<p>I second <a href="http://meteora.ucsd.edu/~pierce/ncview_home_page.html">ncview</a> for taking a quick look at NetCDF files.</p>

<p>I would also recommend trying Unidata's <a href="http://www.unidata.ucar.edu/software/idv/">Integrated Data Viewer (IDV)</a>. It is great for overlaying geophysical fields in 3-D from different sources. Besides NetCDF, it supports many other formats. It also comes with a pre-loaded listing of various observational and model data repositories through THREDDS and OpenDAP. IDV also lets you to define functions and operations between fields on different grids or projections. Note that IDV is not good for serious analysis in my opinion, but is more suitable for exploring datasets visually.</p>

CC BY-SA 3.0
2014-04-23T03:52:58.770Z
2014-04-23T03:52:58.770Z
milancurcic
<p>Just to add my point of view; </p>

<ol>
<li>Using ncks you can do many things, i.e. differentiate, get
ratio, extract some vars, slice on the dimension etc..</li>
<li>If you want to make some binary operations on netcdf files consider ncbo. For huge files I prefer to cut down what I want at the first place, it does opendap remote as well. </li>
<li>Hate matlab so I moved to NCL <a href="http://www.ncl.ucar.edu/" rel="nofollow">(NCAR)</a>
which is straight forward and has many scripts already prepared for most <a href="http://www.ncl.ucar.edu/Applications/list_models.shtml" rel="nofollow">common models</a> . 
No need to tell it is producing publication quality figures ;)</li>
<li>There is portion of the lib for python (pyNGL), the same syntax so once when familiar with ncl easy to use it in python as well, support for other formats like grib, hdf, ... </li>
</ol>

CC BY-SA 3.0
2014-04-23T07:04:39.570Z
2016-10-01T15:12:15.023Z
2016-10-01T15:12:15.023Z
ivica
<p>Normally I use the following softwares for a quick view of my NetCDF files:</p>

<ol>
<li>NASA Panoply (<a href="http://www.giss.nasa.gov/tools/panoply/" rel="nofollow">Panoply netCDF, HDF and GRIB Data Viewer</a>): java based, very good in opening HDF, NetCDF, GRIBs...</li>
<li>CDO functions as shaded, contour, etc. (very basic but useful from command-line)</li>
<li>MATLAB and R with their basic functions</li>
</ol>

CC BY-SA 3.0
2014-04-22T07:29:32.560Z
2016-10-02T09:25:53.267Z
2016-10-02T09:25:53.267Z
Matteo De Felice
<p>For very quick visual comparison I would use <a href="http://scitools.github.io/cube_browser" rel="nofollow">Cube Browser</a> or <a href="http://meteora.ucsd.edu/~pierce/ncview_home_page.html" rel="nofollow">ncview</a> together with a command line tool like the <a href="https://code.zmaw.de/projects/cdo/wiki" rel="nofollow">Climate Data Operators</a>. For quick production of nice looking graphics (and animations) <a href="http://www.giss.nasa.gov/tools/panoply/" rel="nofollow">Panoply</a> really makes good job. For further analysis or special graphics keep following your approach and script with things like <a href="http://www.mathworks.com/products/matlab" rel="nofollow">MATLAB</a>, <a href="https://www.python.org/" rel="nofollow">Python</a> (e.g. with <a href="http://scitools.org.uk/iris/" rel="nofollow">Iris</a>), <a href="http://www.exelisvis.com/IDL" rel="nofollow">IDL</a>, <a href="https://www.r-project.org" rel="nofollow">R</a>, <a href="https://www.ncl.ucar.edu/" rel="nofollow">ncl</a> or whatever people around you are using.</p>

CC BY-SA 3.0
2014-04-22T05:33:00.697Z
2016-06-15T17:35:22.663Z
2016-06-15T17:35:22.663Z
BHF
<p>Using Matlab, you can do ncgeodataset (<a href="http://code.google.com/p/nctoolbox/wiki/ncgeodataset" rel="nofollow">http://code.google.com/p/nctoolbox/wiki/ncgeodataset</a>) to subsample the netcdf without having to download large datasets. </p>

