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| CDO (Climate Data Operators) | |
|---|---|
| Name | CDO (Climate Data Operators) |
| Programming language | C, Fortran |
| Operating system | Unix-like, Microsoft Windows |
| Genre | Data processing, Meteorology, Climatology |
| License | GNU General Public License |
CDO (Climate Data Operators) is a command-line suite for manipulating and analyzing climate and weather data, widely used in meteorology, climatology, and oceanography research workflows. It provides tools to process large gridded datasets produced by models and observations, integrating with ecosystems around NetCDF, GRIB, and CF Convention-compliant archives. Developed and maintained by contributors from research institutes and national laboratories, it is a common component in pipelines alongside tools from European Centre for Medium-Range Weather Forecasts, National Centers for Environmental Prediction, and university groups.
CDO began as a pragmatic toolkit to address the needs of researchers working with output from general circulation models such as those used in the Intergovernmental Panel on Climate Change assessment cycles and reanalysis projects like ERA5 and NCEP/NCAR Reanalysis. It is designed for interoperability with community standards including NetCDF, GRIB, and CF Convention conventions, and is frequently deployed on high-performance computing systems operated by institutions such as Lawrence Berkeley National Laboratory, Max Planck Institute for Meteorology, and national supercomputing centers. Its user base spans research groups at universities like University of Oxford, Massachusetts Institute of Technology, and ETH Zurich, as well as operational centers like ECMWF and NOAA.
CDO implements a rich set of operations: arithmetic, statistical aggregation, regridding, selection, and temporal/spatial manipulation. Typical functions mirror scientific tasks performed in projects associated with Coupled Model Intercomparison Project, Paleoclimate Modelling Intercomparison Project, and observational synthesis efforts led by organizations such as World Meteorological Organization and Global Climate Observing System. It supports metadata handling consistent with CF Convention and integrates with pipelines that include tools from NCAR Command Language, Python libraries like xarray, and visualization systems linked to Matplotlib, ParaView, and NCL. CDO’s operators cover zonal and meridional statistics, vertical level interpolation relevant to ECMWF Reanalysis, and ensemble operations used by groups at Met Office and Los Alamos National Laboratory.
CDO reads and writes multiple scientific file formats common in climate science, notably NetCDF (classic and enhanced), GRIB (GRIB1 and GRIB2), and packed arrays used in legacy archives. It understands conventions used by datasets produced by centers like ECMWF, EUMETSAT, JMA, and CFSR archives, and supports CF-compliant metadata for interoperability with repositories such as PANGAEA and Zenodo. Bindings and converters used in workflows connect CDO to tools from Unidata, OpenDAP, and archive systems maintained by NASA missions and Copernicus services. Support for coordinate systems and projections links to standards from EPSG registry and datasets produced by MODIS, AVHRR, and TRMM.
CDO exposes more than a hundred operators invoked via a compact command-line syntax that chains operations in pipelines similar to those used with Unix utilities and tools in the POSIX tradition. Commands follow patterns compatible with shell environments such as Bash, Zsh, and job schedulers on clusters like SLURM or PBS. Users combine operators for tasks common to projects at CSIRO and Scripps Institution of Oceanography, for example temporal averaging for CMIP diagnostics or spatial remapping to grids used by GFDL model output. Integration with scripting languages such as Perl, Ruby, and Python enables automation in reproducible workflows endorsed by initiatives like ReproZip and community software carpentry training programs.
CDO is applied to preprocess model output for intercomparison projects like CMIP6, compute climate indices referenced in reports by IPCC, and process satellite retrievals for assimilation in systems developed by NOAA and ECMWF. It supports hydrological analyses relevant to studies from IPBES and flood forecasting systems used by national meteorological services. In academic settings at ETH Zurich, University of Cambridge, and Princeton University, CDO is used to generate diagnostic fields, perform bias correction workflows utilized by World Bank climate risk analyses, and prepare inputs for impact models developed by groups at IIASA and Potsdam Institute for Climate Impact Research.
CDO is distributed under the GNU General Public License and maintained by a distributed team of contributors affiliated with European and North American research centers, academic groups, and national meteorological agencies. Source code and releases are packaged for major Linux distributions such as Debian, Ubuntu, and Fedora, and are available via package managers used in research computing environments at CERN and national labs. The project follows community practices for open-source development promoted by organizations like OSI and engages with standards bodies such as CF Convention maintainers and NetCDF developers.
CDO is optimized for large gridded datasets and supports parallel execution modes to exploit multi-core and cluster infrastructures used at NERSC, Jülich Supercomputing Centre, and other HPC centers. It can be combined with MPI-based workflows and batch systems deployed at PRACE and is often used in concert with parallel I/O libraries developed by Unidata and HDF Group to handle high-throughput scenarios typical of CMIP ensemble processing and reanalysis production. Performance tuning commonly involves co-design with storage systems and scheduler configurations found in national computing facilities such as XSEDE and ARCHER.
Category:Climate data processing tools