Download CMIP6 statistically downscaled climate indices (CanDCS-U6 & CanDCS-M6)

Access datasets of statistically downscaled climate indices based on model projections from 26 global climate models. Multi-model ensembles or individual model output may be temporally and spatially defined, and filtered by the desired index, scenario, and model. The indices are categorized by the following: temperature indices, precipitation indices, and degree days or agroclimatic indices. Select a geographic area either by clicking and dragging your mouse on the map or by entering the latitude and longitude coordinates below the map. Data cannot be provided with the selection of a single grid point location.

Three datasets are provided on this page, two sets of Climdex indices calculated with two different downscaling methods, CanDCS-U6 (univariate downscaling) and CanDCS-M6 (multivariate downscaling), and one set of agroclimatic indices calculated from the CanDCS-U6. More information on the datasets provided can be found by clicking on the info button next to the dataset selection below. Technical notes are available for the Climdex and agroclimatic datasets as well as definitions tables for both Climdex and agroclimatic indices.

Temperature datasets for three models in the CanDCS-U6 dataset were updated in August 2023. These updates corrected some anomalously high temperatures in the original data. The Climdex and agroclimatic indices based on the CanDCS-U6 dataset have been recalculated and were updated using the corrected data in August 2023. Additional details on the updated datasets and correction methods can be found in the technical notes.

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CanDCS-U6: Canadian Downscaled Climate Scenarios–Univariate method from CMIP6

CanDCS-M6: Canadian Downscaled Climate Scenarios–Multivariate method from CMIP6

CMIP6 statistically downscaled agroclimatic indices (derived from the Can DCS-U6 scenarios)

The statistical downscaling and calculation of indices for the CanDCS-U6 and M6 datasets was done by the Pacific Climate Impacts Consortium (PCIC). The CanDCS-U6 was downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2) procedure. The CanDCS-M6 was downscaled using the N-dimensional Multivariate Bias Correction (MBCn) method. Both datasets include the same global climate models, variables (daily maximum temperature, minimum temperature, and precipitation), time period (1950-2100), and Shared Socioeconomic Pathways (SSPs) (SSP1-2.6, SSP2-4.5, and SSP5-8.5). For more details on the CanDCS-U6 and M6 datasets, please see the technical notes and the indices definitions table.

To address the needs of different user groups in Canada, the ECCC climatic and agroclimatic indices were proposed by the Canadian adaptation community through a series of consultations. The indices were derived from the CanDCS-U6 scenarios dataset of minimum and maximum temperature, and precipitation. For more details on the ECCC’s CMIP6 statistically downscaled agroclimatic indices, please see the technical notes and the definition list for the equations of each index.

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Note: The data is provided in NetCDF format. Full datasets may take longer to download due to large file size. If you experience difficulty downloading the datasets please email us at f.ccds.info-info.dscc.f@ec.gc.ca

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Date modified:: 2019-03-01