Homework 10: Cartopy¶

1) Plot data from NARR¶

NARR is NCEP's North American Regional Reanalysis, a widely used product for studying the weather and climate of the continental US. The data is available from NOAA's Earth System Research Laboratory via OPeNDAP, meaing that xarray can opent the data "remotely" without downloading a file.

Maps in Scientific Python¶

Making maps is a fundamental part of geoscience research. Maps differ from regular figures in the following principle ways:

• Maps require a projection of geographic coordinates on the 3D Earth to the 2D space of your figure.
• Maps often include extra decorations besides just our data (e.g. continents, country borders, etc.)
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Assignment 4: More Matplotlib¶

The goal here is to replicate the figures you see as closely as possible.

In order to get some data, you will have to run the code in the cells below. Don't worry about how this code works. In the end, it will give you some numpy arrays, which you will use in your plots. You are not allowed to use any packages other than numpy and matplotlib to complete your assignment.

More Matplotlib¶

Matplotlib is the dominant plotting / visualization package in python. It is important to learn to use it well. In the last lecture, we saw some basic examples in the context of learning numpy. This week, we dive much deeper. The goal is to understand how matplotlib represents figures internally.

Assignment 3 - Numpy and Matplotlib¶

Due Thursday September 27¶

1 Creating and Manipulating Arrays¶

First import numpy and matplotlib

Numpy and Matplotlib¶

These are two of the most fundamental parts of the scientific python "ecosystem". Most everything else is built on top of them.