Exploring the sensitivity of precipitation behavior using a single-column model

Relationships between land-surface conditions, boundary layer (PBL) growth, atmospheric stability, and convective precipitation behavior are explored using the Weather Research and Forecasting Model (ARW WRF) in single column model (SCM) mode. SCMs are computationally inexpensive, which enables the exploration of a wide range of parameter space. This study aims to determine the effects of land properties and atmospheric stability on convective precipitation behavior, specifically addressing precipitation event frequency and magnitude, and bridge the gap between computation- ally expensive three-dimensional models and low-order bulk models. This study focuses on the effects of soil moisture and large-scale synoptic forcing on surface fluxes, PBL structure and evolution, and precipitation behavior for different vegetation fractions. Soil moisture conditions become less influential on precipitation behavior with increasing vegetation cover, and large-scale vertical motion becomes more important with increasing subsidence as events become more intense but less frequent. Changes to the low-level inversion weakly affects event frequency while free-tropospheric stability substantially influences total precipitation. Thermodynamic mixing diagrams capture the multi-day dynamics and preferential regions of thermodynamic parameter space where sharp boundaries are delineated. Results indicate that idealized SCMs are able to capture some aspects of land-atmosphere interactions (PBL response to soil moisture, precipitation event magnitude) but not others (precipitation frequency), suggesting the simplifying assumptions pertaining to synoptic forcing may not be justified in all cases