This repository contains Python implementations of three simple models for simulating the diurnal variability of sea surface temperature (SST) under given atmospheric forcing. It further includes an observational dataset for calibration and validation, plus code to reproduce the results in the DiuSST model description paper.
Models in this repo:
- DiuSST, a conceptual depth-resolved 1D model of upper ocean temperature dynamics
- ZengBeljaars05, a prognostic scheme of sea skin temperature by Zeng & Beljaars (2005)
- Slab, a simple slab ocean with proportional and integral correctors
The DiuSST model is described in arXiv:2205.07933, where it is compared to the ZengBeljaars05 and Slab models based on observational data. The ZengBeljaars05 scheme has originally been presented in Zeng & Beljaars (2005). The Slab model is similar to responsive SST models used in idealized studies of tropical atmospheric convection, and is also described in arXiv:2205.07933.
Learn more about the DiuSST model in this 15-minute video!
- The DiuSST model code is documented here.
- For information on running the ZengBeljaars05 and Slab models, see the docstrings in
src/zengbeljaars.pyandsrc/slab.py. - An example notebook to run DiuSST is provided in
docs/run_diusst.ipynb.
The MOCE-5 cruise observations used to calibrate the DiuSST model as described in the paper is stored in input_data/moce5/moce5_dataset.cdf as a netCDF file. The raw data is also contained in the folder input_data/moce5/.
Results in the paper were produced with version v1.2 of this repository. The script scripts/generate_plotdata.py runs the model simulations and saves the model output, which is found in output_files as .npz files. Code to reproduce figures based on these simulation data is located in scripts/figs. Model calibration via Bayesian inference was performed using the scripts paper_bayesian_diusst.py (DiuSST model) and paper_bayesian_slab.py (Slab model). The resulting posterior distributions are saved in output_files as posterior_diusst.h5 and posterior_slab.h5, respectively.
This work has been conducted within the Atmospheric Complexity Group at the Niels Bohr Institute, University of Copenhagen, Denmark.
Collaborators: Romain Fiévet, Jan O. Haerter
We gratefully acknowledge Peter Minnett for providing meteorological and oceanographic data sets from the MOCE-5 cruise contained in this repository. The development and deployment of the instruments used during the cruise was funded by NASA.
I would further like to thank Peter Ditlevsen for co-supervising this project and Gorm G. Jensen for helpful discussions. I am thankful to Chong Jia for a helpful discussion on the cool skin scheme in ZengBeljaars05.