NetCDF User's Guide for C
A netCDF dataset contains a symbol table for variables containing their name, data type, rank (number of dimensions), dimensions, and starting disk address. Each element is stored at a disk address which is a linear function of the array indices (subscripts) by which it is identified. Hence, these indices need not be stored separately (as in a relational database). This provides a fast and compact storage method.
_' and hyphen '-'), beginning with a letter or underscore. (However names commencing with underscore are reserved for system use.) Case is significant in netCDF names.
netcdf example_1 { // example of CDL notation for a netCDF dataset
dimensions: // dimension names and lengths are declared first
lat = 5, lon = 10, level = 4, time = unlimited;
variables: // variable types, names, shapes, attributes
float temp(time,level,lat,lon);
temp:long_name = "temperature";
temp:units = "celsius";
float rh(time,lat,lon);
rh:long_name = "relative humidity";
rh:valid_range = 0.0, 1.0; // min and max
int lat(lat), lon(lon), level(level);
lat:units = "degrees_north";
lon:units = "degrees_east";
level:units = "millibars";
short time(time);
time:units = "hours since 1996-1-1";
// global attributes
:source = "Fictional Model Output";
data: // optional data assignments
level = 1000, 850, 700, 500;
lat = 20, 30, 40, 50, 60;
lon = -160,-140,-118,-96,-84,-52,-45,-35,-25,-15;
time = 12;
rh =.5,.2,.4,.2,.3,.2,.4,.5,.6,.7,
.1,.3,.1,.1,.1,.1,.5,.7,.8,.8,
.1,.2,.2,.2,.2,.5,.7,.8,.9,.9,
.1,.2,.3,.3,.3,.3,.7,.8,.9,.9,
0,.1,.2,.4,.4,.4,.4,.7,.9,.9;
}
The CDL notation for a netCDF dataset can be generated automatically by using ncdump, a utility program described later (see Section 10.5 "ncdump," page 104). Another netCDF utility, ncgen, generates a netCDF dataset (or optionally C or FORTRAN source code containing calls needed to produce a netCDF dataset) from CDL input (see Section 10.4 "ncgen," page 103).
The CDL notation is simple and largely self-explanatory. It will be explained more fully as we describe the components of a netCDF dataset. For now, note that CDL statements are terminated by a semicolon. Spaces, tabs, and newlines can be used freely for readability. Comments in CDL follow the characters '//' on any line. A CDL description of a netCDF dataset takes the form
netCDF name {
dimensions: ...
variables: ...
data: ...
}
where the name is used only as a default in constructing file names by the ncgen utility. The CDL description consists of three optional parts, introduced by the keywords dimensions, variables, and data. NetCDF dimension declarations appear after the dimensions keyword, netCDF variables and attributes are defined after the variables keyword, and variable data assignments appear after the data keyword.
A netCDF dimension has both a name and a length. A dimension length is an arbitrary positive integer, except that one dimension in a netCDF dataset can have the length UNLIMITED.
Such a dimension is called the unlimited dimension or the record dimension. A variable with an unlimited dimension can grow to any length along that dimension. The unlimited dimension index is like a record number in conventional record-oriented files. A netCDF dataset can have at most one unlimited dimension, but need not have any. If a variable has an unlimited dimension, that dimension must be the most significant (slowest changing) one. Thus any unlimited dimension must be the first dimension in a CDL shape and the first dimension in corresponding C array declarations.
CDL dimension declarations may appear on one or more lines following the CDL keyword dimensions. Multiple dimension declarations on the same line may be separated by commas. Each declaration is of the form name = length.
There are four dimensions in the above example: lat, lon, level, and time. The first three are assigned fixed lengths; time is assigned the length UNLIMITED, which means it is the unlimited dimension.
The basic unit of named data in a netCDF dataset is a variable. When a variable is defined, its shape is specified as a list of dimensions. These dimensions must already exist. The number of dimensions is called the rank (a.k.a. dimensionality). A scalar variable has rank 0, a vector has rank 1 and a matrix has rank 2.
It is possible to use the same dimension more than once in specifying a variable shape (but this was not possible in previous netCDF versions). For example, correlation(instrument, instrument) could be a matrix giving correlations between measurements using different instruments. But data whose dimensions correspond to those of physical space/time should have a shape comprising different dimensions, even if some of these have the same length.
A variable external data type is one of a small set of netCDF types that have the names NC_BYTE, NC_CHAR,NC_SHORT, NC_INT,NC_FLOAT, and NC_DOUBLE in the C interface. NC_LONG is a deprecated synonym for NC_INT in the C interface.
In the CDL notation, these types are given the simpler names byte, char, short, int, float, and double. real may be used as a synonym for float in the CDL notation. long is a deprecated synonym for int. The exact meaning of each of the types is discussed in Section 3.1 "netCDF external data types," page 15.
