Radar Data IO#

Xarray Backends#

CfRadial1#

This sub-module contains the CfRadial1 xarray backend for reading CfRadial1-based radar data into Xarray structures as well as a reader to create a complete datatree.Datatree.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.open_cfradial1_datatree(filename)

`CfRadial1BackendEntrypoint`	Xarray BackendEntrypoint for CfRadial1 data.
`open_cfradial1_datatree`	Open CfRadial1 dataset as `datatree.DataTree`.

GAMIC HDF5#

This sub-module contains the GAMIC HDF5 xarray backend for reading GAMIC HDF5-based radar data into Xarray structures as well as a reader to create a complete datatree.Datatree.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.open_gamic_datatree(filename)

`GamicBackendEntrypoint`	Xarray BackendEntrypoint for GAMIC data.
`open_gamic_datatree`	Open GAMIC HDF5 dataset as `datatree.DataTree`.

ODIM_H5#

This sub-module contains the ODIM_H5 xarray backend for reading ODIM_H5-based radar data into Xarray structures as well as a reader to create a complete datatree.Datatree.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.open_odim_datatree(filename)

`OdimBackendEntrypoint`	Xarray BackendEntrypoint for ODIM data.
`open_odim_datatree`	Open ODIM_H5 dataset as `datatree.DataTree`.

Furuno binary data#

Reads data from Furuno’s binary data formats

To read from Furuno files numpy.memmap is used to get access to the data. The Furuno header is read in any case into dedicated OrderedDict’s. Reading sweep data can be skipped by setting loaddata=False. By default, the data is decoded on the fly.

Using rawdata=True the data will be kept undecoded.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.open_furuno_datatree(filename)

`FurunoBackendEntrypoint`	Xarray BackendEntrypoint for Furuno data.
`open_furuno_datatree`	Open FURUNO dataset as `datatree.DataTree`.

Rainbow Data I/O#

This sub-module contains the Rainbow xarray backend for reading data from Leonardo’s Rainbow5 data formats into Xarray structures as well as a reader to create a complete datatree.Datatree. For this mmap.mmap is utilized.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.open_rainbow_datatree(filename)

`RainbowBackendEntrypoint`	Xarray BackendEntrypoint for Rainbow5 data.
`open_rainbow_datatree`	Open ODIM_H5 dataset as `datatree.DataTree`.

IRIS/Sigmet Data I/O#

Reads data from Vaisala’s IRIS data formats

IRIS (Vaisala Sigmet Interactive Radar Information System)

See M211318EN-F Programming Guide ftp://ftp.sigmet.com/outgoing/manuals/

To read from IRIS files numpy.memmap is used to get access to the data. The IRIS header (PRODUCT_HDR, INGEST_HEADER) is read in any case into dedicated OrderedDict’s. Reading sweep data can be skipped by setting loaddata=False. By default the data is decoded on the fly. Using rawdata=True the data will be kept undecoded.

Code ported from wradlib.

`IrisBackendEntrypoint`	Xarray BackendEntrypoint for IRIS/Sigmet data.
`open_iris_datatree`	Open Iris/Sigmet dataset as `datatree.DataTree`.

StreamLine HPL#

This sub-module contains the StreamLine HPL xarray backend for reading StreamLine-based lidar data into Xarray structures.

Import of StreamLine .hpl (txt) files and save locally in directory. Therefore the data is converted into matrices with dimension “number of range gates” x “time stamp/rays”. In newer versions of the StreamLine software, the spectral width can be stored as additional parameter in the .hpl files.

`HPLBackendEntrypoint`	Xarray BackendEntrypoint for Halo Photonics Doppler processed lidar data.
`open_hpl_datatree`	Open Halo Photonics processed Doppler lidar dataset as `datatree.DataTree`.

NEXRAD Level2 Data I/O#

Reads data from NEXRAD Level2 data format

See https://www.roc.noaa.gov/WSR88D/BuildInfo/Files.aspx

Documents:

ICD 2620002 M ICD FOR RDA/RPG - Build RDA 11.5/RPG 13.0 (PDF)
ICD 2620010 E ICD FOR ARCHIVE II/USER - Build 12.0 (PDF)

To read from NEXRAD Level2 files numpy.memmap is used for uncompressed files (pre 2016-06-01) and bz2:BZ2Decompressor for BZ2 compressed data. The NEXRAD header (VOLUME_HEADER, MSG_HEADER) are read in any case into dedicated OrderedDict’s. Reading sweep data can be skipped by setting loaddata=False. By default, the data is decoded on the fly. Using rawdata=True the data will be kept undecoded.

Code adapted from Py-ART.

`NexradLevel2BackendEntrypoint`	Xarray BackendEntrypoint for NEXRAD Level2 Data
`open_nexradlevel2_datatree`	Open NEXRAD Level2 dataset as `datatree.DataTree`.

Datamet#

This sub-module contains the Datamet xarray backend for reading Datamet-based radar data into Xarray structures.

`DataMetBackendEntrypoint`	Xarray BackendEntrypoint for DataMet data.
`open_datamet_datatree`	Open DataMet dataset as `datatree.DataTree`.

Data Export#

CfRadial2 output#

This sub-module contains the writer for export of CfRadial2-based radar data.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.to_cfradial2(dtree, filename)

to_cfradial2

Save DataTree to CfRadial2 compliant file.

ODIM_H5 output#

This sub-module contains the writer for export of ODIM_H5-based radar data.

Code ported from wradlib.

Example:

import xradar as xd
dtree = xd.io.to_odim(dtree, filename)

to_odim

Save DataTree to ODIM_H5/V2_2 compliant file.