Abstract

A coupled atmospheric-hydrologic system models the complex interactions between the land surface and the atmospheric boundary layer and the water-energy cycle from groundwater across the land surface to the top of the atmosphere. A regional climate model called weather research forecasting (WRF) was coupled with a land-surface scheme (Noah) to simulate intensive storms in Alberta of Canada. Accounting for the land-atmosphere feedback enhances the predictability of the fine-tuned WRF-Noah system. Soil moisture, vegetation, and land-surface temperature influence latent and sensible heat fluxes and modulate both thermal and dynamical characteristics of land and the lower atmosphere. WRF was set up in a two-way, 3-domain nested framework so that the output of the outermost domain (D1) was used to run the 2nd domain (D2), and the output of D2 was used to run the innermost, 3rd domain (D3). By this 2-way nesting, D3 and D2 provide the feedback to their outer domains (D2 and D1), respectively. D3 was set at a 3-km resolution adequate to simulate convective storms. WRF-Noah was forced with climate outputs from global climate models (GCMs) for the baseline period 1980–2005. A regional frequency analysis and a quantile-quantile bias correction method were applied to develop intensity-duration-frequency (IDF) curves using precipitation data simulated by WRF-Noah. The simulated baseline precipitation of central Alberta agrees well with observed data from a 13-rain gauge network of the City of Edmonton. The 5th-generation mesoscale atmospheric model (MM5) of National Center for Atmospheric Research was also set up in a 3-domain, but 1-way nesting configuration. As expected, after bias correction, precipitation simulated by MM5 was less accurate than that simulated by WRF-Noah. For storms of short durations and return periods of more than 25 years, both MM5 driven by special reports on emission scenario climate scenarios of coupled model inter-comparison project (CMIP3) and WRF-Noah driven by representative concentration pathway climate scenarios of CMIP5 projected storm intensities in central Alberta to increase from the base period to the 2050s and to the 2080s.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This study was partly funded by the National Science and Engineering Research Council of Canada (NSERC) and the Drainage Services of the City of Edmonton, which also provided the observed RG data for Edmonton. The supercomputing resources were provided by the Westgrid of Compute Canada.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 28Issue 3March 2023

History

Received: Jul 8, 2022
Accepted: Oct 14, 2022
Published online: Dec 16, 2022
Published in print: Mar 1, 2023
Discussion open until: May 16, 2023

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Kai Ernn Gan
Dept. of Computer Science, Univ. of Pennsylvania, Philadelphia, PA 19104; Dept. of Civil Engineering, McMaster Univ., Hamilton, ON, Canada L8S 4L7.
Chun Chao Kuo, Ph.D.
River Forecast Centre, Government of British Columbia, Victoria, BC, Canada V8W 9V1.
Professor, Dept. of Civil and Environmental Engineering, Univ. of Alberta, Edmonton, AB, Canada T6G 1H9 (corresponding author). ORCID: https://orcid.org/0000-0002-5196-2846. Email: [email protected]
Professor, Institute of Hydraulic Engineering and Water Resources Management, Rhine-Westphalia Technical Aachen Univ., Aachen, Germany. ORCID: https://orcid.org/0000-0002-0104-0499
Professor, Dept. of Biological and Agricultural Engineering, Texas A&M Univ., College Station, TX 77843-2117. ORCID: https://orcid.org/0000-0003-1299-1457
Harri Koivusalo
Professor, Dept. of Built Engineering, Aalto Univ., Espoo 02150, Finland.

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