CDL variable declarations appear after the variable keyword in a CDL unit. They have the form
type variable_name ( dim_name_1, dim_name_2, ... );
for variables with dimensions, or
type variable_name;
for scalar variables.
In the above CDL example there are six variables. As discussed below, four of these are coordinate variables. The remaining variables (sometimes called primary variables), temp and rh, contain what is usually thought of as the data. Each of these variables has the unlimited dimension time as its first dimension, so they are called record variables. A variable that is not a record variable has a fixed length (number of data values) given by the product of its dimension lengths. The length of a record variable is also the product of its dimension lengths, but in this case the product is variable because it involves the length of the unlimited dimension, which can vary. The length of the unlimited dimension is the number of records.
A variable with the same name as a dimension is called a coordinate variable. It typically defines a physical coordinate corresponding to that dimension. The above CDL example includes the coordinate variables lat, lon, level and time, defined as follows:
int lat(lat), lon(lon), level(level);
short time(time);
...
data:
level = 1000, 850, 700, 500;
lat = 20, 30, 40, 50, 60;
lon = -160,-140,-118,-96,-84,-52,-45,-35,-25,-15;
time = 12;
These define the latitudes, longitudes, barometric pressures and times corresponding to positions along these dimensions. Thus there is data at altitudes corresponding to 1000, 850, 700 and 500 millibars; and at latitudes 20, 30, 40, 50 and 60 degrees north. Note that each coordinate variable is a vector and has a shape consisting of just the dimension with the same name. A position along a dimension can be specified using an index. This is an integer with a minimum value of 0 for C programs. Thus the 700 millibar level would have an index value of 2 in the example above.
If a dimension has a corresponding coordinate variable, then this provides an alternative, and often more convenient, means of specifying position along it. Current application packages that make use of coordinate variables commonly assume they are numeric vectors and strictly monotonic (all values are different and either increasing or decreasing).
Some attributes provide information about the dataset as a whole and are called global attributes. These are identified by the attribute name together with a blank variable name (in CDL) or a special null "global variable" ID (in C or Fortran).
An attribute has an associated variable (the null "global variable" for a global attribute), a name, a data type, a length, and a value. The current version treats all attributes as vectors; scalar values are treated as single-element vectors.
Conventional attribute names should be used where applicable. New names should be as meaningful as possible.
The external type of an attribute is specified when it is created. The types permitted for attributes are the same as the netCDF external data types for variables. Attributes with the same name for different variables should sometimes be of different types. For example, the attribute valid_max specifying the maximum valid data value for a variable of type int should be of type int, whereas the attribute valid_max for a variable of type double should instead be of type double.
Attributes are more dynamic than variables or dimensions; they can be deleted and have their type, length, and values changed after they are created, whereas the netCDF interface provides no way to delete a variable or to change its type or shape.
The CDL notation for defining an attribute is
variable_name:attribute_name = list_of_values;
for a variable attribute, or
:attribute_name = list_of_values;
for a global attribute. The type and length of each attribute are not explicitly declared in CDL; they are derived from the values assigned to the attribute. All values of an attribute must be of the same type. The notation used for constant values of the various netCDF types is discussed later (see Section 10.3 "CDL Notation for Data Constants," page 102).
In the netCDF example (see Section 2.1.2 "network Common Data Form Language (CDL)," page 9), units is an attribute for the variable lat that has a 13-character array value 'degrees_north'. And valid_range is an attribute for the variable rh that has length 2 and values '0.0' and '1.0'.
One global attribute---source---is defined for the example netCDF dataset. This is a character array intended for documenting the data. Actual netCDF datasets might have more global attributes to document the origin, history, conventions, and other characteristics of the dataset as a whole.
Most generic applications that process netCDF datasets assume standard attribute conventions and it is strongly recommended that these be followed unless there are good reasons for not doing so. See Section 8.1 "Attribute Conventions," page 81, for information about units, long_name, valid_min, valid_max, valid_range, scale_factor, add_offset, _FillValue, and other conventional attributes.
Attributes may be added to a netCDF dataset long after it is first defined, so you don't have to anticipate all potentially useful attributes. However adding new attributes to an existing dataset can incur the same expense as copying the dataset. See Chapter 9 "NetCDF File Structure and Performance," page 95, for a more extensive discussion.
Another difference between attributes and variables is that variables may be multidimensional. Attributes are all either scalars (single-valued) or vectors (a single, fixed dimension).
Variables are created with a name, type, and shape before they are assigned data values, so a variable may exist with no values. The value of an attribute must be specified when it is created, so no attribute ever exists without a value.
A variable may have attributes, but an attribute cannot have attributes. Attributes assigned to variables may have the same units as the variable (for example, valid_range) or have no units (for example, scale_factor). If you want to store data that requires units different from those of the associated variable, it is better to use a variable than an attribute. More generally, if data require ancillary data to describe them, are multidimensional, require any of the defined netCDF dimensions to index their values, or require a significant amount of storage, that data should be represented using variables rather than attributes.