The Version 7.0 (October, 2023) of the IDF_CC tool, includes:

This enhanced version introduces a new feature, allowing users to construct custom multi-model ensembles utilizing the Global Climate Models available in the tool's extensive database. This update provides users with increased flexibility in generating multi-model ensembles for updating IDF curves.

In this latest version, users now have the following options available:
(i) Utilize the existing "All models" ensemble option,
(ii) Opt for a single model selection, or
(iii) Create a custom ensemble combining any number of available climate models.


The Version 6.5 (March, 2023) of the IDF_CC tool, includes:

This updated version now offers the option to update IDF curves using the Gumbel distribution, in addition to the GEV, providing users with more flexibility. Furthermore, the new version comes with an updated dataset of IDF curves (Version 3.3) from Environment and Climate Change Canada (ECCC), which includes precipitation data up to 2021 and changes in the names and/or codes of stations.

The Version 6.0 (February, 2022) of the IDF_CC tool, includes:

Version 6 includes a new dataset of bias-corrected climate models produced by the Pacific Climate Impacts Consortium (PCIC) of the University of Victoria, using the BCCAQ v2 downscaling method. The new dataset includes 26 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) that uses a new set of Shared Socioeconomic Pathway (SSP) scenarios.

Detailed information about the models and the methodology used in producing the bias-corrected models can be found at: https://www.pacificclimate.org/data/statistically-downscaled-climate-scenarios

The Version 5.0 (July, 2021) of the IDF_CC tool, includes:

Version 5 (July, 2021) of the IDF_CC tool, includes the most updated coordinated set of climate experiments from the Coupled Model Intercomparison Project phase 6 (CMIP6). They provide for: (i) understanding of climate extremes in the past and future, (ii) better quantification of the impact of cloud cover towards the sensitivity of climate and general atmospheric circulation, (iii) enhanced understanding and prediction of regional sea-level changes, (iv) determining the impacts of a warming climate on the cryosphere, (v) quantifying factors that govern overland water availability, (vi) understanding the contribution of biogeochemical cycles in controlling GHGs and subsequent climate changes, and (vii) refining near-term climate predictions. CMIP6 represents a substantial expansion over CMIP5 (Eyring et al., 2016).

A new set of “Shared Socioeconomic Pathway” (SSPs) scenarios have been introduced to drive climate models for CMIP6. A set of scenarios were chosen to provide a range of distinct end-of-century climate change outcomes. The previous version of the tool included climate models from CMIP5 that were driven by four Representative Concentration Pathways (RCPs) that examined different possible future greenhouse gas emissions. These scenarios - RCP2.6, RCP4.5, RCP6.0, and RCP8.5 – have been updated for CMIP6. These updated scenarios are called SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, each of which result in similar 2100 radiative forcing levels as their predecessor in CMIP5. Please see more in the technical manual and the About section of the tool for more information.

Version 5 also includes an updated dataset of IDF curves from the Environment and Climate Change Canada (ECCC). The updated dataset includes precipitation data up to 2017, and changes in the names and/or code of stations introduced by ECCC:

The ECCC IDF dataset implemented in this version of the IDF_CC tool can be obtained from ECCC (version 3.20): http://climate.weather.gc.ca/prods_servs/engineering_e.html.

The Version 4.5 (January, 2021) of the IDF_CC tool, includes:

Updated dataset of IDF curves from the Environment and Climate Change Canada (ECCC) with precipitation data up to 2017

• New stations introduced by ECCC
• Changes in the names and/or code of stations introduced by ECCC
• The ECCC IDF dataset implemented in this version of the IDF_CC tool can be obtained from ECCC (version 3.10): http://climate.weather.gc.ca/prods_servs/engineering_e.html.

New publication (June, 2020) - Ungauged locations

Very recently, as part of the regular IDF_CC tool update, we successfully published a paper that describes in detail the new dataset and module for ungauged locations in Canada. With this module, users can obtain IDF curves for any location in the country, including regions where no station observations are available. We are strongly encouraging users of the tool to read the publication Gaur, A., A. Schardong, and S.P. Simonovic (2020) "Gridded Extreme Precipitation Intensity–Duration–Frequency Estimates for the Canadian Landmass" that presents the methodology.
The paper is available from: https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0001924?af=R&. The full paper can also be obtained upon direct request to the authors.

New publication (May, 2020) – New version of the tool

As part of the regular IDF_CC tool update, a new publication on details of Version 4 of the IDF_CC tool, including formal description of the methodology used, is now available: Schardong, A., S. P. Simonovic, A. Gaur, and D. Sandink (2020) “Web-based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations”, Water, Special Issue Extreme Value Analysis of Short-Duration Rainfall and Intensity–Duration–Frequency Models, 12, 1243; doi:10.3390/w12051243, open access, https://www.mdpi.com/2073-4441/12/5/1243/pdf.
We are strongly encouraging you to check this new publication.