<p>For instance, </p>

<pre><code>nc = ncgeodataset('http://thredds.jpl.nasa.gov/thredds/dodsC/ncml_aggregation/OceanTemperature/ghrsst/aggregate__ghrsst_JPL_OUROCEAN-L4UHfnd-GLOB-G1SST_OI.ncml'); 
gvar = nc.geovariable('analysed_sst'); 
s.time={'20-May-2012', '24-May-2012'}; 
s.lat=[40 41.5]; 
s.lon=[0 2.0]; 
sub = gvar.geosubset(s); % Subset method 
pcolor(sub.grid.lon,sub.grid.lat,double(squeeze(sub.data(1,:,:)))-273.15);
</code></pre>

CC BY-SA 3.0
2015-01-26T20:30:16.167Z
2015-01-27T07:32:52.703Z
2015-01-27T07:32:52.703Z
arkaia
<p>While I don't know the specifics of ocean modeling, unless there there is a "standard" in which nodes are organized and written (Ie X,Y,Z), there will always be coding required. Furthermore, the way a a data file is written always depends on how tasks in the model are delegated to the processor: Is the model designed to be run on a personal PC or a Beowulf Cluster? </p>

<p>You might be able to use something such as <a href="http://www.opendx.org/" rel="nofollow">OpenDx</a>, to compare ocean modeling results, though I still think that a quick python script would be in order to properly format all data types.  </p>

CC BY-SA 3.0
2014-04-23T00:57:03.457Z
@defitos not really agnostic, since they suggest using CF
Abe
CC BY-SA 3.0
2014-04-16T17:58:20.873Z
I guess netcdf aspires to be that standard... but it seems to have limited acceptance amongst software vendors as yet.
Semidiurnal Simon
CC BY-SA 3.0
2014-04-16T22:03:40.143Z
@SimonW, I think it's CF that aspires to be the metadata standard for Earth science variables.  NetCDF is more of a content-agnostic container format.
Deditos
CC BY-SA 3.0
2014-04-16T17:47:51.903Z
2014-04-16T17:47:51.903Z
Neo
<p>The writers of netCDF, <a href="http://www.unidata.ucar.edu">UNIDATA</a>, maintain a <a href="http://www.unidata.ucar.edu/software/netcdf/software.html">pretty extensive list</a> of visualisation software on the netCDF website.  It even mentions an Excel add-in, for the masochistic, presumably.</p>

<p>Over the years, I've found <a href="http://ferret.pmel.noaa.gov/Ferret/">Ferret</a> to be reliable with CF compliant files (and non-compliant ones, for that matter) and useful for interactive quick looks and simple manipulations.  It understands, for example, the CF-recommended UDUNITS time format and will automatically apply <code>scale_factor</code> and <code>add_offset</code> attributes to variables.  It's certainly quicker to get something on screen than the Python/R/Matlab route that I usually take for presentation and publication quality plots.</p>

<p>If you're after a more GUI-like viewer, then I've heard good things about <a href="http://www.giss.nasa.gov/tools/panoply/">Panoply</a>, although I must admit I've never used it myself.</p>

CC BY-SA 3.0
2016-07-21T18:59:48.997Z
Thank you for pointing to the list of software. I found the [ncBrowse](http://www.epic.noaa.gov/java/ncBrowse/) to have the easiest point-and-click interface amongst the ones I tried.
ZZZ
CC BY-SA 3.0
2014-04-16T21:55:37.347Z
2014-04-16T21:55:37.347Z
Deditos
<p>I am writing my own MATLAB scripts to do most of the visualization and data analysis of model results. I wonder if there is a quicker way for visual comparison of simulation results gained from different ocean modeling systems. Is there a (preferably free) software package that works with CF (<a href="http://en.wikipedia.org/wiki/Climate_and_Forecast_Metadata_Conventions">Climate and Forecast Metadata Conventions</a>) compliant NetCDF model output directly or is always some coding required? </p>

