Evaluation of change factor methods in downscaling extreme precipitation over India

Flood is one of the most prevalent natural disasters, and extreme precipitation events are the principal cause of most flooding. Understanding climate change impacts on extreme precipitation is vital for sustainable infrastructure development and water resources management. There are different methods to downscale precipitation to local scale from the Global Climate Models' simulations available at coarse resolution. The change factor (CF) method is one of those widely used methods for downscaling extreme precipitation. However, there are many variations in the CF method, and no study is available reporting the best CF method for downscaling extreme precipitation until today. Consequently, this study aims to evaluate different variants of four change factor methods, namely Additive Constant Scaling (ACS), Additive Daily Scaling (ADS), Multiplicative Constant Scaling (MCS) and Multiplicative Daily Scaling (MDS), for simulating extreme precipitation over India. Further, the optimum size of the baseline period for all four change factor methods and the optimum number of change factors for the daily scaling method are also evaluated. A total of 80 variants of four change factor methods, namely ACS, ADS, MCS and MDS, are formulated by varying the size of the baseline period and the number of change factors in the daily scaling method. Change factor methods are evaluated in terms of their capability in downscaling the Annual Maximum (AM) precipitation series and four extreme precipitation series extracted with Peaks Over Threshold (POT) method. The results indicate that the daily scaling methods (ADS and MDS) are the best change factor method for more than 75% (3713 out of 4948) of IMD grids for downscaling extreme precipitation. It is also observed that the variants of the daily scaling method having 100 change factors are alone the best change factor method for 35% (1708 out of 4948) of IMD grids for downscaling extreme precipitation. However, change factor methods having a smaller number of change factors (including constant scaling variants) are consistent compared to the variants of the daily scaling method having 100 change factors.

Automated summary

Understanding the impact of climate change on extreme precipitation is crucial for sustainable infrastructure development and water resources management. The daily scaling method proves to be the best change factor method for downscaling extreme precipitation, particularly the variants with 100 change factors.