing policies, e.g., `all_xst',
follow by analogy.
Note that ncpdq synonyms are subject to the same constraints
and recommendations discussed in the secion on ncbo synonyms
(see ncbo netCDF Binary Operator).
That is, symbolic links must exist from the synonym to ncpdq,
or else the user must define an alias.
The ncpdq packing algorithms must know to which type
particular types of input variables are to be packed.
The correspondence between the input variable type and the output,
packed type, is called the packing map.
The user specifies the desired packing map with the `-M' switch
(or its long option equivalents, `--pck_map' and
`--map') and its pck_map argument.
Five packing maps are currently implemented:
NC_SHORT [default]NC_SHORTNC_DOUBLE,NC_FLOAT] to NC_SHORTNC_INT,NC_SHORT,NC_CHAR,NC_BYTE]NC_BYTENC_BYTENC_DOUBLE,NC_FLOAT] to NC_BYTENC_INT,NC_SHORT,NC_CHAR,NC_BYTE]NC_SHORTNC_SHORTNC_DOUBLE,NC_FLOAT,NC_INT] to NC_SHORTNC_SHORT,NC_CHAR,NC_BYTE]NC_BYTENC_BYTENC_DOUBLE,NC_FLOAT,NC_INT,NC_SHORT] to NC_BYTENC_CHAR,NC_BYTE]NC_DOUBLE to NC_INT.
Pack [NC_FLOAT,NC_INT] to NC_SHORT.
Pack NC_SHORT to NC_BYTE.NC_CHAR,NC_BYTE]NC_FLOAT-dominated
file size by about 50%.
`flt_byt' packing reduces an NC_DOUBLE-dominated file by
about 87%.
The netCDF packing algorithm (see Intrinsic functions) is
lossy—once packed, the exact original data cannot be recovered without
a full backup.
Hence users should be aware of some packing caveats:
First, the interaction of packing and data equal to the
missing_value is complex.
Test the missing_value behavior by performing a pack/unpack cycle
to ensure data that are missing stay missing and data that are
not misssing do not join the Air National Guard and go missing.
This may lead you to elect a new missing_value.
Second, ncpdq actually allows packing into NC_CHAR (with,
e.g., `flt_chr').
However, the intrinsic conversion of signed char to higher
precision types is tricky so for values equal to zero, i.e.,
NUL.
Hence packing to NC_CHAR is not documented or advertised.
Pack into NC_BYTE (with, e.g., `flt_byt') instead.
ncpdq re-shapes variables in input-file by re-ordering and/or reversing dimensions specified in the dimension list. The dimension list is a whitespace-free, comma separated list of dimension names, optionally prefixed by negative signs, that follows the `-a' (or long options `--arrange', `--permute', `--re-order', or `--rdr') switch. To re-order variables by a subset of their dimensions, specify these dimensions in a comma-separated list following `-a', e.g., `-a lon,lat'. To reverse a dimension, prefix its name with a negative sign in the dimension list, e.g., `-a -lat'. Re-ordering and reversal may be performed simultaneously, e.g., `-a lon,-lat,time,-lev'.
Users may specify any permutation of dimensions, including permutations which change the record dimension identity. The record dimension is re-ordered like any other dimension. This unique ncpdq capability makes it possible to concatenate files along any dimension. See Concatenation for a detailed example. The record dimension is always the most slowly varying dimension in a record variable (see Fortran indexing). The specified re-ordering fails if it requires creating more than one record dimension amongst all the output variables 36.
Two special cases of dimension re-ordering and reversal deserve special mention. First, it may be desirable to completely reverse the storage order of a variable. To do this, include all the variable's dimensions in the dimension re-order list in their original order, and prefix each dimension name with the negative sign. Second, it may useful to transpose a variable's storage order, e.g., from C to Fortran data storage order (see Fortran indexing). To do this, include all the variable's dimensions in the dimension re-order list in reversed order. Explicit examples of these two techniques appear below.