The Version 4.0 (August, 2019) of the IDF_CC tool, includes:

The Version 4 includes a new dataset of bias-corrected climate models produced by the Pacific Climate Impacts Consortium (PCIC) of the University of Victoria, using the BCCAQ v2 (available at the http://climate-scenarios.canada.ca/ portal).
The new dataset, containing 24 climate models, is incorporated into the IDF_CC tool database. Detailed information about the models and the methodology used in producing the bias-corrected models can be found at: https://www.pacificclimate.org/data/statistically-downscaled-climate-scenarios

New publication (June, 2019) – Use of regional climate models

As part of the regular IDF_CC tool update, we investigated potential use of regional climate models (RCMs) for updating IDF relationships. In this, we analyzed the difference in updated IDF (Intensity-Duration-Frequency) relationships developed using global climate models (GCMs) and RCMs. The analyses are conducted using 369 selected Environment and Climate Change Canada hydro-meteorological stations from the IDF_CC tool database with record length longer than 20 years. A number of comparison experiments and two evaluation criteria were implemented. The RCMs generated lower extreme precipitation projections than the GCMs for the stations located in the Canadian prairies (provinces of Alberta, Saskatchewan, Manitoba). Stations located at the East and West coasts of Canada show a smaller difference in the projected extremes obtained using GCMs and RCMs. The use of RCMs shows increase in uncertainty when compared to GCMs. This result indicates that even when using regional climate models, it’s advisable to extend the analyses and include as many as possible models from different climate centers. We are strongly encouraging users of the tool to read the publication Schardong, A., and S.P. Simonovic (2019) "Application of Regional Climate Models for Updating Intensity-duration-frequency Curves under Climate Change", International Journal of Environment and Climate Change 9(5): 311-330, 2019, that documents the comparison. The paper is available upon direct request to the authors.

The Version 3.5 (May, 2019) of the IDF_CC tool, includes:

Updated dataset of IDF curves from the Environment and Climate Change Canada (ECCC) with precipitation data up to 2017

• New stations introduced by ECCC
• Changes in the names and/or code of stations introduced by ECCC
• The ECCC IDF dataset implemented in this version of the IDF_CC tool can be obtained from ECCC (version 3.00, dated Feb 27, 2019): http://climate.weather.gc.ca/prods_servs/engineering_e.html.

The Version 3.0 (December, 2018) of the IDF_CC tool was updated with many new features (see Version 3 Technical Manual for details). Main features of the updated version include:

• IDFs for ungauged locations: Version 3 of the tool introduces a new dataset of IDF curves for ungauged locations in Canada. With the new module, users can obtain IDF curves for any location in the country, including regions where no station observations are available.
  
  
• A new user interface: A user-friendly and efficient interface provides for easy tool use.
  
  
• Bias corrected climate models: Bias corrected models developed by the Pacific Climate Impacts Consortium (PCIC) for Environment Canada (PCIC, 2013) have been added to the tool's climate model base, in addition to the Global Circulation Models (GCMs) used with Version 1. Statistically downscaled daily Canada-wide climate scenarios, at a gridded resolution of 300 arc-seconds (0.0833 degrees, or roughly 10 km) for the simulated period of 1950-2100 are used in this updated version of the tool. Daily precipitation from nine bias corrected climate models were added to the Tool. The data is available for three Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5) (Meinshausen et al., 2011). The downscaled outputs are based on Global Climate Model (GCM) projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al., 2012) and historical daily gridded climate data for Canada (McKenney et al., 2011).
  
  
• Generalized Extreme Value (GEV) distribution: Version 3 of the tool uses GEV as the primary distribution to fit and update IDF data. The Gumbel distribution used by Environment and Climate Change Canada for fitting IDF data is outdated and is only kept within this version to provide users with the opportunity to compare official IDF curves obtained using historical data with those obtained by the IDF_CC tool.
  
  
  • Many recent studies have shown that GEV distribution provides better fit to annual maximum precipitation (AMP) series than the Gumbel distribution (summarized in Millington et al., 2011). The L-moments method (Hosking, 1997) has been employed in the new version of the tool for GEV parameter estimation. The IDF updating procedure has also been modified to reflect the use of the GEV distribution (see the Version 2 Technical Manual for details).
  
  
  

References:

• Hosking, J.R.M., Wallis, J.R. (1997). “Regional Frequency Analysis”. Cambridge University Press, Cambridge
• McKenney, D.W., M.F. Hutchinson, P. Papadopol, K. Lawrence, J. Pedlar, K. Campbell, E. Milewska, R. Hopkinson, D. Price, and T. Owen, (2011): Customized spatial climate models for North America. Bulletin of the American Meteorological Society, 92, 12, 1611-1622.
• Meinshausen, M., S. J. Smith, K. Calvin, J. S. Daniel, M. L. T. Kainuma, J-F. Lamarque, K. Matsumoto, S. A. Montzka, S. C. B. Raper, K. Riahi, A. Thomson, G. J. M. Velders, D.P. P. van Vuuren (2011): The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109(1-2), 213-241.
• Millington D., S. Das, and S.P. Simonovic (2011): The Comparison of GEV, Log-Pearson Type 3 and Gumbel Distributions in the Upper Thames River Watershed under Global Circulation Models, Millington, N., S. Das, and S.P. Simonovic (2011). Water Resources Research Report no. 077, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, London, Ontario, Canada, 53 pages. ISBN: (print) 978-0-7714-2898-2; (online) 978-0-7714-2905-7. Available at: http://www.eng.uwo.ca/research/iclr/fids/publications/products/77.pdf , last accessed July 2017.
• PCIC (2013): Data Portal. Available at https://pacificclimate.org/data , last accessed July 2017.
• Taylor, K.E., R.J. Stouffer, and G.A. Meehl, (2012): An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society, 93, 485–498.
• Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016). Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), 1937-1958.