Intake - Satpy Drivers

This package adds additional drivers for the Intake library using the Satpy library to read data files. This package also depends on intake-xarray to define the Xarray container type (xarray Dataset) which these Satpy-based drivers produce.

Installation

To add this package to an existing pip based environment, run:

pip install intake-satpy

Or if you have a conda-based environment you can install it from the conda-forge channel:

conda install -c conda-forge intake-satpy

Usage

This package currently only supplies one intake driver named satpy. As with any intake driver, the satpy driver can be used in a couple different ways. A few examples are shown below.

Inline Usage

Once the intake-satpy package is installed, you can use this driver by calling intake.open_satpy. At the time of writing, it is best to provide as much information to configure/control Satpy as you can by passing the scene_kwargs and load_kwargs.

import intake
from glob import glob

data_source = intake.open_satpy(
    glob("/data/satellite/abi/*.nc"),
    scene_kwargs={"reader": "abi_l1b"},
    load_kwargs={"wishlist": ["C01"]},
)
dataset = data_source.read_chunked()

The read_chunked method will return an xarray Dataset object that will contain the products that Satpy was able to create. Data will be represented as dask arrays underneath. The data_source.to_dask() method will also produce this result. The data_source.read() method will return the same xarray Dataset object but data will be loaded into memory as numpy arrays. Care must be taken as the large satellite formats read by Satpy can quickly fill up your system's memory if loaded in this way.

By default, if wishlist is not provided as a load keyword argument (see above), then all available "reader" level products will be loaded. This means those that can be read directly from the file and does not include any Satpy "composites".

Also by default the loaded dataset is "resampled" using Satpy's "native" resampler to the finest resolution of the loaded products. This allows for all products to exist in a single xarray Dataset object. This behavior can be customized by providing resample_kwargs to the source creation (open_satpy call).

Catalog Usage - Local

The satpy driver can also be used in a catalog definition. See the examples/local_abi_l1b.yaml catalog definition file for an example. With a catalog like this you could then do:

import intake

cat = intake.open_catalog("examples/local_abi_l1b.yaml")
source = cat.abi_l1b(base_dir="/data/satellite/abi")
dataset = source.read_chunked()

A wishlist of products to load can be provided to the source when creating it:

cat = intake.open_catalog("examples/local_abi_l1b.yaml")
source = cat.abi_l1b(base_dir="/data/satellite/abi", load_kwargs={"wishlist": ["C01"]})
dataset = source.read_chunked()

As with the inline usage, if wishlist is not provided then all reader-level products will be loaded.

Catalog Usage - S3

Some of Satpy's readers can also read data from remote storage like S3 buckets. An example catalog is included in the examples/ directory of the intake-satpy repository.

Note that Satpy's performance for reading S3 files is currently very slow, but is being worked on. It is likely not suitable for loading data outside of the network where the S3 storage is (AWS in this example) until future updates to Satpy and NetCDF are made.

import intake

cat = intake.open_catalog("examples/aws_abi_l1b_20220101_18.yaml")
source = cat.abi_l1b()
dataset = source.read_chunked()