Project Description:
Communities are grappling with the devastating consequences of extreme rainfall. From flooded homes and shattered infrastructure to lost livelihoods and widening social inequities, these events leave lasting scars. This project introduces a data-driven approach to address this challenge: BGNet. This advanced deep learning method aims to enhance the resolution of climate data and overcome the limitations of traditional models in predicting high-intensity rainfall events. By accurately modeling the statistical distribution of extremes, BGNet empowers communities and decision-makers with the information they need to implement targeted protective measures, improve disaster response, and build climate resilience, especially for the most vulnerable.
This project is carried out in collaboration with the National Insitute of Water and Atmospheric Research (NIWA).
Keywords: Climate Modelling, Extreme Rainfall, Resolution Upscaling