EXAMPLES
Pack and unpack all variables in file in.nc and store the results in out.nc:
ncpdq in.nc out.nc # Same as ncpack in.nc out.nc
ncpdq -P all_new -M flt_sht in.nc out.nc # Defaults
ncpdq -P all_xst in.nc out.nc
ncpdq -P upk in.nc out.nc # Same as ncunpack in.nc out.nc
ncpdq -U in.nc out.nc # Same as ncunpack in.nc out.nc
The first two commands pack any unpacked variable in the input file. They also unpack and then re-pack every packed variable. The third command only packs unpacked variables in the input file. If a variable is already packed, the third command copies it unchanged to the output file. The fourth and fifth commands unpack any packed variables. If a variable is not packed, the third command copies it unchanged.
The previous examples all utilized the default packing map. Suppose you wish to archive all data that are currently unpacked into a form which only preserves 256 distinct values. Then you could specify the packing map pck_map as `hgh_byt' and the packing policy pck_plc as `all_xst':
ncpdq -P all_xst -M hgh_byt in.nc out.nc
Many different packing maps may be used to construct a given file by performing the packing on subsets of variables (e.g., with `-v') and using the append feature with `-A' (see Appending).
Re-order file in.nc so that the dimension lon always
precedes the dimension lat and store the results in
out.nc:
ncpdq -a lon,lat in.nc out.nc
ncpdq -v three_dmn_var -a lon,lat in.nc out.nc
The first command re-orders every variable in the input file.
The second command extracts and re-orders only the variable
three_dmn_var.
Suppose the dimension lat represents latitude and monotonically
increases increases from south to north.
Reversing the lat dimension means re-ordering the data so that
latitude values decrease monotonically from north to south.
Accomplish this with
% ncpdq -a -lat in.nc out.nc
% ncks -C -v lat in.nc
lat[0]=-90
lat[1]=90
% ncks -C -v lat out.nc
lat[0]=90
lat[1]=-90
This operation reversed the latitude dimension of all variables. Whitespace immediately preceding the negative sign that specifies dimension reversal may be dangerous. Quotes and long options can help protect negative signs that should indicate dimension reversal from being interpreted by the shell as dashes that indicate new command line switches.
ncpdq -a -lat in.nc out.nc # Dangerous? Whitespace before "-lat"
ncpdq -a "-lat" in.nc out.nc # OK. Quotes protect "-" in "-lat"
ncpdq -a lon,-lat in.nc out.nc # OK. No whitespace before "-"
ncpdq --rdr=-lat in.nc out.nc # Preferred. Uses "=" not whitespace
To create the mathematical transpose of a variable, place all its
dimensions in the dimension re-order list in reversed order.
This example creates the transpose of three_dmn_var:
% ncpdq -a lon,lev,lat -v three_dmn_var in.nc out.nc
% ncks -C -v three_dmn_var in.nc
lat[0]=-90 lev[0]=100 lon[0]=0 three_dmn_var[0]=0
lat[0]=-90 lev[0]=100 lon[1]=90 three_dmn_var[1]=1
lat[0]=-90 lev[0]=100 lon[2]=180 three_dmn_var[2]=2
...
lat[1]=90 lev[2]=1000 lon[1]=90 three_dmn_var[21]=21
lat[1]=90 lev[2]=1000 lon[2]=180 three_dmn_var[22]=22
lat[1]=90 lev[2]=1000 lon[3]=270 three_dmn_var[23]=23
% ncks -C -v three_dmn_var out.nc
lon[0]=0 lev[0]=100 lat[0]=-90 three_dmn_var[0]=0
lon[0]=0 lev[0]=100 lat[1]=90 three_dmn_var[1]=12
lon[0]=0 lev[1]=500 lat[0]=-90 three_dmn_var[2]=4
...
lon[3]=270 lev[1]=500 lat[1]=90 three_dmn_var[21]=19
lon[3]=270 lev[2]=1000 lat[0]=-90 three_dmn_var[22]=11
lon[3]=270 lev[2]=1000 lat[1]=90 three_dmn_var[23]=23
To completely reverse the storage order of a variable, include
all its dimensions in the re-order list, each prefixed by a negative
sign.
