NetCDF Time Series To Feature Class (Discrete Sampling Geometry) (Multidimension Tools)

Summary

Creates a feature class from timeseries in netCDF files. In the Climate and Forecast (CF) metadata convention, a timeseries is a type of discrete sampling geometry (DSG).

Learn more about how the Discrete Sampling Geometry (DSG) tools work

Usage

• In the Climate and Forecast (CF) metadata convention, a time series is a series of data points at the same spatial location with monotonically increasing times.

• Discrete sampling geometry (DSG) datasets are characterized by a lower dimensionality than the space-time region where the data is sampled.

• The input netCDF files should be Climate and Forecast (CF) compliant (CF 1.6 or later). The CF conventions define metadata to describe the data represented by each variable and the spatial and temporal properties of the data.

• If the input netCDF files are not CF compliant, you can specify an Input Climate and Forecast Metadata (in_cf_metadata in Python) file with additional or altered attributes. The Input Climate and Forecast Metadata file is an XML format file with an .ncml extension. The attributes from this metadata file will extend or override the metadata in the netCDF file. The Input Climate and Forecast Metadata file can also be used to specify a grid mapping variable if the input netCDF file does not have one.

• A DSG feature type is identified by an instance ID variable marked with a cf_role attribute. Multiple netCDF files with the same schema can be converted to a single feature class with a unique InstanceID field. Each netCDF file should have a variable marked with the same cf_role attribute, which will be used as the identifying field across multiple files. Aggregation will occur strictly along the instance dimension of this variable.

• Multiple instance and observation variables (station number, temperature, salinity, and so on) can be selected in the Instance Variables (instance_variables in Python) and Observation Variables (observation_variables in Python) parameters, respectively.

• If the input netCDF files contain variables organized into groups, the Instance Variables and Observation Variables parameters will list the variables with their absolute paths, with a leading slash ("/") indicating the location relative to the root group. For example, the variable precip located in group /g1 will be shown as /g1/precip.

• For both instance and observation variables, matching is done variable name. That is, if two variables in different netCDF files have the same name, they will be interpreted as representing the same thing. If variables are present within groups, variable names are considered with their absolute path during matching. If multiple variables with the same name are present in different locations relative to the root group (for example, /g1/precip and /g2/precip), they will be interpreted as representing different things.

• You can use the Analysis Extent (analysis_extent in Python) parameter to specify the output analysis area explicitly for a stand-alone tool operation or to override the environment setting as part of a workflow. You can specify the extent by typing values, choosing the display extent, selecting a layer, or browsing for an input dataset.

• The default Analysis Extent value is calculated from the union extent of the input netCDF files.

• If the extent is not explicitly specified as the parameter value, it will be derived from the analysis environment settings.

• A 2D or 3D point feature class will be created that contains all the location information along with the selected instance fields, as well as a related table containing the selected observation variables. An optional layer can also be created, which will join the table to the feature class based on the InstanceID field.

• A data variable in the netCDF file can use a grid_mapping variable to explicitly define the coordinate reference system (CRS) used for the spatial coordinate values. The grid mapping epsg_code attribute can be used to select a GCS or PCS. Also, the grid mapping esri_pe_string, crs_wkt, and spatial_ref attributes can all be used to define either a WKT 1 or WKT 2 string. If any of these attributes are present, no other attributes for the horizontal coordinate system are used. For more information about coordinate reference systems as well as the supported WKIDs, see the Coordinate systems, projections, and transformations topic.

• If the spatial coordinate values are 3D, the grid_mapping variable should also specify a vertical coordinate system (VCS). A VCS is a combination of a vertical datum, a linear unit of measure, and the direction (up or down) that vertical coordinates increase. The datum is typically obtained from an attribute of the grid mapping variable and the other properties are obtained from the vertical coordinate variable. An arbitrary vertical datum can be specified using a compound WKT string as the value of one of the WKT attributes listed above. A gravity-based datum can be specified using either the geoid_name or geopotential_datum_name attribute. In addition, a tidal datum can be implicitly specified using one of the tidal standard names for the vertical coordinate variable. If no VCS is specified and a vertical coordinate variable is present, WGS 1984 Ellipsoid Height (wkid115700) will be selected as the default.

Parameters

• Dialog
• Python

Label	Explanation	Data type
Input NetCDF Files or Folders	The input netCDF files that will be used to create a feature class. Individual netCDF files, as well as folders that contain multiple netCDF files, can be used. The input netCDF files must have the same DSG feature type and schema.	Folder; File
Target Workspace	The geodatabase (enterprise or file) or folder in which the output feature class and table will be created. This must be an existing workspace.	Workspace
Output Point Name	The name of the feature class that will contain the locations from the netCDF variables. These variables will be added as fields from the Instance Variables parameter.	String
Observation Variables (Optional)	The netCDF variables that contain all the observation values at each location and each vertical level. These will be added as fields to the output table	String
Output Join Table Name (Optional)	The name of the output table that will contain all the records from the Observation Variables parameter.	String
Instance Variables (Optional)	The netCDF variables that differentiate individual features and represent the locations where observations are made. These variables will be added as fields to the output feature class.	String
Include Subdirectories (Optional)	Specifies whether the files residing in the subdirectories of an input folder will be used. Checked—All netCDF files in all subdirectories will be used. Unchecked—Only files in the input folder will be used. This is the default.	Boolean
Input Climate and Forecast Metadata (Optional)	The XML format file with an .ncml extension that will supply missing or altered CF information for the input netCDF files.	File
Analysis Extent (Optional)	The extent that defines the area of the output feature class.	Extent
Output Join Layer (Optional)	The output layer that will be created by joining the output table to the output feature class. This is an optional output.	Feature Layer

Derived output

Label	Explanation	Data type
Output Point	The output point feature class.	Feature Class
Output Join Table	The output table.	Table

Environments

Output Coordinate System, Extent

Licensing information

• Basic: Yes
• Standard: Yes
• Advanced: Yes

Related topics

• An overview of the Multidimension toolbox
• An overview of the NetCDF toolset
• Find a geoprocessing tool
• NetCDF Points To Feature Class (Discrete Sampling Geometry)
• NetCDF Profiles To Feature Class (Discrete Sampling Geometry)
• NetCDF Trajectories To Feature Class (Discrete Sampling Geometry)
• How NetCDF Discrete Sampling Geometry (DSG) tools work