Iranian Journal of Geophysics

Iranian Journal of Geophysics

Assessment of the performance of the ensemble mean of an ensmble forecastiong system developed for the WRF model for weather prediction: A case study over the west part of Iran

Document Type : Research Article

Authors
Seyed Mahmoud Khansari 1
Seyed Hossein Sanaei Nejad 2
Amin Alizadeh 3
Azar Zarrin 3
Sarmad Ghader 4
1 Ph.D. Student, Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
2 Professor, Department of Water Science and Engineering, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran
3 Associate Professor, Department of Geography, Faculty of Letters and Humanities, Ferdowsi University of Mashhad, Mashhad, Iran
4 Professor, Department of Physics Space, Institute of Geophysics, University of Tehran, Tehran, Iran
10.30499/ijg.2025.495531.1656
Abstract
The use of meteorological models is one of the most suitable methods for forecasting atmospheric conditions. However, due to the complex nature of the atmosphere, these models sometimes struggle to provide accurate predictions. Innovative methods are being developed to enhance forecasting accuracy, among which the ensemble forecasting method is notable. This study presents results from the development of an ensemble forecasting system for the WRF model aimed at predicting 10-meter wind fields, air temperature, and 24-hour cumulative precipitation in western Iran. To develop the ensemble model, members of the ensemble system were created by combining three selected configurations and introducing perturbations in the model's initial conditions using a Monte Carlo method. Additionally, in the WRF model simulations for each ensemble member, three nested domains with horizontal resolutions of 27, 9, and 3 kilometers were utilized. The results were analyzed using statistical metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Kling-Gupta Efficiency (KGE) in comparison with observational data from existing stations in the region. For 72-hour predictions of wind components at a height of 10 meters above ground level, the RMSE was found to be 2.31 meters per second, while for 2-meter air temperature, it was 2.75 degrees Celsius. These results indicate that the ensemble mean is effective for predicting these variables given the region's topographical conditions. The model's performance in predicting precipitation was evaluated using four statistical metrics for events exceeding two categories. The False Alarm Ratio (FAR) indicated that there were many false alarms for precipitation amounts between 1 and 10 millimeters, while the Heidke Skill Score (HSS) demonstrated high skill relative to random forecasts in this range. Furthermore, the model showed good capability in identifying actual precipitation events and performed well for rainfall amounts exceeding 50 millimeters; however, slight over-predictions were noted in other cases. The model faced its greatest challenges in predicting variables within the mountainous areas of the region during forecast days.
Keywords
Numerical weather prediction
ensemble system
WRF model
perturbation

Subjects

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Iranian Journal of Geophysics
Volume 19, Issue 5
November and December 2025
Pages 141-155