Extreme Precipitation in the Great Lakes Region: Trend Estimation and Relation With Large-Scale Circulation and Humidity

Andrew Paxton,Trent W Ford,Jonathan W F Remo,Justin T Schoof

doi:10.3389/frwa.2021.782847

Abstract

Extreme precipitation contributes to widespread impacts in the U.S. Great Lakes region, ranging from agricultural losses to urban floods and associated infrastructure costs. Previous studies have reported historical increases in the frequency of extreme precipitation in the region and downscaled model projections indicate further changes as the climate system continues to warm. Here, we conduct trend analysis on the 5 km NOAA NClimDiv data for the U.S. Great Lakes region using both parametric (Ordinary Least Squares) and non-parametric methods (Theil-Sen/Mann-Kendall) and accounting for temporal autocorrelation and field significance to produce robust estimates of extreme precipitation frequency trends in the region. The approaches provide similar overall results and reflect an increase in extreme precipitation frequency in parts of the U.S. Great Lakes region. To relate the identified trends to large scale drivers, a bivariate self-organizing map (SOM) is constructed using standardized values of 500 hPa geo-potential height and 850 hPa specific humidity obtained from the ECMWF ERA-5 reanalysis. Using a Monte Carlo approach, we identify six SOM nodes that account for only 25.4% of all days, but 50.5% of extreme precipitation days. Composites of days with and without extreme precipitation for each node indicate that extreme events are associated with stronger features (height gradient and background humidity) than their non-extreme counterparts. The analysis also identifies a significant increase in the frequency of one SOM node often associated with extreme precipitation (accounting for 8.5% of all extreme precipitation days) and a significant increase in the frequency of extreme precipitation days relative to all days across the six extreme precipitation nodes collectively. Our results suggest that changes in atmospheric circulation and related moisture transport and convergence are major contributors to changes in extreme precipitation in the U.S. Great Lakes region.

Highlights

Extreme precipitation is associated with wide-reaching impacts in the Great Lakes region of the United States, including direct effects on localized and large-scale flooding (Winters et al, 2015), transportation and infrastructure (Angel et al, 2018) and agriculture, and many indirect effects, such as heightened risk of gastrointestinal illness (Drayna et al, 2010), impacts on disease vectorExtreme Precipitation Great Lakes Region habitats, and overall water quality
While accounting for autocorrelation and field significance reduced the spatial extent of the identified trends, we identified the
The spatial structure of extreme precipitation frequency under Node 2 qualitatively matches the observed trend structure

Summary

Introduction

Extreme precipitation is associated with wide-reaching impacts in the Great Lakes region of the United States, including direct effects on localized and large-scale flooding (Winters et al, 2015), transportation and infrastructure (Angel et al, 2018) and agriculture, and many indirect effects, such as heightened risk of gastrointestinal illness (Drayna et al, 2010), impacts on disease vectorExtreme Precipitation Great Lakes Region habitats, and overall water quality. Extreme precipitation is associated with wide-reaching impacts in the Great Lakes region of the United States, including direct effects on localized and large-scale flooding (Winters et al, 2015), transportation and infrastructure (Angel et al, 2018) and agriculture, and many indirect effects, such as heightened risk of gastrointestinal illness (Drayna et al, 2010), impacts on disease vector. Regional studies conducted with multiple generations of climate models, statistical and dynamical downscaling approaches, and mid- and late-century time horizons have pointed to more frequent and intense precipitation events in the region under additional global and regional warming (Pryor et al, 2013; D’orgeville et al, 2014; Byun and Hamlet, 2018; Zhang et al, 2019)

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