Using machine learning and simple features to predict climate – part 1

Earth’s climate is one of the fundamental boundary conditions on many Earth surface processes. For this reason, global climate models (GCMs) are often a critical part of Earth science research. However, they remain highly computationally expensive to run, and often access to a super-computer is needed to run a GCM in a reasonable amount of time. This motivates the question: is it possible to reasonably predict climate without an expensive GCM?

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Topography art

Looking for a new background for your computer, tablet, or phone? Or just looking to make a cool visual of a place that you like? We can make an awesome “ridge plot” of a location using an elevation map, all in Python.

The Jupyter notebook in which this visualization is made can be found here, although commits after this post may change the most updated version of the code.

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An early-career scientist’s perspective on building a personal website

TLDR: After considerable experimentation on alternatives, my choice is WordPress.org hosted at one of these sites.

The majority of scientists these days (including myself) are coding-literate, but don’t have any particular experience in developing websites. This makes tools that allow the creation of a nice website without directly writing .html, .css, etc. appealing, because it means that we don’t have to learn the details of these languages that we aren’t likely to be using outside of this context. In addition, we want to be focused on content, not maintenance.

For me, the following are the key prerequisites that a website builder should have:

  • Easy to update/maintain.
  • Reasonably easy to learn/use.
  • Allows creation of a nice website with some flexibility in how it looks.
  • Doesn’t require you to know complex .html, .css, etc.
  • Cheap (or free, ideally).
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