Description

One of the ways of obtaining local-scale climate change scenarios is to use regression-based statistical downscaling of GCMs. In this approach, an empirical relationship between GCM predictors (i.e., near-surface and upper-level atmosphere circulation variables) and surface predictands (such as observed temperature or precipitation from a station) is derived by linear or non-linear transfer functions. For this purpose, an ensemble of daily predictor variables are produced from CanESM5, MPI-ESM1.2-HR, NorESM2-MM, and two reanalysis datasets. A total of 26 predictor variables are included in each ensemble, composed of both raw and derived variables, with multiple atmospheric variables available at three different pressure levels. Predictor variables are available at the daily scale on a 64 by 128 latitude-longitude global Gaussian grid with T42 spectral truncation. The historical simulation for 1979-2014 as well as the four Tier 1 Shared Socioeconomic Pathways (SSPs) prioritized by the Intergovernmental Panel on Climate Change (IPCC) and Scenario Model Intercomparison Project (ScenarioMIP) (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) and SSP1-1.9 (due to its relevance for the Paris Agreement) for 2015-2100 are available for each GCM (O'Neill et al., 2016). Two reanalysis dataset options are available for the historical period 1979-2014 (ECMWF ERA5 and NCEP-DOE Reanalysis 2). GCMs chosen for inclusion into the CMIP6 predictors dataset was determined by three factors. Firstly, the equilibrium climate sensitivity (ECS) must have been calculated according to the Gregory methodology and the selected GCMs must cover a range of ECS values (see sections 1.1. and 1.2.). Secondly, the GCM must have run the historical simulation and as many of the five SSPs as possible (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Thirdly, for the relevant simulations, the seven base variables at all three included pressure levels (if applicable) must be available for download on Earth System Grid Federation (ESGF) website (https://esgf-node.llnl.gov/search/cmip6/).

Resources

Name	Format	Description	Link
CMIP6 ensemble of daily predictor variables (EN)	ZIP		https://climate-scenarios.canada.ca/?page=pred-cmip6
The ensemble of CMIP6 daily predictor variables for statistical downscaling (EN)	HTML		https://climate-scenarios.canada.ca/?page=pred-cmip6-notes
CMIP6 ensemble of daily predictor variables (FR)	ZIP		https://scenarios-climatiques.canada.ca/?page=pred-cmip6
The ensemble of CMIP6 daily predictor variables for statistical downscaling (FR)	HTML		https://scenarios-climatiques.canada.ca/?page=pred-cmip6-notes

Tags

Topics

Categories