CC BY-SA 3.0
2014-04-19T07:36:21.467Z
I disagree about this being one for Software Recommendations - the overarching question isn't so much "what software should I use" as "What's a quick and easy way to compare these oceanographic data sets". I think that if the question was edited to change the emphasis as such, it would fairly clearly be valid here. It *may* be a little broad, but I think it could be fixed with a little editing - perhaps an example of the problem to be solved.
Semidiurnal Simon
CC BY-SA 3.0
2014-04-17T05:07:27.413Z
@bhf ah, thanks. Looks like maybe that is a climate-science-specific thing at present, though if it could spread to other areas of ocean & atmospheric science it could only be a good thing...
Semidiurnal Simon
CC BY-SA 3.0
2014-04-17T07:42:14.183Z
Please don't ask shopping /recommendation questions here. Try [softwarerecs.se]
410 gone
<ocean><oceanography><models><software><netcdf>
What tools allow a quick comparison of NetCDF output from ocean models?
ZZZ
# What tools allow a quick comparison of NetCDF output from ocean models?

(Asked by: username_0 on 2014-04-16)

I am writing my own MATLAB scripts to do most of the visualization and data analysis of model results. I wonder if there is a quicker way for visual comparison of simulation results gained from different ocean modeling systems. Is there a (preferably free) software package that works with CF ([Climate and Forecast Metadata Conventions](http://en.wikipedia.org/wiki/Climate_and_Forecast_Metadata_Conventions)) compliant NetCDF model output directly or is always some coding required?

**Tags:** ocean, oceanography, models, software, netcdf

> **Comments:**
> **username_1**: @bhf ah, thanks. Looks like maybe that is a climate-science-specific thing at present, though if it could spread to other areas of ocean & atmospheric science it could only be a good thing...  
> **username_2**: Please don't ask shopping /recommendation questions here. Try [softwarerecs.se]  
> **username_1**: I disagree about this being one for Software Recommendations - the overarching question isn't so much "what software should I use" as "What's a quick and easy way to compare these oceanographic data sets". I think that if the question was edited to change the emphasis as such, it would fairly clearly be valid here. It *may* be a little broad, but I think it could be fixed with a little editing - perhaps an example of the problem to be solved.  

---

## 7 answers

### Answer by username_10 on 2014-04-16. Score: 18 | Accepted answer

The writers of netCDF, [UNIDATA](http://www.unidata.ucar.edu), maintain a [pretty extensive list](http://www.unidata.ucar.edu/software/netcdf/software.html) of visualisation software on the netCDF website. It even mentions an Excel add-in, for the masochistic, presumably.

Over the years, I've found [Ferret](http://ferret.pmel.noaa.gov/Ferret/) to be reliable with CF compliant files (and non-compliant ones, for that matter) and useful for interactive quick looks and simple manipulations. It understands, for example, the CF-recommended UDUNITS time format and will automatically apply `scale_factor` and `add_offset` attributes to variables. It's certainly quicker to get something on screen than the Python/R/Matlab route that I usually take for presentation and publication quality plots.

If you're after a more GUI-like viewer, then I've heard good things about [Panoply](http://www.giss.nasa.gov/tools/panoply/), although I must admit I've never used it myself.

> **Comments:**
> **username_0**: Thank you for pointing to the list of software. I found the [ncBrowse](http://www.epic.noaa.gov/java/ncBrowse/) to have the easiest point-and-click interface amongst the ones I tried.  

---

### Answer by username_6 on 2014-04-22. Score: 20

For very quick visual comparison I would use [Cube Browser](http://scitools.github.io/cube_browser) or [ncview](http://meteora.ucsd.edu/~pierce/ncview_home_page.html) together with a command line tool like the [Climate Data Operators](https://code.zmaw.de/projects/cdo/wiki). For quick production of nice looking graphics (and animations) [Panoply](http://www.giss.nasa.gov/tools/panoply/) really makes good job. For further analysis or special graphics keep following your approach and script with things like [MATLAB](http://www.mathworks.com/products/matlab), [Python](https://www.python.org/) (e.g. with [Iris](http://scitools.org.uk/iris/)), [IDL](http://www.exelisvis.com/IDL), [R](https://www.r-project.org), [ncl](https://www.ncl.ucar.edu/) or whatever people around you are using.


