Nivar

Nivar

Performance Evaluation of the WRF Weather Forecast Model in Estimating Heavy Rainfall in Lorestan Province

Document Type : Original Article

Authors
Fatemeh Falah 1
Hossein Zeinivand 2
Majid Azadi 3
1 Lorestan university
2 Lorestan University
3 Academic Board of Research Institute of Meteorology and Atmospheric Sciences
10.30467/nivar.2025.504939.1323
Abstract
Accurate and reliable precipitation forecasting, as a critical component of meteorology, plays a pivotal role in water resource management and in mitigating natural hazards such as floods and droughts. In recent decades, Numerical Weather Prediction (NWP) models have emerged as powerful tools for forecasting precipitation and other atmospheric phenomena. Among them, the Weather Research and Forecasting (WRF) model is widely applied due to its high capability in simulating atmospheric processes and providing accurate forecasts at multiple spatial and temporal scales. This study evaluates the performance of the WRF model in estimating average precipitation over Lorestan Province, Iran. Simulations were performed for a 97-hour forecast horizon covering five flood-inducing events during rainy days in March 2019, April 2018, March 2017, and April 2016. Three nested domains with spatial resolutions of 1.5 km, 5 km, and 6.1 km, and three distinct model configurations were employed. Global Forecast System (GFS) data served as the initial and boundary conditions, and simulation results were compared with observational records from synoptic meteorological stations in the province. The results indicate that the configuration combining the Kain–Fritsch (new Eta) cumulus parameterization, Lin et al. microphysics, Rapid Radiative Transfer Model (RRTM) longwave radiation, Goddard shortwave radiation, and YSU boundary layer scheme yielded the highest accuracy in reproducing average precipitation across the study area. These findings highlight the importance of appropriate model configuration in enhancing WRF’s predictive skill for heavy rainfall events in complex mountainous regions such as Lorestan.
Keywords
Convective parameterization
Precipitation simulation
YSU boundary layer
Lorestan Province
Subjects
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  • Receive Date 06 February 2025
  • Revise Date 12 August 2025
  • Accept Date 25 August 2025
  • Publish Date 23 September 2025