This example reverses the storage order of three_dmn_var:
% ncpdq -a -lat,-lev,-lon -v three_dmn_var in.nc out.nc
% ncks -C -v three_dmn_var in.nc
lat[0]=-90 lev[0]=100 lon[0]=0 three_dmn_var[0]=0
lat[0]=-90 lev[0]=100 lon[1]=90 three_dmn_var[1]=1
lat[0]=-90 lev[0]=100 lon[2]=180 three_dmn_var[2]=2
...
lat[1]=90 lev[2]=1000 lon[1]=90 three_dmn_var[21]=21
lat[1]=90 lev[2]=1000 lon[2]=180 three_dmn_var[22]=22
lat[1]=90 lev[2]=1000 lon[3]=270 three_dmn_var[23]=23
% ncks -C -v three_dmn_var out.nc
lat[0]=90 lev[0]=1000 lon[0]=270 three_dmn_var[0]=23
lat[0]=90 lev[0]=1000 lon[1]=180 three_dmn_var[1]=22
lat[0]=90 lev[0]=1000 lon[2]=90 three_dmn_var[2]=21
...
lat[1]=-90 lev[2]=100 lon[1]=180 three_dmn_var[21]=2
lat[1]=-90 lev[2]=100 lon[2]=90 three_dmn_var[22]=1
lat[1]=-90 lev[2]=100 lon[3]=0 three_dmn_var[23]=0
ncra [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]][,[stride]]] [-F] [-h] [-l path]
[-n loop] [-O] [-o output-file] [-p path] [-R] [-r]
[-t thr_nbr] [-v var[,...]] [-x] [-y op_typ]
[input-files] [output-file]
DESCRIPTION
ncra averages record variables across an arbitrary number of
input-files.
The record dimension is retained as a degenerate (size 1) dimension in
the output variables.
See Averaging vs. Concatenating, for a description of the
distinctions between the various averagers and concatenators.
As a multi-file operator, ncra will read the list of
input-files from stdin if they are not specified
as positional arguments on the command line
(see Large numbers of input files).
Input files may vary in size, but each must have a record dimension. The record coordinate, if any, should be monotonic for (or else non-fatal warnings may be generated). Hyperslabs of the record dimension which include more than one file are handled correctly. ncra supports the stride argument to the `-d' hyperslab option for the record dimension only, stride is not supported for non-record dimensions.
ncra weights each record (e.g., time slice) in the
input-files equally.
ncra does not attempt to see if, say, the time
coordinate is irregularly spaced and thus would require a weighted
average in order to be a true time average.
EXAMPLES
Average files 85.nc, 86.nc, ... 89.nc along the record dimension, and store the results in 8589.nc:
ncra 85.nc 86.nc 87.nc 88.nc 89.nc 8589.nc
ncra 8[56789].nc 8589.nc
ncra -n 5,2,1 85.nc 8589.nc
These three methods produce identical answers. See Specifying input files, for an explanation of the distinctions between these methods.
Assume the files 85.nc, 86.nc, ... 89.nc each contain a record coordinate time of length 12 defined such that the third record in 86.nc contains data from March 1986, etc. NCO knows how to hyperslab the record dimension across files. Thus, to average data from December, 1985 through February, 1986:
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
The file 87.nc is superfluous, but does not cause an error. The `-F' turns on the Fortran (1-based) indexing convention. The following uses the stride option to average all the March temperature data from multiple input files into a single output file
ncra -F -d time,3,,12 -v temperature 85.nc 86.nc 87.nc 858687_03.nc
See Stride, for a description of the stride argument.
Assume the time coordinate is incrementally numbered such that January, 1985 = 1 and December, 1989 = 60. Assuming `??' only expands to the five desired files, the following averages June, 1985–June, 1989:
ncra -d time,6.,54. ??.nc 8506_8906.nc
ncrcat [-A] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]][,[stride]]] [-F] [-h] [-l path]
[-n loop] [-O] [-o output-file] [-p path] [-R] [-r]
[-v var[,...]] [-x] [input-files] [output-file]
DESCRIPTION
ncrcat concatenates record variables across an arbitrary
number of input-files.
The final record dimension is by default the sum of the lengths of the
record dimensions in the input files.
See Averaging vs. Concatenating, for a description of the
distinctions between the various averagers and concatenators.
As a multi-file operator, ncrcat will read the list of
input-files from stdin if they are not specified
as positional arguments on the command line
(see Large numbers of input files).
