EAPSI: Identifying Dominant Atmospheric Circulation Patterns Leading to Extreme Precipitation in Mid-Latitudes

Farnham David J, New York NY

Investigators

Abstract

This award supports research to investigate the statistical predictability of extreme precipitation in mid-latitude locations. Atmospheric circulations that enhance the chance of extreme precipitation in mid-latitude locations (e.g. regions of the United States of America) will be statistically summarized and used to advance flood prediction techniques. The work has the potential to improve the accuracy of flood risk assessments and projections, as well as the ability of modelers to forecast mid-latitude extreme precipitation events up to a week in advance. Such improvements could allow for improved decision-making in infrastructure planning and early warning systems in flood prone areas. The project will be conducted in collaboration with Dr. Hyun-Han Kwon at the Risk Prevention Center and the Department of Civil Engineering at Chonbuk National University in South Korea. Dr. Kwon is an expert in hydrological modeling at large spatial scales. The work will apply nonlinear dimensional reduction techniques to characterize and classify spatio-temporal structures of the underlying atmospheric variables (e.g. pressure, temperature, and humidity) leading to mid-latitude extreme precipitation. This work aims to provide a benchmark for studies of extreme rainfall mechanisms that can benefit both statistical and dynamical modeling initiatives that seek to 1) forecast extreme precipitation on the daily to weekly timescales, and 2) assess the underlying risk of flooding in a specific region. This project will focus on tropical moisture transports to specific mid-latitude locations (the Northeast US and central Korea), while also pursuing a generalizable product for linking statistical models to atmospheric circulations. Moreover, establishing the conditional dependence of extreme precipitation on atmospheric conditions will allow for more meaningful extrapolation of future risks in a changing climate. This research is funded jointly by NSF and the National Research Foundation of Korea.