Skip to main content

Modular Earth System Model Emulator with spatially Resolved output

Project description

MESMER: spatially resolved Earth System Model emulations

MESMER is a Modular Earth System Model Emulator with spatially Resolved output, which stochastically creates Earth System Model-specific spatio-temporally correlated climate variable field realizations at a negligible computational cost.

In combination with a global mean temperature emulator, MESMER can account for all three major sources of climate change projection uncertainty at the local scale: (i) internal variability uncertainty, i.e., unforced natural climate variability; (ii) forced climate response uncertainty, i.e., the Earth’s system response to forced natural changes (solar and volcanic) and human influences (greenhouse gas and aerosol emissions, land use changes etc.); and (iii) emission uncertainty, i.e., uncertainty in the emission pathway humans decide to follow. An interface between MESMER and global mean temperature emulators can be found at https://github.com/MESMER-group/mesmer-openscmrunner.

MESMER is under active development both scientifically and technically. Future work will increase its user friendliness and extend its emulation capabilities to include additional emulation methods and target climate variables.

Citing MESMER

Scientific publications using MESMER should cite the following publication:

Beusch, L., Gudmundsson, L., and Seneviratne, S. I.: Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land, Earth Syst. Dynam., 11, 139–159, https://doi.org/10.5194/esd-11-139-2020, 2020.

If MESMER is used to emulate multiple emission pathways and/or in combination with a global mean emulator, the following publication should additionally be cited:

Beusch, L., Nicholls, Z., Gudmundsson, L., Hauser, M., Meinshausen, M., and Seneviratne, S. I.: From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3), Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, 2022.

License

Copyright (c) 2021 ETH Zurich, MESMER contributors listed in AUTHORS.

MESMER is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 or (at your option) any later version.

MESMER is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with MESMER. If not, see https://www.gnu.org/licenses/.

The full list of code contributors can be found in AUTHORS or on github.com/contributors

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

mesmer-emulator-0.9.0.tar.gz (11.3 MB view details)

Uploaded Source

Built Distribution

mesmer_emulator-0.9.0-py3-none-any.whl (90.4 kB view details)

Uploaded Python 3

File details

Details for the file mesmer-emulator-0.9.0.tar.gz.

File metadata

  • Download URL: mesmer-emulator-0.9.0.tar.gz
  • Upload date:
  • Size: 11.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.6

File hashes

Hashes for mesmer-emulator-0.9.0.tar.gz
Algorithm Hash digest
SHA256 a3fb96410f206ea0c091b3218ed3aaf6187c73df65e69542bc487a0ecfb3bc6c
MD5 6f593099c81d2c6eed1f965fccde9fd6
BLAKE2b-256 b9631bc1a2795933e4929f24596fb0620849e98c970d334097c49810be2bf7b7

See more details on using hashes here.

Provenance

File details

Details for the file mesmer_emulator-0.9.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mesmer_emulator-0.9.0-py3-none-any.whl
Algorithm Hash digest
SHA256 bc3cc91d99a67a1e3a9d11c5311e015f1a639ee862dd2d4769bd5997ab4d3b9b
MD5 2ee7a815375bce8a73989869664deb77
BLAKE2b-256 fc248f30d291c2408293bf6716cc350c7d4025f05364db487fe2b69a5697fe23

See more details on using hashes here.

Provenance

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