Technical documentation: CMIP6 drought indices

On this page

• Overview
• Data and processing
• Multi-model simulations
• Best practice
• Interpreting drought projection results
• Use limitation
• Contact information
• References

Overview

Drought indices derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are provided. Variables include the Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Runoff Index (SRI), and Standardized Soil Moisture Index (SSI), representing meteorological, hydrological, and agricultural droughts, respectively. Intermediate datasets are also available, including potential evapotranspiration (PET), water balance (monthly precipitation minus PET), climate moisture index (CMI; annual precipitation minus PET), actual surface soil moisture, and actual surface runoff.

The projected indices should be interpreted as a relative measure of surface water surplus (for positive values) or deficit (negative values) with respect to the hydroclimate of the reference period. Please see Bonsal et al. (2024) for more details on the methodology.

Climate projections vary across GCMs due to differences in the representation and approximation of earth systems and processes, and natural variability and uncertainty regarding future climate drivers. As a result, it is common practice to use a multi-model ensemble, or average across many GCMs, as opposed to using a single GCM in isolation. For this purpose, the Canadian Climate Data and Scenarios (CCDS) site has a suite of drought indices, variables, scenarios, future time periods, and percentiles (see CMIP6 drought indices). Only one realization member from each model was included in the multi-model ensembles, giving each model equal weight.

Data and processing

Multi-model simulations

Potential evapotranspiration (PET) is subtracted from precipitation to calculate SPEI. PET was calculated using the Penman-Monteith method (which incorporates wind speed, humidity, radiation, and air temperature from the various GCMs)^Reference2. Temperature and precipitation were bias corrected prior to the calculation of SPEI. SPEI was calculated by summing the difference between precipitation and PET accumulated over n months, representing a simplified climatic water balance, which is then standardized to a normal (Gaussian) distribution^{Reference1 Reference3}. The Pearson Type 3 probability distribution was used to fit the climatic water balance (precipitation minus PET) to yield SPEI values with a reference period of 1950-2014 for parameter calibration. Additional details on how SPEI was calculated are described in Tam et al. (2023)^Reference2.

Hydrological drought is represented by GCM-derived surface runoff leaving the land portion of the grid cell, excluding drainage through the base of the soil model (in mm/day). Surface runoff simulations were standardized using the generalized extreme value probability distribution, with a baseline reference period, 1950-2014, to produce the Standardized Runoff Index (SRI).

Agricultural drought is represented by GCM-derived surface (10 cm) soil moisture measured in kg/m². Surface soil moisture was standardized using the Pearson Type 3 probability distribution with a reference period of 1950-2014 for parameter calibration, producing the Standardized Soil Moisture Index (SSI). Please see Bonsal et al. (2024) for more details on SSI and SRI calculations.

Multi-model SPEI, SRI and SSI datasets for historical simulations and three emission scenarios, SSPs 1-2.6, 2-4.5, 5-8.5, are available at a 1x1 degree grid resolution. Both multi-model ensembles and individual model output are available for download. Table 2 shows model availability for each drought index.

Best practice

Given the range of natural climate variability and uncertainties regarding future greenhouse gas emission pathways and climate response, results projected by one climate model should not be used in isolation. Rather, it is good practice to consider a range of projections from multiple climate models (ensembles) and emission scenarios.

While likelihoods are not associated with particular climate change scenarios, the use of a range of scenarios may help convey to users the potential spread across a range of possible emission pathways.

Interpreting drought projection results

Projected changes in SPEI, SRI, and SSI in Canada under various scenarios are available for download. Standardized drought projections should be interpreted as a relative measure of surface water surplus or deficit with respect to hydroclimate conditions of the reference period, 1950-2014. Thus, results of surface water deficit may be interpreted as dryness or, in other words, an indicator of drought conditions.

Further, results at a location gives the number of standard deviations by which the transformed variable deviated from the mean values assessed for the reference period. As SPEI, SRI, and SSI are normalized indices, a value of zero would indicate no change relative to historical values. The results presented herein are aimed at informing assessments of droughts based on relative changes with respect to observed conditions.

A range of indices have been developed over the years to understand and quantify the different types of drought, each varying in theoretical methodology, application, and formulation. SPEI, SRI, and SSI are three of the many indices to quantify drought severity, frequency, and intensity. Each index has its own utilities; the choice of a drought index would therefore depend on context or application as well as data availability.

SPEI, SRI, and SSI serve as a reasonable metric for meteorological or climatological, hydrological, and agricultural drought conditions, respectively, though each have their own limitations in the interpretation of results. For example, SPEI may not be adequate for gauging surface water availability of cold regions, including most northern parts of Canada. This is because the formulations of SPEI do not consider snow and glaciers, which play a critical role in governing the supply and availability of surface water of such regions.

Use limitation

Multi-model ensembles made available through Environment and Climate Change Canada websites are provided under the Open Government Licence - Canada.

In addition to these terms and conditions, individual model datasets are subject to the terms of use of the source organization.

Contact information

Email: f.ccds.info-info.dscc.f@ec.gc.ca