Supplementary Materials for Past warming trend constrains future warming in CMIP6 models, Tokarska et al. 2020
Supplementary material for this article is available
Model code used in Mauritsen and Roeckner (2020) Tuning the MPI‐ESM1.2 Global Climate Model….
The model code used here can be obtained from the https://www.mpimet.mpg.de/en/science/models/ website.
Code used in Andrews and Forster (2020) Energy budget constraints on historical forcing
The code used to produce the energy budget constraint and Fig. 1 in this study is available via the online repository at https://github.com/timothyandrews/historical-radiative-forcing/
Model data used in Tokarska et al. (2019) Path independence of carbon budgets….
Model data used in this study is available at http://data.iac.ethz.ch/Tokarska_et_al_2019_Overshoot_UVicESCM/
Time-series of annual global surface air temperature anomaly data for the CMIP6 historical, SSP1-2.6, and SSP5-8.5 simulations
Supporting dataset for "Latest climate models confirm need for urgent mitigation", Forster P.M. et al. (2020) Nature Climate Change doi:10.1038/s41558-019-0660-0
Data used in Forster et al Emissions changes in 2020 due to COVID-19 (Forster, 2020)
Data are differences in either kt per day or Mt per day (for CO2) compared to annual averaged baseline emissions. Rows are days in 2020. Columns are ISO_A3 abbreviations of countries. Last two columns are international aviation and shipping. Two estimates are given: high and mid. Based on Google mobility data and EDGAR datasets. Data projected from day 120 until Day 366.
Case studies of climate sensitivity with PMIP: Python statistical codes (Renoult et al., 2020)
These 4 codes can be run 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. They link to Renoult et al. (in review), A Bayesian framework for emergent constraints: case studies of climate sensitivity with PMIP.