Supplementary material: Incremental improvements of 2030 targets insufficient to achieve the Paris Agreement goals
ANDREAS GEIGES; Alexander Nauels; Marina Andrijevic; Peter Pfleiderer
# NDC_ambition_ESD_paper_material
ANDREAS GEIGES; Alexander Nauels; Marina Andrijevic; Peter Pfleiderer
# NDC_ambition_ESD_paper_material
Code for Silicone
Dataset for: Wood et al Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing
Data for Stringent mitigation substantially reduces risk of unprecedented near-term warming rates
Data for Fig. 2, and additional figures comparing SSPs and RCPs, are available from https://github.com/Priestley-Centre/CMIP5_CMIP6_FaIR_gsat_data.
Three-dimensional large eddy simulation and a bulk sea ice model to examine the lifecycle of clouds formed during wintertime advection of moist and warm air over sea ice, following a Lagrangian perspective.
Access to primary data is provided on the MPG site.
These data in .csv file format are available from:
C4MIP http://www.c4mip.net/index.php?id=3387
CDRMIP https://www.kiel-earth-institute.de/CDR_Model_Intercomparison_Project.html websites.
The PDRMIP model output is publicly available on CICERO website
Calculation of radiative forcing and effective radiative forcing of global aviation impacts
This dataset provides radiative kernels based on the HadGEM3-GA7.1 atmospheric model. The kernels are produced with respect to a pre-industrial baseline
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/
Anomaly data for the CMIP6 historical, SSP1-2.6, and SSP5-8.5 simulations
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.
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.