ARL Weekly News – July 2, 2021
Accepted: Temple Lee, Michael Buban and Tilden P. Myers: Application of Bulk Richardson Parameterizations of Surface Fluxes to Heterogeneous Land Surfaces was accepted at Monthly Weather Review. In the paper, the authors demonstrated that using a bulk Richardson approach yielded predictions of friction velocity, sensible heat flux, and latent heat flux that were just as good as, and in some instances better, than predictions of these quantities obtained when using long-standing similarity relationships derived from Monin-Obukhov Similarity Theory. The results presented in this paper result motivate us to consider implementing the bulk Richardson approach into numerical weather prediction models, as doing so is expected to improve surface-layer parameterization schemes used within these models.
Published: Temple Lee and Sandip Pal: The Impact of Height-Independent Errors in State Variables on the Determination of the Daytime Atmospheric Boundary Layer Depth Using the Bulk Richardson Approach. J. Atmos. Ocean. Tech., 38, 47–61, doi.org/10.1175/JTECH-D-20-0135.1, 2021.
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 (δBLD) estimates is equally as important as the BLDs themselves. Here we quantified δBLD 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 δBLD ranging from −15 to 200 m. A +2°C bias in temperature yielded a mean δBLD ranging from −214 to +18 m. For a −5% relative humidity bias, the mean δBLD ranged from −302 to +7 m. For a +5% relative humidity bias, the mean δBLD ranged from +2 to +249 m. Differences of ±2 m s−1 in the winds yielded BLD errors of ~±300 m. The δBLD 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 δBLD by quantifying δBLD arising from rawinsonde-derived thermodynamic and kinematic measurements. Knowledge of δBLD is critical in, for example, intercomparison studies where rawinsonde-derived BLDs are used as references.