NetCDF

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NetCDF (Network Common Data Form), is a file format that stores scientific data in arrays. Array values may be accessed directly, without knowing how the data are stored, and metadata information may be stored with the data.

  • Binary file format commonly used for scientific data

  • Self-describing, includes metadata

  • Multi-dimensional array data model

The netCDF data model consists of the following:

  • variable

    • Multi-dimensional array

    • Column-oriented: each variable as a separate entity

  • dimension

    • Usually temporal, spatial, spectral, …

    • Can be unlimited length. One, at most, is recommended for a growing time dimension

  • attribute

    • Metadata: global and variable level

  • group

    • Akin to directories

    • Avoid unless you really need the complex structure

Why use NetCDF

NetCDF is a file format commonly used at LASP as it is the “highly preferred” format for NASA Earth Observing System Data and Information System data products, per their Data Product Development Guide for Data Producers. This affects all NASA Earth Science missions.

NetCDF features:

  • Self-describing

    • structure captures coordinate system (functional relationship)

    • includes metadata

  • Efficient storage

    • packing

    • compression

  • Efficient access

    • chunking

    • http byte range

    • parallel IO

  • Open specification (unlike IDL save files)

Options available

There are two netCDF data models:

  • NetCDF-3 classic

  • NetCDF-4 built on HDF5

    • recommended but prefer classic constructs

How to use this data format

NetCDF Files

  • Binary format with open specification

  • Requires software libraries to read and write C, Fortran, Java, python, IDL, …

  • Internal compression, don’t bother to compress NetCDF files externally

  • HTTP byte range requests

  • Parallel IO

  • nc file extension

  • Don’t be afraid of big files

Coordinate System

  • Dimensions should be used to define a coordinate system

    • e.g. temporal, spatial, spectral

    • Avoid using dimensions to group data

    • Think “functional relationship”. Each independent variable should represent a dimension.

  • coordinate variable

    • 1D variable with dimension of the same name

    • strictly monotonic (ordered)

    • no missing values

    • Independent variable of functional relationship

    • Every dimension should have one

  • shared dimensions

    • Each variable should reuse dimensions to indicate that they share the same coordinates (domain set)

Time as Coordinate Variable

  • If the data are a function of a single time dimension then there should be a single time variable

    • avoid breaking time up by date and time of day

  • Prefer numeric time units

    • time unit since an epoch

    • e.g. “seconds since 1970-01-01”, “microseconds since 1980-01-06”

Metadata

Other useful variable attributes

  • _FillValue

    • missing_value is considered deprecated and is not recommended by the NetCDF Users Group.

    • NaN is another option, however, NaNs in files are handled differently in every language and so it may be better to pick a value for official data products that many users will be using

  • valid_range, valid_min, valid_max

  • scale_factor, add_offset (packed values)

  • cell_methods : standards for representing data cells (bins)

    • e.g. daily average, wavelength bins