Investigating a Wet Bulb Globe Temperature Calculation for MetPy

Caitlyn McAllister
Caitlyn McAllister

During the duration of this summer’s internship program I hit the ground running by learning how to code in Python. Before this internship, I had only opened Python a few times while attending classes and did a little coding in this language for a collaborative project at my university. I familiarized myself over the first month by using the workshops available in JupyterLab provided by Unidata. I learned everything from loops to using the THREDDS data sever to plot variables. Outside of the language, I got to learn how an online community works with GitHub to share and process software and data. I also learned about development environments, which I had no clue about before. I will definitely be using all of these tools moving forward.

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Building Support for Efficient MetPy Calculations Across Large Datasets with Dask

Russell Manser
Russell Manser

Coming into this summer, my goal was to integrate Dask Array support into MetPy. I knew that this was an ambitious task, but I am happy to say that I made progress toward accomplishing it!

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MetPy Mondays #141 - Animating Hurricane Forecast Tracks

This week we animate the forecast track of hurricanes with data from the NHC and matplotlib!

MetPy Mondays #140 - S3 Radar Archive Data

This week learn how to access data from the S3 radar archive!

MetPy Mondays #139 - Uploading Plots to S3 from Python Part 2

This week we finish our S3 project by writing an upload function and creating an IAM user!

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A weblog about software development by Unidata developers*

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