Input files may vary in size, but each must have a record dimension. The record coordinate, if any, should be monotonic (or else non-fatal warnings may be generated). Hyperslabs of the record dimension which include more than one file are handled correctly. ncra supports the stride argument to the `-d' hyperslab option for the record dimension only, stride is not supported for non-record dimensions.
ncrcat applies special rules to ARM convention time
fields (e.g., time_offset).
See ARM Conventions for a complete description.
EXAMPLES
Concatenate files 85.nc, 86.nc, ... 89.nc along the record dimension, and store the results in 8589.nc:
ncrcat 85.nc 86.nc 87.nc 88.nc 89.nc 8589.nc
ncrcat 8[56789].nc 8589.nc
ncrcat -n 5,2,1 85.nc 8589.nc
These three methods produce identical answers. See Specifying input files, for an explanation of the distinctions between these methods.
Assume the files 85.nc, 86.nc, ... 89.nc each contain a record coordinate time of length 12 defined such that the third record in 86.nc contains data from March 1986, etc. NCO knows how to hyperslab the record dimension across files. Thus, to concatenate data from December, 1985–February, 1986:
ncrcat -d time,11,13 85.nc 86.nc 87.nc 8512_8602.nc
ncrcat -F -d time,12,14 85.nc 86.nc 87.nc 8512_8602.nc
The file 87.nc is superfluous, but does not cause an error. When ncra and ncrcat encounter a file which does contain any records that meet the specified hyperslab criteria, they disregard the file and proceed to the next file without failing. The `-F' turns on the Fortran (1-based) indexing convention. The following uses the stride option to concatenate all the March temperature data from multiple input files into a single output file
ncrcat -F -d time,3,,12 -v temperature 85.nc 86.nc 87.nc 858687_03.nc
See Stride, for a description of the stride argument.
Assume the time coordinate is incrementally numbered such that
January, 1985 = 1 and December, 1989 = 60.
Assuming ?? only expands to the five desired files, the following
concatenates June, 1985–June, 1989:
ncrcat -d time,6.,54. ??.nc 8506_8906.nc
ncrename [-a old_name,new_name] [-a ...] [-D dbg]
[-d old_name,new_name] [-d ...] [-h] [-l path]
[-O] [-o output-file] [-p path] [-R] [-r]
[-v old_name,new_name] [-v ...]
input-file [[output-file]]
DESCRIPTION
ncrename renames dimensions, variables, and attributes in a netCDF file. Each object that has a name in the list of old names is renamed using the corresponding name in the list of new names. All the new names must be unique. Every old name must exist in the input file, unless the old name is preceded by the character `.'. The validity of old_name is not checked prior to the renaming. Thus, if old_name is specified without the the `.' prefix and is not present in input-file, ncrename will abort. The new_name should never be prefixed by a `.' (the period will be included as part of the new name). The OPTIONS and EXAMPLES show how to select specific variables whose attributes are to be renamed.
ncrename is the exception to the normal rules that the user will
be interactively prompted before an existing file is changed, and that a
temporary copy of an output file is constructed during the operation.
If only input-file is specified, then ncrename will change
the names of the input-file in place without prompting and without
creating a temporary copy of input-file.
This is because the renaming operation is considered reversible if the
user makes a mistake.
The new_name can easily be changed back to old_name by using
ncrename one more time.
Note that renaming a dimension to the name of a dependent variable can be used to invert the relationship between an independent coordinate variable and a dependent variable. In this case, the named dependent variable must be one-dimensional and should have no missing values. Such a variable will become a coordinate variable.
According to the netCDF User's Guide, renaming properties in netCDF files does not incur the penalty of recopying the entire file when the new_name is shorter than the old_name.
OPTIONS
EXAMPLES
Rename the variable p to pressure and t to
temperature in netCDF in.nc.
