Quickly Retrieve Current and Historical NWM Forecasts from a Google Big Query Cloud Database
Day 2 Lunch Session (12:30 PM MDT)
Presenters:
Dan Ames
Brigham Young University
Kel Markert
Google, Brigham Young University
This brief lunchtime workshop will show you how to quickly retrieve current and historical National Water Model short range, medium range, and long range forecasts from a new and exciting Google Cloud Big Query database using a custom REST Application Programmer Interface (API) developed by CIROH researchers. If you are frustrated downloading and processing NetCDF files to extract forecasts for your hydologic features of interest, you will love the simplicity of using this new API and database. We will give a few simple examples that you can test on your computer in a Google Colab python notebook while enjoying your conference lunch.
Learning Outcomes:
- Learn the general concepts behind NWM and Google Cloud workflow.
- Learn about the design and structure of the Google Big Query database for historical and current forecasts.
- Learn the basic code syntax in Python for using the Google Cloud NWM API to retrieve historical forecasts individual hydrologic features.
Prerequisites:
Knowledge:
- General understanding of the types of forecasts created by the NWM.
- Some experience with Python coding.
Software/Hardware:
- A laptop or tablet that can access a Python notebook in Google Colab.
Accounts:
- Google Drive Account
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