"A Large-Scale Investigation of Soil Moisture Feedbacks on Precipitation Intensity in the Central United States"
Land-atmosphere interactions are widely studied, especially in the context of thunderstorms. Soil moisture has been shown to play a role in convective processes, with a wide body of literature regarding influences on the spatial distribution of resulting convective precipitation. Considerably less is known about impacts on intensity. We adopt a framework from studies on urban modification of convection to investigate various relationships between surface, atmosphere, and storm characteristics. The Thunderstorm Observation by Radar (ThOR) algorithm takes a Lagrangian approach to acquiring a full data record of thunderstorms over the Central United States. Using the European Centre for Medium-Range Weather Forecasts’ Reanalysis v5 Land data (ERA5-Land), we can assign surface variable values to each storm track after proper filtering. Pearson’s correlation tests are run on several variables, and the spatial distribution is investigated. Although the results are still preliminary, we found that there is generally no direct or strong correlation between soil moisture and precipitation. However, there is an indirect chain of influences that connects soil moisture trends with precipitation intensity. From this, we can discern that higher soil moisture decreases the boundary layer height of storm environments, which in turn lowers precipitation intensity. This pattern is present domain-wide but falls victim to smaller sample sizes in the northern half of the domain.
