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some tools for accessing OCO-2 data
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SIF tools

The public github repository was created to support a fluorescence application workshop at AGU 2018:

The main purpose of the examples and tools provided here is to help users not yet familiar with SIF data to learn about its use, the pitfalls and what programming tools are necessary. Some script programming experience is necessary to work with satellite data anyhow and we opted to used open source software, using either python and R. Jupyter notebooks for python (as well as Julia, etc) provide an ideal way to walk you through some of the code with explanations and example datasets. Note that most of the coding was done shortly before the workshop, so things mights be in a state of flux. Also, we used the GPLv3 public license for the code provided here, it would be good to make this a community resource and we would highly appreciate it if any imporvements can be shared with us so that updates will be available to the growing SIF community.

Requirements: You will need the following python libraries for sure:

h5py, netCDF4, numpy, matplotlib

Download data:

This provides a quick link to tar'ed directories (careful, large files!). You can download these and extract them on your computer.

Traditional download: Paths for all OCO-2 and TROPOMI data: The scripts will only focus on April through October 2018 (overlapping time period for TROPOMI and OCO-2)

For the python examples, please ensure that you have python3 and Jupyter notebooks installed: A basic intro is here:

NIR pic of Oak tree in front of Linde center

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