In this case p must exist in the input file (or
ncrename will abort), but the presence of t is optional:
ncrename -v p,pressure -v .t,temperature in.nc
ncrename does not automatically attach dimensions to variables of the same name. If you want to rename a coordinate variable so that it remains a coordinate variable, you must separately rename both the dimension and the variable:
ncrename -d lon,longitude -v lon,longitude in.nc
Create netCDF out.nc identical to in.nc except the
attribute _FillValue is changed to missing_value
which possess it), the attribute units is renamed to
CGS_units (but only in those variables which possess it)
and the global attribute Zaire is renamed to Congo:
ncrename -a _FillValue,missing_value -a .units,CGS_units \
-a tpt@hieght,height -a prs_sfc@.hieght,height in.nc out.nc
The presence and absence of the `.' and `@' features
cause this command to execute successfully only if a number of
conditions are met.
All variables must have a _FillValue attribute and
_FillValue must also be a global attribute.
The units attribute, on the other hand, will be renamed to
CGS_units wherever it is found but need not be present in
the file at all (either as a global or a variable attribute).
The variable tpt must contain the hieght attribute.
The variable prs_sfc need not exist, and need not contain the
hieght attribute.
ncwa [-A] [-a dim[,...]] [-C] [-c] [-D dbg]
[-d dim,[min][,[max]]] [-F] [-h] [-I] [-l path]
[-M mask_val] [-m mask_var] [-N] [-n] [-O]
[-o output-file] [-p path] [-R] [-r] [-T condition]
[-t thr_nbr] [-v var[,...]] [-W] [-w weight] [-x] [-y op_typ]
input-file [output-file]
DESCRIPTION
ncwa averages variables in a single file over arbitrary
dimensions, with options to specify weights, masks, and normalization.
See Averaging vs. Concatenating, for a description of the
distinctions between the various averagers and concatenators.
The default behavior of ncwa is to arithmetically average
every numerical variable over all dimensions and produce a scalar
result.
To average variables over only a subset of their dimensions, specify
these dimensions in a comma-separated list following `-a', e.g.,
`-a time,lat,lon'.
As with all arithmetic operators, the operation may be restricted to
an arbitrary hypserslab by employing the `-d' option
(see Hyperslabs).
ncwa also handles values matching the variable's
missing_value attribute correctly.
Moreover, ncwa understands how to manipulate user-specified
weights, masks, and normalization options.
With these options, ncwa can compute sophisticated averages
(and integrals) from the command line.
mask_var and weight, if specified, are broadcast to conform to the variables being averaged. The rank of variables is reduced by the number of dimensions which they are averaged over. Thus arrays which are one dimensional in the input-file and are averaged by ncwa appear in the output-file as scalars. This allows the user to infer which dimensions may have been averaged. Note that that it is impossible for ncwa to make make a weight or mask_var of rank W conform to a var of rank V if W > V. This situation often arises when coordinate variables (which, by definition, are one dimensional) are weighted and averaged. ncwa assumes you know this is impossible and so ncwa does not attempt to broadcast weight or mask_var to conform to var in this case, nor does ncwa print a warning message telling you this, because it is so common. Specifying dbg > 2 does cause ncwa to emit warnings in these situations, however.
Non-coordinate variables are always masked and weighted if specified.
Coordinate variables, however, may be treated specially.
By default, an averaged coordinate variable, e.g., latitude,
appears in output-file averaged the same way as any other variable
containing an averaged dimension.
In other words, by default ncwa weights and masks
coordinate variables like all other variables.
This design decision was intended to be helpful but for some
applications it may be preferable not to weight or mask coordinate
variables just like all other variables.
Consider the following arguments to ncwa:
-a latitude -w lat_wgt -d latitude,0.,90. where lat_wgt is
a weight in the latitude dimension.
Since, by default ncwa weights coordinate variables, the
value of latitude in the output-file depends on the weights
in lat_wgt and is not likely to be 45.0, the midpoint latitude
of the hyperslab.
Option `-I' overrides this default behavior and causes
ncwa not to weight or mask coordinate variables
37.
In the above case, this causes the value of latitude in the
output-file to be 45.0, an appealing result.
Thus, `-I' specifies simple arithmetic averages for the coordinate
variables.
In the case of latitude, `-I' specifies that you prefer to archive
the central latitude of the hyperslab over which variables were averaged
rather than the area weighted centroid of the hyperslab
38.
The mathematical definition of operations involving rank reduction
is given above (see Operation Types).
