Long-term variations in the frequencies of different rainfall events during summer monsoon season (June through September) are analysed over a period of 38-years (1980–2017) using the simulations of Weather Research and Forecasting (WRF) model evaluated against the India Meteorological Department (IMD). Further, we have divided the study period into two sub-periods such as before (1980–1998), and after the mega ENSO event (1999–2017). Our analysis suggests the WRF exhibits good skill in capturing the increased trends in the frequency of heavy and very heavy (extreme) rainfall events during the recent epoch (1999–2017).We have assessed the skill of WRF in capturing the observed probability distributions of daily rain rates over different sub-regions of India. Our results depict that the downscaled products of WRF captured well the extreme rainfall as observed in IMD, signifying that this dynamically downscaled model with continuous 36-hours re-initialization makes it suitable to simulate extreme rainfall events compared to light rainfall event. However, our analysis reports that there is a slight overestimation in WRF rainfall and fails in capturing the light rainfall events compared to IMD. The overestimation of rainfall by WRF possibly be due to increased pressure gradients and enhances the convection in the upper streams and associated rainfall. Our study emphasizes that the variability in summer monsoon rainfall during the recent period is due to the changes in the monsoon circulations, particularly monsoon low level jet (MLLJ) which leads to alter the moisture budget in terms of moisture convergence and transport. Moreover, the variability in frequencies of rainfall events are analysed for strong La Niña /El Niño years and observed an increase in extremes over major part of India during strong La Niña except over parts of Central India and NEI where strong El Niño dominates; which is well captured by the WRF model.
Bibliographical noteKAUST Repository Item: Exported on 2021-08-05
ASJC Scopus subject areas
- Atmospheric Science