Evaluation of the WRF Model Performance for Heavy Rainfall Simulation A Case Study of the Kan Basin in Iran

Document Type : Complete scientific research article

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Abstract

Background and objectives: Every year, heavy rainfalls cause flood events and huge losses to life and property over the flood prone catchments of Iran. Heavy rainfall forecasting is an important step in development of a flood warning system. In recent decades, the Numerical Weather Prediction (NWP) models were widely used for weather prediction. Several operational centers, including the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environmental Prediction (NCEP), the Japan Meteorological Agency (JMA), and the United Kingdom Meteorological Office (UKMO) offer valuable operational numerical predictions at a global scale. Regional models were developed to admit the need for comprehensive and high-impact weather forecasting with higher spatial resolution. Weather Research and Forecasting (WRF) model is extensively applied for regional rainfall forecasting. The WRF modeling system is data assimilation system and a mesoscale forecast. It is aimed to progressive atmospheric research and operational forecasting. In this paper, the performance of the WRF model is evaluated for heavy rainfall simulation in Kan Watershed, Tehran.
Materials and methods: Three domains were used in the implementation of WRF model. Horizontal resolution of domains are 27km, 9 km and 3 km respectively. The initial boundary which used to run the model has been downloaded from the National Centers for Environmental Prediction (NCEP) from Global Forecasting System (GFS). It is worth noting that the physics scheme of model was selected using the results of the previous research on the selection of the best physics for WRF model. The evaluation was conducted on the short-term forecasting. For this purpose, three heavy rainfall events occurred over the study area have been simulated using the WRF model. Precipitation forecasts were also downloaded from NCEP's Internet web site. Then, the heavy rainfall simulated by WRF model and presented by NCEP were compared to the observed rainfall.
Results: The results showed that rainfall amount has been underestimated by NCEP forecasts and the time of precipitation events has not been correctly predicted. It is also observed that the WRF model is able to capture the heavy rainfall events, So that the error indexes (RMSE and MAE) significantly reduced compared to global model.
Conclusion: The WRF model increased the accuracy of precipitation forecasting compared to the global model. Thus, it is recommended to use the WRF model coupled with a hydrological model to development a flood warning systems in in the flash flood-prone watersheds.
Keywords: Prediction, Heavy Rainfall, WRF, Kan Watershed.

Keywords

References

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Journal of Water and Soil Conservation
Volume 25, Issue 1
March and April 2018
Pages 229-242

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