Using Python to Retrieve Weather Observations from a Mesonet API with Application to Practical Use Cases

Weather observations continue to become more abundant with the advent of low-cost weather stations and the proliferation of mesonets. While aggregating and processing these observations can be a considerable task, it serves a crucial purpose of providing a single, reliable source of observations for situational awareness, processing into numerical weather models, and application into atmospheric research. Synoptic Data, a Public Benefit Corporation, provides this service not only to NOAA’s National Mesonet Program, but to the public through a free, open-access API. This short course will demonstrate the utility of accessing observations from hundreds of networks in a single API with hands-on examples of interacting with the Synoptic Data API using Python. Demonstrations will include examples of tools and workflows that visualize and can benefit from including weather observations from many providers. This course will also include a working sprint portion that allows participants to implement weather observations into their projects, workflows, or new ideas, with technical help from presenters who are experienced in Python and interacting with data APIs.

January 8, 2023 at 8:00 AM - 12:00 PM Mountain Time (In Person) - Colorado Convention Center: Room 504

Registration close date:	December 29, 2022
Participant cap:	None

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Course Description:

Participants will leave the short course with an understanding of the volume and diversity of freely accessible mesonet data, and how to access it from Synoptic Data’s API. This will include a brief concept understanding of how weather observations are aggregated and made available through an API. Participants will also be exposed to the value of mesonet observations, obtained from an API, through hands-on applications to several real-world scenarios using Python.

Requirements & Prerequisites

A basic understanding of Python is required for this short course. Familiarity and some experience with Pandas and MetPy Python libraries is strongly encouraged to get the most out of this course. Each participant is asked to bring a laptop for hands-on portions of the course, with the ability to install software packages and run programs via the terminal or an IDE.

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If you have questions regarding the course, please contact Brock Burghardt, the course organizer.