Carbon budget calculator
Description
Calculates remaining carbon budget given atmospheric simulation inputs. A copy of the github record https://github.com/Rlamboll/AR6CarbonBudgetCalc/releases/tag/v1.0.0
The workhorse script is src/run_budget_calculator.py
, with options to change it found at the top of the file.
The calculation is based on the framework in Estimating and tracking the remaining carbon budget for stringent climate targets, Rogelj et al. 2019. This revolves around five terms: the warming to date (input directly), the non-CO2 warming (calculated from scenarios analysed previously by MAGICC or FaIR), the zero-emissions commitment (ZEC, input directly), the transient climate response to cumulative emissions of CO2 (TCRE, parameters are input for a distribution which may be either lognormal or normal) and unrepresented Earth feedbacks (a linear function of temperature change).
By changing the default values this code can replicate the values in the IPCC reports for AR6 WGI and WGIII.
With runver = sr15prewg1, zec_sd = 0, recent_emissions=209
this replicates Table 5.8 in Chapter 5 (Canadell et al, 2021), Table TS.3 in the Technical Summary (Arias et al, 2021) and Table SPM.2 of the Summary for Policymakers (IPCC, 2021) of the IPCC AR6 WGI report. Note that values reported in the report are rounded to the nearest 10 PgC or 50 GtCO2 and the impact of ZEC standard deviation are tabulated separately. All the reports use the MAGICC True, FaIR False scenario.
With zec_sd = 0, recent_emissions=209
this replicates the carbon budget results in chapter 3 (Riahi et al, 2022) of the IPCC AR6 WG3 report.
With peak_version = "nonCO2AtPeakAverage", List_use_permafrost=[True], norm_nonco2_years=True, nonlinear_nonco2 = "QRW"
this replicates our recommended update.
With recent_emissions=204, historical_dT = 1.15
this replicates the results in "Indicators of Global Climate Change 2022: annual update".
The code expects to find data from MAGICC and/or FaIR simulations in the InputData
folder in the format output for a pyam dataframe. Alternatively unprocessed FaIR data may be provided as folders of .nc or .hfd files, which can be processed into pyam format.
Notes
Files
AR6CarbonBudgetCalc-1.0.1.zip
Files
(406.8 MB)
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