The mask condition has the syntax mask_var condition mask_val. Here mask_var is the name of the masking variable (specified with `-m', `--mask-variable', `--mask_variable', `--msk_nm', or `--msk_var'). The truth condition argument (specified with `-T', `--truth_condition', `--msk_cmp_typ', or `--op_rlt' may be any one of the six arithmetic comparatives: eq, ne, gt, lt, ge, le.
These are the Fortran-style character abbreviations for the logical operations ==, !=, >, <, >=,
The mask condition defaults to eq (equality). The mask_val argument to `-M' (or `--mask-value', or `--msk_val') is the right hand side of the mask condition. Thus for the i'th element of the hyperslab to be averaged, the mask condition is
mask(i) condition mask_val.
ncwa has one switch which controls the normalization of the averages appearing in the output-file. Short option `-N' (or long options `--nmr' or `--numerator') prevents ncwa from dividing the weighted sum of the variable (the numerator in the averaging expression) by the weighted sum of the weights (the denominator in the averaging expression). Thus `-N' tells ncwa to return just the numerator of the arithmetic expression defining the operation (see Operation Types).
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
Every variable in in.nc is reduced to a scalar in out.nc because, by default, averaging is performed over all dimensions.
Store the zonal (longitudinal) mean of in.nc in out.nc:
ncwa -a lon in.nc out.nc
Here the tally is simply the size of lon, or 128.
Compute the meridional (latitudinal) mean, with values weighted by the corresponding element of gw 39:
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
Here the tally is
64 times 128 = 8192.
Compute the area mean over the globe, but include only points for which
ORO < 0.5
40:
ncwa -m ORO -M 0.5 -T lt -w gw -a lat,lon in.nc out.nc
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 -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
Determine the total area of the maritime tropical Pacific, assuming the variable area contains the area of each gridcell
ncwa -N -v area -m ORO -M 0.5 -T lt -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 missing_value 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 -m ${msk_var} -T le -M ${thr_max} out.nc out.nc
ncecat -O out.nc out.nc # Wrap out.nc in degenerate "record" dimension
ncwa -O -a record -m ${msk_var} -T ge -M ${thr_min} out.nc out.nc
After the first use of ncwa, out.nc contains
missing_value where ${msk_var} >= ${thr_max}.
The process is then repeated on the remaining data to filter out
points where ${msk_var} <= ${thr_min}.
The resulting out.nc contains valid data only
where thr_min <= msk_var <= thr_max.
We welcome contributions from anyone. The NCO project homepage at https://sf.net/projects/nco contains more information on how to contribute.
Financial contributions to NCO development may be made through PayPal. NCO has been shared for almost 10 years yet no one has ever contributed any money to the developers 41. So you could be the first!
The primary contributors to NCO development are:
min(), max(), total()
support in ncra and ncwa.
Type conversion for arithmetic.
Migration to netCDF3 API.
ncap parser, lexer, and I/O.
Multislabbing algorithm.
Variable wildcarding.
Various hacks.
NSF has funded a project to improve Distributed Data Reduction & Analysis (DDRA) by evolving NCO into a suite of Scientific Data Operators called SDO. The two main components of this project are NCO parallelism (OpenMP, MPI) and Server-Side DDRA (SSDDRA) implemented through extensions to OPeNDAP and netCDF4. This project will dramatically reduce bandwidth usage for NCO DDRA.
With this first NCO proposal funded, the content of the next NCO proposal is clear. We are interested in obtaining NASA support for HDF-specific enhancements to NCO. We plan to submit a proposal to the next suitable NASA NRA or NSF opportunity.
We are considering a lot of interesting ideas for still more proposals. Please contact us if you wish to be involved with any future NCO-related proposals. Comments on the proposals and letters of support are also very welcome.
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filessubtract: ncbo netCDF Binary Operatortime: ARM Conventionstime: NCAR CCSM Conventionstime: UDUnits Supporttime_offset: ARM Conventionsttl: Operation Typesulimit: Large Datasets and Memoryunits: ncflint netCDF File Interpolatorunits: ncatted netCDF Attribute Editorunits: UDUnits SupportUSE_FORTRAN_ARITHMETIC: Windows Operating SystemWIN32: Windows Operating System| (wildcard character): Variable subsetting[1]
To produce these formats, nco.texi was simply run through the
freely available programs texi2dvi, dvips,
texi2html, and makeinfo.
