Using Python for Weather Analysis: Isotherms

Background

In this activity, you will construct a Jupyter notebook that will perform two main functions using the libraries previously described:

Import NDBC Bouy Data
Plot time series data
Create a coastal Isotherm map

Isotherm creation using point interpolation:

https://unidata.github.io/MetPy/latest/examples/gridding/Wind_SLP_Interpolation.html#sphx-glr-examples-gridding-wind-slp-interpolation-py

NDBC Bouy Data Platform: https://www.ndbc.noaa.gov/

Activity:

1. For this lab install the siphon library using conda install siphon. Then check the libraries in your active conda environment to ensure you have the necessary libraries to complete the analysis. Refer back to the videos 3,4 and 5 from the previous lab session.

Use this command to see a list of the libraries available in your activated Conda environment:

conda list -n your <conda environment here>

2. Watch the video above and work through the steps to make a time series plot for a bouy of your choosing.

**Note: you will need to convert the time field to an numeric field, as the time format for the data will not allow it to be plotted in the format that has been delivered to you.

Libraries used:

Example Outputs:

Time series Bouy Data

Isotherm Output

Code Solution:

https://github.com/rab9975/Jupyter-Weather-Analysis/blob/master/Lab3_Time_Series_Isotherm_final.ipynb

Related Resources:

https://mapscaping.com/blogs/the-mapscaping-podcast/introduction-to-jupyter-notebooks