Numerical simulation and analysis of the April 2013 Chicago Floods

- The 2013 Chicago Spring Floods is a golden case for advancing weather prediction.
- We describe the event from a meteorological perspective based on observational data.
- We simulated the record rainfall event using the WRF model at high resolutions.

SummaryThe weather event associated to record Chicago floods on April 2013 is investigated by using the Weather Research and Forecasting (WRF) model. Observations at Argonne National Laboratory and multi-sensor (weather radar and rain gauge) precipitation data from the National Weather Service were employed to evaluate the model's performance. The WRF model captured the synoptic-scale atmospheric features well, but the simulated 24-h accumulated precipitation and short-period temporal evolution of precipitation over the heavy-rain region were less successful. To investigate the potential reasons for the model bias, four supplementary sensitivity experiments using various microphysics schemes and cumulus parameterizations were designed. Of the five tested parameterizations, the WRF Single-Moment 6-class (WSM6) graupel scheme and Kain-Fritsch (KF) cumulus parameterization outperformed the others, such as Grell-Dévényi (GD) cumulus parameterization, which underestimated the precipitation by 30-50% on a regional-average scale. Morrison microphysics and KF outperformed the others for the spatial patterns of 24-h accumulated precipitation. The spatial correlation between observation and Morrison-KF was 0.45, higher than those for other simulations. All of the simulations underestimated the precipitation over northeastern Illinois (especially at Argonne) during 0400-0800 UTC 18 April because of weak ascending motion or small moisture. All of the simulations except WSM6-GD also underestimated the precipitation during 1200-1600 UTC 18 April because of weak southerly flow.