Due to a bug in TeX, the resulting Postscript file, nco.ps,
contains the Table of Contents as the final pages.
Thus if you print nco.ps, remember to insert the Table of
Contents after the cover sheet before you staple the manual.
[2] The `_BSD_SOURCE' token is required on some Linux platforms where gcc dislikes the network header files like netinet/in.h).
[3] NCO may still build with an
ANSI or ISO C89 or C94/95-compliant compiler if the
C pre-processor undefines the restrict type qualifier, e.g.,
by invoking the compiler with `-Drestrict='''.
[4] The Cygwin package is available from
http://sourceware.redhat.com/cygwin
Currently, Cygwin 20.x comes with the GNU C/C++/Fortran
compilers (gcc, g++, g77).
These GNU compilers may be used to build the netCDF
distribution itself.
[5] The ldd command, if it is available on your system,
will tell you where the executable is looking for each dynamically
loaded library. Use, e.g., ldd `which ncea`.
[6] The Hierarchical Data Format, or HDF, is another self-describing data format similar to, but more elaborate than, netCDF.
[7] One must link the NCO code to the HDF4 MFHDF library instead of the usual netCDF library. Does `MF' stands for Mike Folk? Perhaps. In any case, the MFHDF library only supports netCDF 2.x calls. Thus I will try to keep this capability in NCO as long as it is not too much trouble.
[8] The ncrename operator is an exception to this rule. See ncrename netCDF Renamer.
[9] The terminology merging is reserved for an (unwritten) operator which replaces hyperslabs of a variable in one file with hyperslabs of the same variable from another file
[10] Yes, the terminology is confusing. By all means mail me if you think of a better nomenclature. Should NCO use paste instead of append?
[11] Currently ncea and ncrcat are symbolically linked to the ncra executable, which behaves slightly differently based on its invocation name (i.e., `argv[0]'). These three operators share the same source code, but merely have different inner loops.
[12] The third averaging operator, ncwa, is the most sophisticated averager in NCO. However, ncwa is in a different class than ncra and ncea because it can only operate on a single file per invocation (as opposed to multiple files). On that single file, however, ncwa provides a richer set of averaging options—including weighting, masking, and broadcasting.
[13] The exact length which exceeds the operating system internal
limit for command line lengths varies from OS to OS
and from shell to shell.
GNU bash may not have any arbitrary fixed limits to the
size of command line arguments.
Many OSs cannot handle command line arguments (including
results of file globbing) exceeding 4096 characters.
[14] If a getopt_long function cannot be found on the system, NCO will use the getopt_long from the my_getopt package by Benjamin Sittler bsittler@iname.com. This is BSD-licensed software available from http://www.geocities.com/ResearchTriangle/Node/9405/#my_getopt.
[15] The `-n' option is a backward compatible superset of the
NINTAP option from the NCAR CCM Processor.
[16] The msrcp command must be in the user's path and
located in one of the following directories: /usr/local/bin,
/usr/bin, /opt/local/bin, or /usr/local/dcs/bin.
[17] DODS is being deprecated because it is ambiguous, referring both to a protocol and to a collection of (oceanography) data. It is superceded by two terms. DAP is the discipline-neutral Data Access Protocol at the heart of DODS. The National Virtual Ocean Data System (NVODS) refers to the collection of oceanography data and oceanographic extensions to DAP. In other words, NVODS is implemented with OPeNDAP. OPeNDAP is also the open source project which maintains, develops, and promulgates the DAP standard. OPeNDAP and DAP really are interchangeable. Got it yet?
[18] Automagic support for DODS/OPeNDAP version 3.2.x was deprecated in December, 2003 with NCO 2.8.4. NCO now supports DODS/OPeNDAP version 3.4.x.
[19] The minimal set of libraries required to build NCO as DODS/OPeNDAP clients are DODS-dap-3.4.x, DODS-nc3-dods-3.4.5, and DODS-packages-3.4.x.