---

### Answer by username_3 on 2014-04-23. Score: 13

I second [ncview](http://meteora.ucsd.edu/~pierce/ncview_home_page.html) for taking a quick look at NetCDF files.

I would also recommend trying Unidata's [Integrated Data Viewer (IDV)](http://www.unidata.ucar.edu/software/idv/). It is great for overlaying geophysical fields in 3-D from different sources. Besides NetCDF, it supports many other formats. It also comes with a pre-loaded listing of various observational and model data repositories through THREDDS and OpenDAP. IDV also lets you to define functions and operations between fields on different grids or projections. Note that IDV is not good for serious analysis in my opinion, but is more suitable for exploring datasets visually.


---

### Answer by username_4 on 2014-04-23. Score: 12

Just to add my point of view;

1. Using ncks you can do many things, i.e. differentiate, get
   ratio, extract some vars, slice on the dimension etc..
2. If you want to make some binary operations on netcdf files consider ncbo. For huge files I prefer to cut down what I want at the first place, it does opendap remote as well.
3. Hate matlab so I moved to NCL [(NCAR)](http://www.ncl.ucar.edu/)
   which is straight forward and has many scripts already prepared for most [common models](http://www.ncl.ucar.edu/Applications/list_models.shtml) .
   No need to tell it is producing publication quality figures ;)
4. There is portion of the lib for python (pyNGL), the same syntax so once when familiar with ncl easy to use it in python as well, support for other formats like grib, hdf, ...


---

### Answer by username_5 on 2014-04-22. Score: 11

Normally I use the following softwares for a quick view of my NetCDF files:

1. NASA Panoply ([Panoply netCDF, HDF and GRIB Data Viewer](http://www.giss.nasa.gov/tools/panoply/)): java based, very good in opening HDF, NetCDF, GRIBs...
2. CDO functions as shaded, contour, etc. (very basic but useful from command-line)
3. MATLAB and R with their basic functions


---

### Answer by username_7 on 2015-01-26. Score: 6

Using Matlab, you can do ncgeodataset (<http://code.google.com/p/nctoolbox/wiki/ncgeodataset>) to subsample the netcdf without having to download large datasets.

For instance,

```
nc = ncgeodataset('http://thredds.jpl.nasa.gov/thredds/dodsC/ncml_aggregation/OceanTemperature/ghrsst/aggregate__ghrsst_JPL_OUROCEAN-L4UHfnd-GLOB-G1SST_OI.ncml'); 
gvar = nc.geovariable('analysed_sst'); 
s.time={'20-May-2012', '24-May-2012'}; 
s.lat=[40 41.5]; 
s.lon=[0 2.0]; 
sub = gvar.geosubset(s); % Subset method 
pcolor(sub.grid.lon,sub.grid.lat,double(squeeze(sub.data(1,:,:)))-273.15);

```


---

### Answer by username_8 on 2014-04-16. Score: 4

While I don't know the specifics of ocean modeling, unless there there is a "standard" in which nodes are organized and written (Ie X,Y,Z), there will always be coding required. Furthermore, the way a a data file is written always depends on how tasks in the model are delegated to the processor: Is the model designed to be run on a personal PC or a Beowulf Cluster?

You might be able to use something such as [OpenDx](http://www.opendx.org/), to compare ocean modeling results, though I still think that a quick python script would be in order to properly format all data types.

> **Comments:**
> **username_1**: I guess netcdf aspires to be that standard... but it seems to have limited acceptance amongst software vendors as yet.  
> **username_10**: @SimonW, I think it's CF that aspires to be the metadata standard for Earth science variables.  NetCDF is more of a content-agnostic container format.  
> **username_9**: @defitos not really agnostic, since they suggest using CF  

---

