ECS_Bump

Repo to reproduce the results of Meraner et al. (2013) and Seeley and Jeevanjee (2020) with climlab and PyRADS

Created/Mantained By: Andrew Williams ([email protected])

Abstract:

To-do

• Go through a couple of the climlab tutorials and get a simple SCM model going.

• Iterate through various surface temperatures and calculate the ECS for each one.

• Calculate decomposition into $F_2x$ and $lambda_eff$ terms.

• Qu: Can climlab's RRTMG interface give the spectrally resolved OLR? Like, averaged in its 16 LW bands? That would be cool

• Edit: Not really, it'd be a bit of work I think - not worth it for now.

• EDIT: See this climlab issue I raised, hopefully it should result in a PR which allows access to the underlying RRTMG_LW fluxes through climlab! :)

• EDIT: PR submitted!

• Use PyRADS for a simple spectral decomposition of the OLR changes. Do we see the H20 windows and C02 radiator fins??

Installation

An environment.yml file is provided from which you can generate an ecsbump environment with the command conda env create --file environment.yml.

To add this environment to you jupyter lab instance, you must first activate this environment and then run ipython kernel install --user --name=ecsbump.

My custom version of climlab can be installed by running git clone https://github.com/AndrewWilliams3142/climlab.git, cd climlab, git checkout spectral_lw and then running python -m pip install . --no-deps -vv

PyRADS

To run the sections involving PyRADS, you should follow the installation instructions on the github repo, then set the os.chdir() command in the notebook to wherever you've cloned PyRADS.

Also, you can directly clone my PyRADS fork and use the ecsbump branch, which comes with a setup.py file and the changes to OpticalThickness.py described in the main notebook.

Acknowledgements:

Thanks to Brian Rose for creating climlab, which allows for a convenient Python interface to RRTMG, and also a suite of exciting options for open-source climate modelling!

Also thanks to Daniel Koll for creating and maintaining PyRADS, which is the line-by-line code I use here and which also has an intuitive Python API. :)

References:

1. Seeley, J. T., & Jeevanjee, N. (2020). H2O windows and CO2 radiator fins: a clear‐sky explanation for the peak in ECS. Geophysical Research Letters, 47, e2020GL089609. https://doi.org/10.1029/2020GL089609

2. Meraner, K., Mauritsen, T., and Voigt, A. (2013), Robust increase in equilibrium climate sensitivity under global warming, Geophys. Res. Lett., 40, 5944– 5948, doi:10.1002/2013GL058118.