This appendix contains examples of aggregation variables. Details of how to encode and decode aggregation variables are found in [aggregation-variables].
Example L.1 Aggregation variable with fragment datasets defined by relative-path URI references
dimensions:
time = 12 ;
level = 1 ;
latitude = 73 ;
longitude = 144 ;
// Array of fragments dimensions
f_time = 2 ;
f_level = 1 ;
f_latitude = 1 ;
f_longitude = 1 ;
// Map variable dimensions
j = 4 ; // Number of aggregated dimensions
i = 2 ; // Largest number of fragments along any aggregated dimension
variables:
// Data aggregation variable
double temperature ;
temperature:standard_name = "air_temperature" ;
temperature:units = "K" ;
temperature:cell_methods = "time: mean" ;
temperature:aggregated_dimensions = "time level latitude longitude" ;
temperature:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
// Coordinate variables
double time(time) ;
time:standard_name = "time" ;
time:units = "days since 2001-01-01" ;
time:calendar = "standard" ;
double level(level) ;
level:standard_name = "height_above_mean_sea_level" ;
level:units = "m" ;
double latitude(latitude) ;
latitude:standard_name = "latitude" ;
latitude:units = "degrees_north" ;
double longitude(longitude) ;
longitude:standard_name = "longitude" ;
longitude:units = "degrees_east" ;
// Array of fragments feature variables
string fragment_uris(f_time, f_level, f_latitude, f_longitude) ;
string fragment_identifiers ;
int fragment_map(j, i) ;
data:
temperature = _ ;
time = 0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334 ;
level = ... ;
latitude = ... ;
longitude = ... ;
fragment_map = 3, 9,
1, _,
73, _,
144, _ ;
fragment_uris = "January-March.nc", "April-December.nc" ;
fragment_identifiers = "temperature" ;
The temperature data variable is an aggregation variable.
Its four-dimensional aggregated data with shape (12, 1, 73, 144) is constructed from two non-overlapping fragments, with data shapes (3, 1, 73, 144) and (9, 1, 73, 144), which span the first 3 and last 9 elements respectively of the time aggregated dimension.
The fragment dataset names are relative-path URI references, and so in this case are assumed to be in the same directory as the aggregation dataset itself.
The data for the level, latitude and longitude variables are omitted for clarity.
Example L.2 Aggregation variable with fragment datasets defined by absolute URIs
dimensions:
time = 12 ;
level = 1 ;
latitude = 73 ;
longitude = 144 ;
// Array of fragments dimensions
f_time = 2 ;
f_level = 1 ;
f_latitude = 1 ;
f_longitude = 1 ;
// Map variable dimensions
j = 4 ; // Number of aggregated dimensions for temperature
j_time = 1 ; // Number of aggregated dimensions for time
i = 2 ; // Largest number of fragments along any aggregated dimension
variables:
// Data aggregation variable
double temperature ;
temperature:standard_name = "air_temperature" ;
temperature:units = "K" ;
temperature:cell_methods = "time: mean" ;
temperature:aggregated_dimensions = "time level latitude longitude" ;
temperature:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
// Coordinate aggregation variable
double time ;
time:standard_name = "time" ;
time:units = "days since 2001-01-01" ;
time:calendar = "standard" ;
time:aggregated_dimensions = "time" ;
time:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers_time
map: fragment_map_time" ;
// Coordinate variables
double level(level) ;
level:standard_name = "height_above_mean_sea_level" ;
level:units = "m" ;
double latitude(latitude) ;
latitude:standard_name = "latitude" ;
latitude:units = "degrees_north" ;
double longitude(longitude) ;
longitude:standard_name = "longitude" ;
longitude:units = "degrees_east" ;
// Array of fragments feature variables
int fragment_map(j, i) ;
string fragment_uris(f_time, f_level, f_latitude, f_longitude) ;
string fragment_identifiers ;
int fragment_map_time(j_time, i) ;
string fragment_uris_time(f_time) ;
string fragment_identifiers_time ;
data:
temperature = _ ;
time = _ ;
level = ... ;
latitude = ... ;
longitude = ... ;
fragment_map = 3, 9,
1, _,
73, _,
144, _ ;
fragment_uris = "file:///data/January-March.nc",
"https:///remote.host/data/April-December.nc" ;
fragment_identifiers = "temperature" ;
fragment_map_time = 3, 9 ;
fragment_uris_time = "file:///data/January-March.nc",
"https:///remote.host/data/April-December.nc" ;
fragment_identifiers_time = "time" ;
This example is similar to Example L.1, but now the fragment dataset names are absolute URIs (one local, one remote), and time is now also an aggregation coordinate variable, with its aggregated data being derived from the same fragment datasets as temperature.
