Published July 2, 2020 | Version 2.2.0
Software Open

"A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP": Python and R statistical scripts of the study

Creators

  • 1. Department of Meteorology, Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
  • 2. Blue Skies Research Ltd, Settle, United Kingdom

Description

This code can be ran to estimate climate sensitivity by using the tropical temperature of the models participating in the Paleoclimate Modelling Intercomparison Project (PMIP) and simulating either the Last Glacial Maximum or the mid-Pliocene Warm Period.

Any climate properties can replace the variables x or y, following the theory of emergent constraints.

A detailed description of each method can be found in: M. Renoult, J.D. Annan, J.C. Hargreaves, N. Sagoo, C. Flynn, M.-L. Kapsch, Q. Li, G. Lohmann, U. Mikolajewicz, R. Ohgaito, X. Shi, Q. Zhang, T. Mauritsen, In Review. A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP. Climate of the Past.

The original repository and patch notes of the code can be found at https://git.bolin.su.se/bolin/renoult-2020

Notes

This result is part of the highECS project that has received funding from the European Research Council (ERC) (Grant agreement No.770765) and the CONSTRAIN project, the European Union's Horizon 2020 research and innovation program (Grant agreement No.820829).

Files

renoult_02_07_2020_Emergent_constraints.zip

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Additional details

Funding

highECS – Reining in the upper bound on Earth’s Climate Sensitivities 770765
European Commission
CONSTRAIN – Constraining uncertainty of multi decadal climate projections 820829
European Commission