The performance of different parametrization on RegCM

This study investigates the accuracy and reliability of climate predictions utilizing the RegCM 4.7.0 regional climate model, focusing on two distinct topographies in Türkiye. The primary objective is to identify which physical parameters enhance the model's ability to simulate climate scenarios and to assess how varying resolutions impact computational efficiency without compromising accuracy. This study employs precipitation and temperature data for dynamic downscaling, analyzing high and low topographic areas at 25 km, 10 km, and 5 km resolutions. Appropriate parameters, such as Planetary Boundary Layer and Convective Precipitation Schemes, are selected. The results are then compared with CRU and NCAR reanalysis data, which are interpolated to match the model's resolution. The findings reveal that temperature bias values are more accurate than precipitation values, and the same physical parameters yield better results in high topographic areas. An increase in resolution corresponds to an increase in bias values. Spatial correlation values for temperature decrease as resolution increases, showing better results in higher topography. For precipitation, the best outcomes are observed at an altitude of 10 km, with no specific pattern for low topography areas. In conclusion, the study demonstrates that high topographic areas exhibit moderate correlations, while low topographic areas show little to no correlation. The research suggests that a 25 km resolution is the most efficient for RegCM 4.7.0, as higher resolutions may lead to minor deviations due to interpolation​​.