d18oc_sst

This is a companion to Malevich, Steven B, Lael Vetter, and Jessica E. Tierney, (2019). "Global core top calibration of d18O in planktic foraminifera to sea-surface temperature". Submitted to "Paleoceanography and Paleoclimatology".

This repository contains code walking through the four Bayesian regression coretop calibration models. This is in the notebook in ./notebooks/bayesian_calibration_examples.ipynb. You should be able to view this notebook online in github or nbviewer.

Data

Data used for the examples is in ./data/parsed/. These are simple CSV files. This data is also in the Supplemental Information of Malevich et al. 2019.

Running the notebook locally

If you would like to run the examples yourself, you can download this repo. The included environment.yml file lists the package requirements to create a virtual environment in Anaconda/conda.

First unzip the downloaded zip or clone the repo with git and move into the "d18Oc_sst" directory. Assuming you have conda installed and configured, you can create the environment with:

conda env create -f environment.yml

and follow the prompts. With the environment created, activate the new environment. You can start a Jupyter notebook server for your Desktop computer with:

jupyter notebook

This should launch a web browser allowing you to navigate to Jupyter notebook in ./notebooks/.