Skip to main content

Python version of the CICERO-SCM simple climate model

Project description

This is the python version of the CICERO-SCM simple climate model/emulator.

The Cicero Simple Climate model was first developed over 20 years ago and has been in use at Cicero with various updated ever since. Broadly speaking, it goes from global emissions to concentrations, to radiative forcing to global temperature change. The model can beshort circuited to start at any of these inputs, running directly from forcing or concentrations rather than all the way. However, for shortlived forcers, forcing is calculated directly from emisssions, so emissions need to be supplied even in a concentration driven run.

The model includes a carbon cycle model introduced in a 1996 paper by Joos et al. The interplay between CO2, CH4 and N2O has been updated according to the 2016 work of Etminan et al. Otherwise, simplified impulse response functions take Tg emissions to concentrasions using lifetimes.

Natural emissions of CH4 and N2O should be time variable and tuned in order to fit historical evolution.

The forcing to temperature calculation is acheived via the 1992 Schlesinger upwelling diffusion model, calculating energy balance in a default set of 40 layered ocean with a box atmosphere for each hemisphere. Both forcing calculations and energy budget can be tuned using various user supplied parameters.

Currently, this is a fairly faithful python rendering of the pre-existing fortran model, albeit with some added flexibility, some AR6 updates, and a couple of bugfixes.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ciceroscm-1.1.2.tar.gz (1.3 MB view details)

Uploaded Source

Built Distribution

ciceroscm-1.1.2-py2.py3-none-any.whl (52.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file ciceroscm-1.1.2.tar.gz.

File metadata

  • Download URL: ciceroscm-1.1.2.tar.gz
  • Upload date:
  • Size: 1.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for ciceroscm-1.1.2.tar.gz
Algorithm Hash digest
SHA256 8b76d5f73d40c997ab8aa08b0a6cfd18a0b2f0cb68248e96ee16fcabc059e3f3
MD5 ed41689912407c65b32713a0205636bd
BLAKE2b-256 429ac2917127763d65fb477588a3b14cf219d57cddcdc1c7cba4de1c1bd587f9

See more details on using hashes here.

File details

Details for the file ciceroscm-1.1.2-py2.py3-none-any.whl.

File metadata

  • Download URL: ciceroscm-1.1.2-py2.py3-none-any.whl
  • Upload date:
  • Size: 52.3 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for ciceroscm-1.1.2-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 e8482c64cf99ec1036a4d3bc2887142bc996f7703a98dc2dfe4ff5fcfedd7c46
MD5 dbcb65832495a896d197364e13c15f68
BLAKE2b-256 fe9f74d9e565e1c20d8a3dfc8c441daadb3465d157e4015ec6be6dbb0cf21445

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page