Attributing weather patterns to Davao River extreme rainfall from Reanalysis and GCM

Abstract

Extreme rainfall or heavy rainfall events (HREs) causes significant socio-economic damages annually affecting local development especially in developing countries. Thus, assessing changes in frequency and magnitude of HREs under climate change using global climate model (GCM) projections became ubiquitous to hydrological impact studies. Here, we present a framework for evaluating GCM's ability in reproducing the seasonal frequency of HREs in Davao River basin and the associated weather patterns that led to HREs. Our results show that HREs in MRI-AGCM 3.2S occurred 81 % in DJF and 4 % in JJA, which showed over(under) estimation bias during DJF(JJA) season compared to ERA5 HREs that show occurrence of 50 % in DJF and 18 % in JJA. Furthermore, we examined the weather pattern and anomalies that led to anomalous conditions of the season specific HREs in Davao River basin, which showed MRI-AGCM3.2S was able to reproduce the general structure of anomalous conditions fairly well on both seasons in comparison with ERA5. However, the slight over(under)estimation of the surface anomalous conditions in DJF(JJA) are directly proportional to the over(under)estimation in rainfall magnitude in the basin.