Future Changes in Midwest Extreme Precipitation: Mesoscale Convective Systems, Thunderstorms, Winter Storms, and Tropical Cyclone Remnants
Extreme precipitation in the Midwestern United States is associated with multiple storm types including thunderstorms, mesoscale convective systems (MCSs), tropical cyclone (TC) remnants, and winter storms. Anthropogenic warming is expected to increase climatological precipitation globally, however, there may be little correspondence with regional storm-based changes. Furthermore, there remains uncertainty in precipitation-temperature scaling due to use of convective parameterization in most global models. In this study, we investigated historically-impactful extreme precipitation events from multiple types of Midwest storms using the Weather Research and Forecasting model at convection-permitting resolution. We simulated five-member ensembles of historical hindcasts and experiments representing the storms in the future using the pseudo-global-warming method. We found that future precipitation changes depend on storm type, with increases near Clausius-Clapeyron (CC) for winter storms, no consensus for thunderstorms and MCSs, and sub-CC increases for TC remnants. This research highlights the importance of considering storm type in future extreme precipitation projections.
- Mercurio, T. J., & Patricola, C. M. (2025). Future Changes in Midwest Extreme Precipitation Depend on Storm Type. Geophysical Research Letters, 52 (5), e2024GL113126.
This research was supported by Iowa State University, College of Liberal Arts and Sciences and used resources of the Texas Advanced Computing Center (TACC) and the National Energy Research Scientific Computing Center (NERSC).
Future Changes in Extreme Precipitation over the San Francisco Bay Area: Atmospheric Rivers and Extratropical Cyclones
Extreme precipitation poses a major challenge for local governments, including the City and County of San Francisco, California, as flooding can damage and destroy infrastructure and property. As the climate continues to warm, reliable future precipitation projections are needed to provide the best possible information to decision makers. However, future changes in the magnitude of extreme precipitation are uncertain, as current state-of-the-art global climate models are typically run at relatively coarse horizontal resolutions that require the use of convective parameterization and have difficulty simulating observed extreme rainfall rates. Here, we performed ensembles of convection-permitting regional climate model simulations to investigate how five historically impactful extreme precipitation events over the San Francisco Bay Area could change if similar events occurred in future climates. We found that changes in storm-total precipitation depend strongly on storm type. Precipitation associated with an atmospheric river (AR) accompanied by an extratropical cyclone (ETC) is projected to increase at a rate exceeding (by up to 1.5 times) the theoretical Clausius Clapeyron scaling of 6–7% per C warming. On the other hand, future precipitation changes are weak or negative for events characterized by an AR only, despite increases in precipitable water and integrated vapor transport that are similar to those of the co-occurring AR and ETC events. The differences in the sign of future precipitation change between AR-only events and co-occurring AR and ETC events is instead linked with changes in mid-tropospheric vertical velocity. Given that the majority of observed ARs are associated with an ETC, this research has important implications for future precipitation impacts over the Bay Area, as it indicates that storm-total precipitation associated with the most common type of storm event may increase by up to 26–37% in 2100 relative to historical.
- Patricola, C. M., Wehner, M. F., Bercos-Hickey, E., Maciel, F. V., May, C., Mak, M., Yip, O., Roche, A., & Leal, S. (2022). Future Changes in Extreme Precipitation over the San Francisco Bay Area: Dependence on Atmospheric River and Extratropical Cyclone Events, Weather and Climate Extremes, 36, 100440.
This research was supported by the City and County of San Francisco (CCSF) and used resources of the National Energy Research Scientific Computing Center (NERSC) and the Texas Advanced Computing Center (TACC).
Maximizing ENSO as a Source of Western US Hydroclimate Predictability
Until recently, the El Niño–Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015–2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015–2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997–1998 and 1982–1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño’s spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO’s spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California’s seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events.
- Patricola, C. M., O’Brien, J. P., Risser, M. D., Rhoades, A. M., O’Brien, T. A., Ullrich, P. A., Stone, D. A., & Collins, W. D. (2020). Maximizing ENSO as a Source of Western US Hydroclimate Predictability. Climate Dynamics, 54(1), 351-372.
This research was supported by the U.S. Department of Energy Office of Science (BER, RGMA Program). High-performance computing resources provided by the National Energy Research Scientific Computing Center (NERSC).
updated 6/11/2025