Large Scale Meteorological Patterns Associated with Sub-Daily Extreme Precipitation in Illinois

High intensity, short duration precipitation events present significant economic challenges to both agricultural and urban regions in IL and can lead to the loss of property and human life. Because extreme precipitation events are expected to become more frequent and more intense as the climate warms, it is vital to understand the regional mechanisms that drive sub-daily extreme precipitation. The primary aim of this study is to identify the sub-daily large scale meteorological patterns (LSMP) associated with extreme precipitation in Illinois in ECWMF ERA-5 reanalysis data. To establish the range of 6-hour synoptic-scale circulation and humidity patterns in ERA-5, a bivariate self-organizing map (SOM) is constructed using standardized values of 500 hPa geopotential height and 850 hPa specific humidity. A Monte Carlo approach is then used to identify patterns likely to coincide with short-duration extreme precipitation in Illinois. These LSMPs are investigated to find the conditions that make the atmospheric patterns conducive to extreme precipitation, such as likelihood for moisture transport and convergence. Node transitions are also analyzed to capture the evolution of sub-daily extreme precipitation events. With a better understanding of the physical drivers of sub-daily extreme precipitation in this region, future work will focus on exploring the representation of those drivers in contemporary climate models. Studies have shown that global climate models may not fully capture the timing and amplitude of the diurnal cycle of precipitation, especially at the regional level. Quantifying the LSMPs and their transitions, as they relate to extreme precipitation, will provide additional information that can be used for climate model evaluation.