Assessment of numerical model predictions of a severe weather in northern Iran: a case study

Abstract

The capability of numerical models in simulating severe weather is related to the setting up of the parameters in the model, and the dynamical and physical schemes implemented in the model. Every model is not able to make accurate predictions in different time and locations. The Advanced Regional Prediction System (ARPS) was used with three different horizontal resolutions (30, 10, and 4 km) to simulate a severe snow storm in the south of the Caspian Sea, focusing primarily on the Tehran metropolitan area. This extratropical cyclone is selected due to its heavy precipitation (up to 3 m of snow in some regions) and a significant damage in terms of human and financial losses, as well as the variety forms of precipitation during its activity, including snow, rain, and hail. The ARPS model is used because the current operational numerical model, the Weather Research and Forecasting (WRF), at the national forecasting center of Iran does not predict well such an extreme event, particularly on the east coast of the Caspian Sea. Quantitatively speaking, our large-scale analyses show that there is a low bias in the simulated surface pressure, although the pressure patterns have generally admissible similarity with the observations. Geopotential height at 500 hPa is in reasonable agreement with the GFS reanalysis (here after observations). In terms of precipitation, the maximum values are simulated to be on the coasts of the Caspian Sea. In the innermost domain with 4-km horizontal resolution, precipitation values have been compared against the observations. The accumulative precipitation values in most of the weather stations are more than the actual values. Simulation results also indicate that in Mehrabad airport (center of Tehran) the model has successfully predicted vertical profiles of the considered variables.