The data for the level, latitude and longitude variables are omitted for clarity.
Example L.3 Aggregation variable with multiple aggregated dimensions
dimensions:
time = 12 ;
level = 1 ;
latitude = 73 ;
longitude = 144 ;
// Array of fragments dimensions
f_time = 12 ;
f_level = 1 ;
f_latitude = 2 ;
f_longitude = 4 ;
// Map variable dimensions
j = 4 ; // Number of aggregated dimensions
i = 12 ; // Largest number of fragments along any aggregated dimension
variables:
// Data aggregation variable
double temperature ;
temperature:standard_name = "air_temperature" ;
temperature:units = "K" ;
temperature:cell_methods = "time: mean" ;
temperature:aggregated_dimensions = "time level latitude longitude" ;
temperature:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
double pressure(time, level, latitude, longitude) ;
temperature:standard_name = "air_pressure" ;
temperature:units = "hPa" ;
temperature:cell_methods = "time: mean" ;
// Coordinate variables
double time(time) ;
time:standard_name = "time" ;
time:units = "days since 2001-01-01" ;
time:calendar = "standard" ;
double level(level) ;
level:standard_name = "height_above_mean_sea_level" ;
level:units = "m" ;
double latitude(latitude) ;
latitude:standard_name = "latitude" ;
latitude:units = "degrees_north" ;
double longitude(longitude) ;
longitude:standard_name = "longitude" ;
longitude:units = "degrees_east" ;
// Array of fragments feature variables
int fragment_map(j, i) ;
string fragment_uris(f_time, f_level, f_latitude, f_longitude) ;
string fragment_identifiers ;
data:
temperature = _ ;
pressure = ... ;
time = 0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334 ;
level = ... ;
latitude = ... ;
longitude = ... ;
fragment_map = 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, _, _, _, _, _, _, _, _, _, _, _,
37, 36, _, _, _, _, _, _, _, _, _, _,
36, 36, 36, 36, _, _, _, _, _, _, _, _ ;
fragment_uris = ... ;
fragment_identifiers = "temperature" ;
The temperature data variable is an aggregation of 96 fragments.
The shape of the array of fragments, inferred from the fragment_map data, is (12, 1, 2, 4), indicating that three of the four aggregated dimensions are spanned by multiple fragments.
The pressure data variable is not an aggregation variable.
The data for the pressure, level, latitude and longitude variables, and the fragment_uris variable, are omitted for clarity.
Example L.4 Aggregation discrete sampling geometry variable
dimensions:
station = 3 ;
obs = 15000 ;
// Array of fragments dimensions
f_station = 3 ;
// Map variable dimensions
j = 1 ; // Number of aggregated dimensions
i = 3 ; // Largest number of fragments along any aggregated dimension
variables:
// Data aggregation variable
float tas(obs) ;
tas:standard_name = "air_temperature" ;
tas:units = "K" ;
tas:coordinates = "time lat lon station_name" ;
tas:aggregated_dimensions = "obs" ;
tas:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
// DSG count variable
int row_size(station) ;
row_size:long_name = "number of observations per station" ;
row_size:sample_dimension = "obs" ;
// Auxiliary coordinate aggregation variables
float time ;
time:standard_name = "time" ;
time:units = "days since 1970-01-01" ;
time:calendar = "standard" ;
time:aggregated_dimensions = "obs" ;
time:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers_time
map: fragment_map" ;
float lon(station) ;
lon:standard_name = "longitude" ;
lon:long_name = "station longitude" ;
lon:units = "degrees_east" ;
lon:aggregated_dimensions = "station" ;
lon:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers_lon
map: fragment_map_latlon" ;
float lat(station) ;
lat:standard_name = "latitude" ;
lat:long_name = "station latitude" ;
lat:units = "degrees_north" ;
lat:aggregated_dimensions = "station" ;
lat:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers_lat
map: fragment_map_latlon" ;
// Array of fragments feature variables
int fragment_map(j, i) ;
string fragment_uris(f_station) ;
string fragment_identifiers ;
int fragment_map_latlon(j, i) ;
string fragment_identifiers_time(f_station) ;
string fragment_identifiers_lat ;
string fragment_identifiers_lon ;
// global attributes:
:featureType = "timeSeries" ;
data:
tas = _ ;
row_size = 5000, 4000, 6000 ;
time = _ ;
lat = _ ;
lon = _ ;
fragment_map = 5000, 4000, 6000 ;
fragment_uris = "Harwell.nc", "Abingdon.nc", "Lambourne.nc" ;
fragment_identifiers = "tas" ;
fragment_map_latlon = 1, 1, 1 ;
fragment_identifiers_time = "t1", "t2", "t3" ;
fragment_identifiers_lat = "lat" ;
fragment_identifiers_lon = "lon" ;
Three fragments are aggregated into a collection of discrete sampling geometry (DSG) timeseries feature types with contiguous ragged array representation.