[20] We are most familiar with the DODS/OPeNDAP ability to enable network-transparent data access. DODS/OPeNDAP has many other features, including sophisticated hyperslabbing and server-side processing via constraint expressions. If you know more about this, please consider writing a section on "DODS/OPeNDAP Capabilities of Interest to NCO Users" for incorporation in the NCO User's Guide.
[21] For example, the DOE ARM program often
uses att_type = NC_CHAR and missing_value =
`-99999.'.
[22]
32767 = 2^15−1
[23] Operators began performing type conversions before arithmetic in NCO version 1.2, August, 2000. Previous versions never performed unnecessary type conversion for arithmetic.
[24]
The actual type conversions are handled by intrinsic C-language type
conversion, so the floor() function is not explicitly called,
though the results would be the same if it were.
[25]
The exception is appending/altering the attributes x_op,
y_op, z_op, and t_op for variables which have been
averaged across space and time dimensions.
This feature is scheduled for future inclusion in NCO.
[26]
The CCSM convention recommends time be stored in the format
time since base_time, e.g., the units attribute of
time might be `days since 1992-10-8 15:15:42.5 -6:00'.
A problem with this format occurs when using ncrcat to
concatenate multiple files together, each with a different
base_time.
That is, any time values from files following the first file to
be concatenated should be corrected to the base_time offset
specified in the units attribute of time from the first
file.
The analogous problem has been fixed in ARM files
(see ARM Conventions) and could be fixed for CCSM files if
there is sufficient lobbying.
[27] Although not a part of the standard, NCO enforces
the policy that the missing_value attribute, if any, of a packed
variable is also stored at the original precision.
[28]
ANSI C compilers are guaranteed to support double precision versions
of these functions.
These functions normally operate on netCDF variables of type NC_DOUBLE
without having to perform intrinsic conversions.
For example, ANSI compilers provide sin for the sine of C-type
double variables.
The ANSI standard does not require, but many compilers provide,
an extended set of mathematical functions that apply to single
(float) and quadruple (long double) precision variables.
Using these functions (e.g., sinf for float,
sinl for long double), when available, is more efficient
than casting variables to type double, performing the operation,
and then recasting.
NCO uses the faster intrinsic functions when they are
available, and uses the casting method when they are not.
[29] Linux supports more of these intrinsic functions than other OSs.
[30] A naked (i.e., unprotected or unquoted) `*' is a wildcard character. A naked `-' may confuse the command line parser. A naked `+' and `/' are relatively harmless.
[31] The widely used shell Bash correctly interprets all these special characters even when they are not quoted. That is, Bash does not prevent NCO from correctly interpreting the intended arithmetic operation when the following arguments are given (without quotes) to ncbo: `--op_typ=+', `--op_typ=-', `--op_typ=*', and `--op_typ=/'
[32] The command to do this is `ln -s -f ncbo ncadd'
[33] The command to do this is `alias ncadd='ncbo --op_typ=add''
[34] This is because ncra collapses the record dimension to a size of 1 (making it a degenerate dimension), but does not remove it, while ncwa removes all dimensions it averages over. In other words, ncra changes the size but not the rank of variables, while ncwa changes both the size and the rank of variables.
[35] Those familiar with netCDF mechanics might wish to know what is happening here: ncks does not attempt to redefine the variable in output-file to match its definition in input-file, ncks merely copies the values of the variable and its coordinate dimensions, if any, from input-file to output-file.
[36] This limitation, imposed by the netCDF storage layer, may be relaxed in the future with netCDF4.
[37] The default behavior of (`-I') changed on 1998/12/01—before this date the default was not to weight or mask coordinate variables.
[38] If lat_wgt contains Gaussian weights then the value of
latitude in the output-file will be the area-weighted
centroid of the hyperslab.
For the example given, this is about 30 degrees.
[39] gw stands for Gaussian weight in the
NCAR climate model.
[40] ORO stands for Orography in the NCAR
climate model.
ORO < 0.5 selects the gridpoints which are covered by
ocean.
[41] Happy users have sent me a few gifts, though. This includes a box of imported chocolate. Mmm. Appreciation and gifts are definitely better than money. Naturally, I'm too lazy to split and send gifts to the other developers. However, unlike some NCO developers, I have a high-paying "real job". My intention is to split monetary donations among the active developers and to send them their shares via PayPal.