Posts

NetCDF is a ubiquitous binary data format in the geosciences. While it may not be widely known in other domains it has several advantages. Most importantly it can efficiently store large amounts of data and is self-describing.

Using code written by others can save a lot of time, but we are generally better at managing our own code. We diligently commit our code into version control systems like git and write automated tests, but do not at all control (or even list) the code that is written by third-parties.

Please see the github library based on this blog post: https://github.com/nbren12/call_py_fort. I have gotten many emails about small bugs and environment/compiling issues with the code samples in this blog post that are hard for me to help with.

I use a lot of different software tools in the course of my research, so I need a way to keep track of them in case something destroys my computer. That is the purpose of this post.

I am currently working with model output from the cloud-resolving model SAM. The full-resolution datasets are often too-large to load into memory because I have over 16000 horizontal grid points, and it is more convenient to work with coarse-grained data.

At work, my datafiles are split accross several different machines with different filesystems. These are My desktop my laptop NYU HPC NYU Abu Dhabi HPC In this post, I outline a strategy for archiving my data, and tracking where what is on different servers.

This tutorial describes the spline basis and smoothing techniques which are based on splines. using Plots pyplot() Here is a simple function and noisy data. The object of this tutorial is to estimate the sinuosoidal curve given the noisy observations.