The Impact of Height-Independent Errors in State Variables on the Determination of the Daytime Atmospheric Boundary Layer Depth Using the Bulk Richardson Approach

Abstract

Abstract Rawinsonde observations have long been used to estimate the atmospheric boundary layer depth (BLD), which is an important parameter for monitoring air quality, dispersion studies, weather forecast models, and inversion systems for estimating regional surface–atmosphere fluxes of tracers. Although many approaches exist for deriving the BLDs from rawinsonde observations, the bulk Richardson approach has been found to be most appropriate. However, the impact of errors in the measured thermodynamic and kinematic fields on the estimated BLDs remains unexplored. We argue that quantifying BLD error ( δ BLD) estimates is equally as important as the BLDs themselves. Here we quantified δ BLD by applying the bulk Richardson method to 35 years of rawinsonde data obtained from three stations in the United States: Sterling, Virginia; Amarillo, Texas; and Salt Lake City, Utah. Results revealed similar features in terms of their respective errors. A −2°C bias in temperature yielded a mean δ BLD ranging from −15 to 200 m. A +2°C bias in temperature yielded a mean δ BLD ranging from −214 to +18 m. For a −5% relative humidity bias, the mean δ BLD ranged from −302 to +7 m. For a +5% relative humidity bias, the mean δ BLD ranged from +2 to +249 m. Differences of ±2 m s −1 in the winds yielded BLD errors of ~±300 m. The δ BLD increased as a function of BLD when introducing errors to the thermodynamic fields and decreased as a function of BLD when introducing errors to the kinematic fields. These findings expand upon previous work evaluating rawinsonde-derived δ BLD by quantifying δ BLD arising from rawinsonde-derived thermodynamic and kinematic measurements. Knowledge of δ BLD is critical in, for example, intercomparison studies where rawinsonde-derived BLDs are used as references.

Topics & Concepts