Abstract
Abstract. The CF (Climate and Forecast) metadata conventions are designed to promote the creation, processing, and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. The CF conventions provide a description of the physical meaning of data and of their spatial and temporal properties, but they depend on the netCDF file encoding which can currently only be fully understood and interpreted by someone familiar with the rules and relationships specified in the conventions documentation. To aid in development of CF-compliant software and to capture with a minimal set of elements all of the information contained in the CF conventions, we propose a formal data model for CF which is independent of netCDF and describes all possible CF-compliant data. Because such data will often be analysed and visualised using software based on other data models, we compare our CF data model with the ISO 19123 coverage model, the Open Geospatial Consortium CF netCDF standard, and the Unidata Common Data Model. To demonstrate that this CF data model can in fact be implemented, we present cf-python, a Python software library that conforms to the model and can manipulate any CF-compliant dataset.
Highlights
Network Common Data Form supports a view of data as a collection of self-describing, portable objects that can be accessed through standardised software libraries
Since CF introduces other types of variables for coordinate data, we sometimes refer to the kind defined in the Network Common Data Form (netCDF) user guide as a coordinate variable “in the NUG sense”. (By the phrase “coordinate variable”, the CF standard document consistently means “coordinate variable in the NUG sense”.) We describe the various kinds of coordinate variables in more detail later (Sect. 3.3)
We have described the CF conventions in terms of their relationship to the physical world and in terms of their netCDF encoding, and these steps led to our identifying the elements which contribute to a CF data model
Summary
Network Common Data Form (netCDF) supports a view of data as a collection of self-describing, portable objects that can be accessed through standardised software libraries. As well as others, it has become a popular way to create, access, and share array-orientated scientific data (Rew and Davis, 1990; Rew et al, 2006). In this context, “self-describing” means that a file contains, for each data array, an associated description of what it represents scientifically, i.e. metadata. CF was developed for gridded data from climate and forecast models of the atmosphere and ocean, but its use has subsequently extended to other geosciences, and to observations as well as numerical models. The use of CF is recommended where applicable by Unidata
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