Influence of land surface models on predictions of the vertical structure of stable boundary layers in AT&D applications
Penn State University has been investigating the predictability and behavior of SBLs in the ridge and valley region of central Pennsylvania under DTRA-funded contracts. The tools we have been using include (1) an automated array of sonic anemometers and temperature sensors in the Rock Springs area of Nittany Valley, and (2) daily high-resolution (to 444-m horizontal grid spacing and near-surface 2-m vertical grid spacing) simulations using the Weather Research and Forecasting (WRF) numerical model, Advanced Research WRF (ARW). WRF-ARW is designed to simulate a range of physical processes in the atmosphere but also requires specification of heat and moisture fluxes at the ground. Initial WRF-ARW predictions show promising results for at least some aspects of SBL near-surface meandering flows at resolvable horizontal and temporal scales. However, for modeled SBLs to be useful for AT&D applications, their vertical structure must also be validated, from the fluxes at the ground to the temperature and wind fields at and above the SBL top.
In this study we compare predicted WRF-ARW vertical structure to local 2-D and 3-D sonic anemometer and temperature sensor data between 2 m and 47 m AGL. Recently acquired mini-sodars will allow us to extend studies of atmospheric structure from a few tens to a few hundred meters above the surface.
To better model the heat and moisture fluxes at the land-atmosphere boundary, we also investigate the use of the Noah land surface model (LSM). Previous WRF investigations by Penn State had used a thermal diffusion scheme to predict soil temperature while keeping soil moisture constant at climatological values. The Noah LSM predicts both soil moisture and temperature and accounts for moisture fluxes from soil, vegetation, and snow. The use of this more detailed scheme, in concert with case-specific soil moisture values based on antecedent conditions, should allow for a better representation of surface heat and moisture fluxes and thus a more accurate simulation of the SBL. However, obtaining sufficiently accurate initial conditions for the additional fields used by Noah (e.g., soil moisture) may be particularly difficult at the scales modeled here (i.e., 444-m). Finally, we demonstrate the effects of using the Noah LSM on SBL predictions of temperature and winds, and the corresponding influence on dispersion calculations using trajectories and the SCIPUFF AT&D model.