.. include:: ../common_links.inc .. _glossary: Glossary ============= .. glossary:: Cartopy A python package for producing maps, and other geospatial data. Allows plotting on these maps, over a range of projections. | **Related:** :term:`Matplotlib` | **More information:** `CartoPy Site `_ | CF Conventions Rules for storing meteorological Climate and Forecast data in :term:`NetCDF Format` files, defining a standard metadata format to describe what the data is. This also forms the data model which iris is based on. | **Related:** :term:`NetCDF Format` | **More information:** `CF Conventions `_ | Coordinate A container for data points, comes in three main flavours. - Dimensional Coordinate - A coordinate that describes a single data dimension of a cube. They can only contain numerical values, in a sorted order (ascending or descending). - Auxiliary Coordinate - A coordinate that can map to multiple data dimensions. Can contain any type of data. - Scalar Coordinate - A coordinate that is not mapped to any data dimension, instead representing the cube as a whole. | **Related:** :term:`Cube` | **More information:** :doc:`iris_cubes` | Cube Cubes are the main method of storing data in Iris. A cube can consist of: - Array of :term:`Phenomenon` Data (Required) - :term:`Coordinates ` - :term:`Standard Name` - :term:`Long Name` - :term:`Unit` - :term:`Cell Methods ` - :term:`Coordinate Factories ` | **Related:** :term:`NumPy` | **More information:** :doc:`iris_cubes` | Cell Method A cell method represents that a cube's data has been derived from a past statistical operation, such as a MEAN or SUM operation. | **Related:** :term:`Cube` | **More information:** :doc:`iris_cubes` | Coordinate Factory A coordinate factory derives coordinates (sometimes referred to as derived coordinates) from the values of existing coordinates. E.g. A hybrid height factory might use "height above sea level" and "height at ground level" coordinate data to calculate a "height above ground level" coordinate. | **Related:** :term:`Cube` | **More information:** :doc:`iris_cubes` | Dask A data analytics python library. Iris predominantly uses Dask Arrays; a collection of NumPy-esque arrays. The data is operated in batches, so that not all data is in RAM at once. | **Related:** :term:`Lazy Data` **|** :term:`NumPy` | **More information:** :doc:`real_and_lazy_data` | Fields File (FF) Format A meteorological file format, the output of the Unified Model. | **Related:** :term:`GRIB Format` **|** :term:`Post Processing (PP) Format` **|** :term:`NetCDF Format` | **More information:** `Unified Model `_ | GRIB Format A WMO-standard meteorological file format. | **Related:** :term:`Fields File (FF) Format` **|** :term:`Post Processing (PP) Format` **|** :term:`NetCDF Format` | **More information:** `GRIB 1 User Guide `_ **|** `GRIB 2 User Guide.pdf `_ | Lazy Data Data stored in hard drive, and then temporarily loaded into RAM in batches when needed. Allows of less memory usage and faster performance, thanks to parallel processing. | **Related:** :term:`Dask` **|** :term:`Real Data` | **More information:** :doc:`real_and_lazy_data` | Long Name A name describing a :term:`phenomenon`, not limited to the the same restraints as :term:`standard name`. | **Related:** :term:`Standard Name` **|** :term:`Cube` | **More information:** :doc:`iris_cubes` | Matplotlib A python package for plotting and projecting data in a wide variety of formats. | **Related:** :term:`CartoPy` **|** :term:`NumPy` | **More information:** `matplotlib`_ | Metadata The information which describes a phenomenon. Within Iris specifically, all information which distinguishes one phenomenon from another, e.g. :term:`units ` or :term:`Cell Methods ` | **Related:** :term:`Phenomenon` **|** :term:`Cube` | **More information:** :doc:`../further_topics/metadata` | NetCDF Format A flexible file format for storing multi-dimensional array-like data. When Iris loads this format, it also especially recognises and interprets data encoded according to the :term:`CF Conventions`. __ `NetCDF4`_ | **Related:** :term:`Fields File (FF) Format` **|** :term:`GRIB Format` **|** :term:`Post Processing (PP) Format` | **More information:** `NetCDF-4 Python Git`__ | NumPy A mathematical Python library, predominantly based around multi-dimensional arrays. | **Related:** :term:`Dask` **|** :term:`Cube` **|** :term:`Xarray` | **More information:** `NumPy.org `_ | Phenomenon The primary data which is measured, usually within a cube, e.g. air temperature. | **Related:** :term:`Metadata` **|** :term:`Standard Name` **|** :term:`Cube` | **More information:** :doc:`iris_cubes` | Post Processing (PP) Format A meteorological file format, created from a post processed :term:`Fields File (FF) Format`. | **Related:** :term:`GRIB Format` **|** :term:`NetCDF Format` | **More information:** `PP Wikipedia Page `_ | Real Data Data that has been loaded into RAM, as opposed to sitting on the hard drive. | **Related:** :term:`Lazy Data` **|** :term:`NumPy` | **More information:** :doc:`real_and_lazy_data` | Standard Name A name describing a :term:`phenomenon`, one from a fixed list defined at `CF Standard Names `_. | **Related:** :term:`Long Name` **|** :term:`Cube` | **More information:** :doc:`iris_cubes` | Unit The unit with which the :term:`phenomenon` is measured e.g. m / sec. | **Related:** :term:`Cube` | **More information:** :doc:`iris_cubes` | Xarray A python library for sophisticated labelled multi-dimensional operations. Has a broader scope than Iris - it is not focused on meteorological data. | **Related:** :term:`NumPy` | **More information:** `Xarray Documentation `_ | ---- `To top `_