RII Track-4:NSF: Improving subseasonal-to-seasonal forecasts of Central Pacific extreme hydrometeorological events and their impacts in Hawaii

This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows project will provide a fellowship to an Assistant professor and training for a graduate student at the University of Hawaii. This work will be conducted in collaboration with researchers at the Center for Western Weather and Water Extremes at the Scripps Institution of Oceanography at the University of California San Diego. Forecasting extreme weather events is essential for safety, preparedness, and infrastructure planning, especially in regions like Hawaiʻi, where the unique geography poses significant challenges. Hawaiʻi’s isolated location increases the importance of early and accurate forecasts to facilitate timely emergency response. This project aims to strengthen the science of forecasting such events in Hawaiʻi by understanding the region’s specific climate complexities. By improving our forecasting capabilities, this endeavor will not only advance scientific research but will also contribute significantly to the well-being and safety of Hawaiʻi’s residents, especially socioeconomically disadvantaged communities that often bear the brunt of extreme weather events. This fellowship will support training opportunities for the PI in subseasonal-to-seasonal (S2S) weather forecasting by supporting the establishment of a long-term collaboration with the Center for Western Weather and Water Extremes. The primary objectives of this project are to deepen the understanding of intraseasonal climate variability in the Central Pacific and to develop a subseasonal-to-seasonal (S2S) forecast system for extreme hydrometeorological events ranging from 2 weeks to 6 months. During the fellowship, this collaboration aims to clarify the impact of the Madden-Julian Oscillation on Hawaiʻi’s hydroclimate using observational and reanalysis data, and to evaluate the accuracy of S2S forecasts in the Central Pacific using a variety of metrics. In addition, an S2S forecast system for Hawaiʻi will be created by downscaling real-time ensemble forecasts. This system could be used by forecasters and other stakeholders to support emergency planning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.