weather-tools

Apache Beam pipelines to make weather data accessible and useful.

Introduction

This project contributes a series of command-line tools to make common data engineering tasks easier for researchers in climate and weather. These solutions were born out of the need to improve repeated work performed by research teams across Alphabet.

The first tool created was the weather downloader (weather-dl). This makes it easier to ingest data from the European Center for Medium Range Forecasts (ECMWF). weather-dl enables users to describe very specifically what data they'd like to ingest from ECMWF's catalogs. It also offers them control over how to parallelize requests, empowering users to retrieve data efficiently. Downloads are driven from a configuration file, which can be reviewed (and version-controlled) independently of pipeline or analysis code.

We also provide two additional tools to aid climate and weather researchers: the weather mover (weather-mv) and the weather splitter (weather-sp). These CLIs are still in their alpha stages of development. Yet, they have been used for production workflows for several partner teams.

We created the weather mover (weather-mv) to load geospatial data from cloud buckets into Google BigQuery. This enables rapid exploratory analysis and visualization of weather data: From BigQuery, scientists can load arbitrary climate data fields into a Pandas or XArray dataframe via a simple SQL query.

The weather splitter (weather-sp) helps normalize how archival weather data is stored in cloud buckets: Whether you're trying to merge two datasets with overlapping variables — or, you simply need to open Grib data from XArray, it's really useful to split datasets into their component variables.

Installing

It's recommended that you create a local python environment (with Anaconda). Otherwise, these tools can be installed with pip:

pip install google-weather-tools

From here, you can use the weather-* tools from your python environment. Currently, the following tools are available:

• ⛈ weather-dl (beta) – Download weather data (namely, from ECMWF's API).
• ⛅️ weather-mv (alpha) – Load weather data into BigQuery.
• 🌪 weather-sp (alpha) – Split weather data by variable.

Quickstart

Together, let's download Era 5 pressure level data and ingest it into Google BigQuery.

Pre-requisites:

1. Acquire and install a license from ECMWF's Copernicus (CDS) API.
2. Create an empty BigQuery Dataset. This can be done in the console or via the bq CLI. For example:

   bq mk --project_id=$PROJECT $DATASET_ID
   

Steps:

1. Use weather-dl to acquire the Era 5 pressure level data.

   For simplicity, let's run everything on your local machine. For the downloader, this means we'll use the --local-run option:

   weather-dl configs/era5_example_config_local_run.cfg --local-run
   

   Recommendation: Pass the -d, --dry-run flag to any of these commands to preview effects.

   Generally, weather-dl is designed to ingest weather data to cloud storage. To learn how to configure downloads, please see this documentation. See detailed usage of weather-dl here.

2. (optional) Split your downloaded dataset up by variable with weather-sp:

    weather-sp --input-pattern "./local_run/era5-*.nc" --output-dir "split_data" 
   

   Consult the weather-sp docs for more.

3. Use weather-mv to upload this data to Google BigQuery.

   weather-mv --uris "./local_run/**.nc" \ # or  --uris "./split_data/**.nc" \
      --output_table "$PROJECT.$DATASET_ID.$TABLE_ID" \
      --temp_location "gs://$BUCKET/tmp" \  # Needed for batch writes to BigQuery
      --direct_num_workers 2
   

   See these docs for more about this tool.

   Warning: Dry-runs are currently not supported. See #22.

That's it! Soon, you'll have your weather data ready for analysis in BigQuery.

Note: The exact interfaces for these CLIs are subject to change. For example, we plan to make the CLIs have more uniform arguments (#21).

Contributing

The weather tools are under active development, and contributions are welcome! Please check out our guide to get started.

License

This is not an official Google product.

Copyright 2021 Google LLC

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.