Quick Start#

RadDB allows to download weather radar data from various cloud buckets of several meteorological offices. To download the data, it is necessary to create the RadDB configuration file.

Create the RadDB configuration file#

The RadDB configuration file records the directory on your local machine where to save the radar data of interest.

To facilitate the creation of the configuration file, you can adapt and run the following script in Python. The configuration file will be created in the user’s home directory under the name .config_raddb.yaml.

import raddb

base_dir = "<path/to/a/local/directory/>"  # where to download all RADAR data
raddb.define_configs(
    base_dir=base_dir,
)

Now please close and restart the python session to make sure that the configuration file is correctly loaded. You can check that the configuration file has been correctly created with:

import raddb

configs = raddb.read_configs()
print(configs)

Search the radar of interest#

To list the available radars, you can use the following command:

import raddb

raddb.available_radars()

You can also search which radars of a specific network are available during a given time period:

raddb.available_radars(network="NEXRAD", start_time="1992-01-01", end__time="1993-01-01")

The available radar networks can be listed using:

raddb.available_networks()

Download the data#

To download the data, you can adapt the following code snippet:

import raddb

radar = "KABR"
network = "NEXRAD"

start_time = "2021-02-01 12:00:00"
end_time = "2021-02-01 13:00:00"

raddb.download(
    network=network,
    radar=radar,
    start_time=start_time,
    end_time=end_time,
)

Search the data#

RadDB enables to search files files which have been downloaded locally, or files which are located into a cloud bucket. To search for file locally, specify procol="local", while to retrieve the file path of cloud bucket files, specify procol="s3".

# Search for files on cloud bucket
filepaths = raddb.find_files(
    network=network,
    radar=radar,
    start_time=start_time,
    end_time=end_time,
    fs_args=fs_args,
    protocol="s3",
    verbose=verbose,
)
print(filepaths)

# Search for files locally
filepaths = raddb.find_files(
    network=network,
    radar=radar,
    start_time=start_time,
    end_time=end_time,
    fs_args=fs_args,
    protocol="local",
    verbose=verbose,
)
print(filepaths)

RadDB provide an utility to group filepaths by temporal interval, radar volume identifiers, etc.

dict_filepaths = raddb.group_filepaths(filepaths, network=network, groups="volume_identifier")
dict_filepaths = raddb.group_filepaths(filepaths, network=network, groups=["day", "hour"])

Open the data#

RadDB enables to open radars files into various objects by simply providing a local or cloud file path.

raddb.open_datatree(filepath, network) opens a file into a xarray.DataTree object using the appropriate xradar reader. Typically, an xarray.DataTree object contains multiple radar sweeps.
raddb.open_dataset(filepath, network, sweep="sweep_0") opens a file and extract a single radar sweep into a xarray.Dataset object. The name of the radar sweep must be known beforehand !
raddb.open_pyart(filepath, network) opens a file into a pyart.Radar object.

Further documentation#

For radar data processing, please have a look at xradar, pyart and wradlib software.

If you are not familiar with xarray, numpy, pandas, and dask, it is highly suggested to first have a look also at the documentation of these software.

Quick Start

Contents