The auxiliary coordinate variables time, lon, and lat are also aggregation variables.
The time variables in the fragment datasets all have different netCDF variable names, which differ from the netCDF name of the time aggregation variable.
The fragments for all aggregation variables, in this case, come from the same three fragment datasets.
No data have been omitted from the CDL.
Example L.5 Aggregation ancillary variable with unique fragment values
dimensions:
time = 12 ;
level = 1 ;
latitude = 73 ;
longitude = 144 ;
// Array of fragments dimensions
f_time = 2 ;
f_level = 1 ;
f_latitude = 1 ;
f_longitude = 1 ;
// Map variable dimensions
j = 4 ; // Number of aggregated dimensions for temperature
i = 2 ; // Largest number of fragments along any aggregated dimension
j_uid = 1 ; // Number of aggregated dimensions for uid
variables:
// Data aggregation variable
double temperature ;
temperature:standard_name = "air_temperature" ;
temperature:units = "K" ;
temperature:cell_methods = "time: mean" ;
temperature:ancillary_variables = "uid" ;
temperature:aggregated_dimensions = "time level latitude longitude" ;
temperature:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
// Ancillary aggregation variable
string uid ;
uid:long_name = "Fragment dataset unique identifiers" ;
uid:missing_value = "" ;
uid:aggregated_dimensions = "time" ;
uid:aggregated_data = "unique_values: fragment_unique_values
map: fragment_map_uid" ;
// Coordinate variables
double time(time) ;
time:standard_name = "time" ;
time:units = "days since 2001-01-01" ;
time:calendar = "standard" ;
double level(level) ;
level:standard_name = "height_above_mean_sea_level" ;
level:units = "m" ;
double latitude(latitude) ;
latitude:standard_name = "latitude" ;
latitude:units = "degrees_north" ;
double longitude(longitude) ;
longitude:standard_name = "longitude" ;
longitude:units = "degrees_east" ;
// Array of fragments feature variables
int fragment_map(j, i) ;
string fragment_uris(f_time, f_level, f_latitude, f_longitude) ;
string fragment_identifiers ;
int fragment_map_uid(j_uid, i) ;
string fragment_unique_values(f_time) ;
data:
temperature = _ ;
uid = _ ;
time = 0, 31, 59, 90, 120, 151, 181, 212, 243, 273, 304, 334 ;
level = ... ;
latitude = ... ;
longitude = ... ;
fragment_map = 3, 9,
1, _,
73, _,
144, _ ;
fragment_uris = "January-March.nc", "April-December.nc" ;
fragment_identifiers = "temperature" ;
fragment_map_uid = 3, 9 ;
fragment_unique_values = "04b9-7eb5-4046-97b-0bf8", "05ee0-a183-43b3-a67-1eca" ;
This example is similar to Example L.1, but now there is an additional aggregation ancillary variable uid which defines its fragments from the unique values stored in the fragment_unique_values variable.
The data for the level, latitude and longitude variables are omitted for clarity.
Example L.6 Aggregation variable with a scalar map variable
dimensions:
variables:
// Data aggregation variable
double temperature ;
temperature:standard_name = "air_temperature" ;
temperature:units = "K" ;
temperature:cell_methods = "time: mean" ;
temperature:aggregated_dimensions = "" ;
temperature:aggregated_data = "uris: fragment_uris
identifiers: fragment_identifiers
map: fragment_map" ;
// Scalar coordinate variables
double time ;
time:standard_name = "time" ;
time:units = "days since 2001-01-01" ;
time:calendar = "standard" ;
double height ;
level:standard_name = "height" ;
level:units = "m" ;
double latitude ;
latitude:standard_name = "latitude" ;
latitude:units = "degrees_north" ;
double longitude ;
longitude:standard_name = "longitude" ;
longitude:units = "degrees_east" ;
// Array of fragments feature variables
int fragment_map ;
string fragment_uris ;
string fragment_identifiers ;
data:
temperature = _ ;
time = 0 ;
height = 1.5 ;
latitude = 43.7 ;
longitude = 7.27 ;
fragment_map = 1 ;
fragment_uris = "file.nc" ;
fragment_identifiers = "tas" ;
An aggregation variable with scalar aggregated data, for which the aggregated_dimensions attribute is an empty string, and the map variable fragment_map is a scalar with the value 1.