Investigating Soil Moisture-Precipitation Relationships During Recent Flooding Events Using WRF Simulations and NOAA Operational Modeling Products

Extreme precipitation and floods are among the most common and impactful disasters in the United States and other parts of the world, and their sizes and frequencies are known to have connections with climate change. Accurately forecasting the timing and intensity of extreme precipitation and floods is important for reducing the damages caused by these exceptional events, and this can benefit from a better understanding of the relationships between soil moisture (SM) and precipitation. Here, we conduct a number of regional-scale Weather Research and Forecasting (WRF) model simulations to study several recent flooding events in the United States (i.e., the August 2016 Louisiana flood, the May 2018 flood in Ellicott City, Maryland, and the midwestern floods in Spring/Summer 2019). NOAAs operational Global Forecast System (GFS) products serve as WRFs initial and boundary conditions. Based on the WRF and GFS model fields, the following specific questions are addressed: 1) How does the accuracy of predicted precipitation, along with other elements of water and energy balances, affect the accuracy of modeled SM changes and flood forecasts; 2) How does the antecedent SM (i.e., SM fields at the model initialization prior to the floods) impact the extreme precipitation prediction; and 3) How do model resolution, forecast lead time, and the inclusion of aerosol feedbacks affect the findings from 1) and 2)? The analysis of these events is also supported by a variety of observations collected on different platforms (e.g., SMAP and CYGNSS soil moisture, GPM precipitation, ACT-America and FIREX-AQ aircraft data, and ground-based measurements). The interconnections between floods, ecosystem productivity and fire regimes, as well as the implications of the impacts of flooding for urban planning, are also discussed.