Statistically downscaled climate indices from CMIP6 global climate models (CanDCS-U6 & CanDCS-M6)

Environment and Climate Change Canada’s (ECCC) Climate Research Division (CRD) and the Pacific Climate Impacts Consortium (PCIC) previously produced statistically downscaled climate scenarios based on simulations from climate models that participated in the Coupled Model Intercomparison Project phase 5 (CMIP5) in 2015. ECCC and PCIC have now updated the CMIP5-based downscaled scenarios with two new sets of downscaled scenarios based on the next generation of climate projections from the Coupled Model Intercomparison Project phase 6 (CMIP6). The scenarios are named Canadian Downscaled Climate Scenarios–Univariate method from CMIP6 (CanDCS-U6) and Canadian Downscaled Climate Scenarios–Multivariate method from CMIP6 (CanDCS-M6).



CMIP6 climate projections are based on both updated global climate models and new emissions scenarios called “Shared Socioeconomic Pathways” (SSPs). Statistically downscaled datasets have been produced from 26 CMIP6 global climate models (GCMs) under three different emission scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5), with PCIC later adding SSP3-7.0 to the CanDCS-M6 dataset. The CanDCS-U6 was downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2) procedure, and the CanDCS-M6 was downscaled using the N-dimensional Multivariate Bias Correction (MBCn) method. The CanDCS-U6 dataset was produced using the same downscaling target data (NRCANmet) as the CMIP5-based downscaled scenarios, while the CanDCS-M6 dataset implements a new target dataset (ANUSPLIN and PNWNAmet blended dataset).



Statistically downscaled individual model output and ensembles are available for download. Downscaled climate indices are available across Canada at 10km grid spatial resolution for the 1950-2014 historical period and for the 2015-2100 period following each of the three emission scenarios.



A total of 31 climate indices have been calculated using the CanDCS-U6 and CanDCS-M6 datasets. The climate indices include 27 Climdex indices established by the Expert Team on Climate Change Detection and Indices (ETCCDI) and 4 additional indices that are slightly modified from the Climdex indices. These indices are calculated from daily precipitation and temperature values from the downscaled simulations and are available at annual or monthly temporal resolution, depending on the index. Monthly indices are also available in seasonal and annual versions.



Note: projected future changes by statistically downscaled products are not necessarily more credible than those by the underlying climate model outputs. In many cases, especially for absolute threshold-based indices, projections based on downscaled data have a smaller spread because of the removal of model biases. However, this is not the case for all indices. Downscaling from GCM resolution to the fine resolution needed for impacts assessment increases the level of spatial detail and temporal variability to better match observations. Since these adjustments are GCM dependent, the resulting indices could have a wider spread when computed from downscaled data as compared to those directly computed from GCM output. In the latter case, it is not the downscaling procedure that makes future projection more uncertain; rather, it is indicative of higher variability associated with finer spatial scale.



Individual model datasets and all related derived products are subject to the terms of use ( https://pcmdi.llnl.gov/CMIP6/TermsOfUse/TermsOfUse6-1.html) of the source organization.

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Metadata Record Information

File Identifier
764720d5-8c0a-4e1e-93fc-d9e3eb0ab6b3 XML
Date Stamp
2024-08-13T14:44:49.117Z
Metadata language

eng; CAN
Character set
UTF8
Hierarchy Level
Dataset
Point of contact
  Government of Canada; Environment and Climate Change Canada; Science and Technology Branch (STB) / Atmospheric Science and Technology Directorate (ASTD) / Climate Research Division (CRD)

 

Data identification

Title

Statistically downscaled climate indices from CMIP6 global climate models (CanDCS-U6 & CanDCS-M6)
Date (Publication)
2022-03-31
Date (Creation)
2021-01-21
Status
Completed
Metadata language

eng; CAN
Character set
utf8
Topic category
  • Climatology, meteorology, atmosphere
Maintenance and Update Frequency
As needed
Spatial representation type
Grid
Publisher
  Government of Canada; Environment and Climate Change Canada; Science and Technology Branch (STB) / Atmospheric Science and Technology Directorate (ASTD) / Climate Research Division (CRD)

Keywords

Government of Canada Core Subject Thesaurus

  • Climate

  • Models

  • Statistical analysis

Business Functions

  • Provide Climate Information Products and Services

  • Expand Scientific Knowledge for Climate Monitoring and Prediction

GC Organization Names

  • Government of Canada

Branch

  • Science and Technology Branch

Directorate

  • Atmospheric Science and Technology

ECCC Resource Formats EN

  • NetCDF

ECCC Geographic Scope EN

  • National (CA)
 
Use Limitation

Open Government Licence - Canada ( http://open.canada.ca/en/open-government-licence-canada)

Access Constraints
License
Use Constraints
License
Begin Date
1951-01-01
End Date
2100-12-31

Extent

N
S
E
W
thumbnail




 
 

Ref. system Reference Systems

Reference system identifier
http://www.epsg-registry.org / EPSG:4326 /
 

Distribution

Distribution Formats

Distribution format
  • NetCDF ( unknown)

 
Distributor
  Government of Canada; Environment and Climate Change Canada; Science and Technology Branch (STB) / Atmospheric Science and Technology Directorate (ASTD) / Climate Research Division (CRD)

 
 

Overviews

N
S
E
W
thumbnail




Keywords

Branch

Science and Technology Branch
Business Functions

Expand Scientific Knowledge for Climate Monitoring and Prediction Provide Climate Information Products and Services
Directorate

Atmospheric Science and Technology
ECCC Resource Formats EN

NetCDF
GC Organization Names

Government of Canada
Government of Canada Core Subject Thesaurus

Climate Models Statistical analysis


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