This dataset consists of monthly spatial patterns of meteorological change for 34 Global Circulation Models (GCMs). The patterns are a set of regression coefficients, each representing the change per degree of mean global warming over land, for the corresponding meteorological variable. The meteorological variables analysed for each GCM include: surface temperature change per degree global warming (K K-1); surface relative humidity change per degree global warming (percentage of K-1); wind change per degree global warming (m s-1 K-1); longwave change per degree global warming (W m-2 K 1); shortwave change per degree global warming (W m-2 K-1); precipitation change per degree global warming (mm day-1 K-1) and pressure change per degree global warming (hPa K-1).
The supporting information document associated with this metadata includes parameters for an energy balance model (IMOGEN EBM) that calculates the amount of global warming. Each GCM output has been re-mapped on to UKMO-HadCM3 grid, with resolution of 3.75° longitude and 2.5° latitude; this produces a surface spatial resolution of about 417 km E-W x 278 km N-S, reducing to 295 km E-W x 278 km N-S at 45° North and South. This corresponds to 1631 land points, each of which has a row in the provided data files.
The data presented here is calibration of IMOGEN EBM parameters and patterns against 34 GCMs in the Coupled Model Intercomparison Project phase 5 (CMIP5) GCM ensemble.
Further information about the dataset and its derivation can be found in Comyn-Platt, E. et al. (in press). Carbon budgets for 1.5 and 2°C targets lowered by natural wetland and permafrost feedbacks. Nature Geoscience. http://doi.org/10.1038/s41561-018-0174-9
Publication date: 2018-06-26
The pattern-scaling set is derived from 34 global circulation models (GCM) of the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model dataset. For each GCM emulated, regression is performed for each meteorological variable, each month and each grid box against global mean warming over land.
The calibration against CMIP5 models has full numerical code documentation, traceability on demand and with scripts utilising open-access software. This meets the ISO standards for numerical model building and is available on request to Chris Huntingford.