Turbulence and land-atmosphere interactions over Eastern Snake River Plain, Idaho
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Abstract
Turbulence in the atmospheric boundary layer (ABL) influences land-atmosphere interactions and affects weather and climate by shaping surface-atmosphere exchanges of heat, moisture, and momentum. However, accurately characterizing and modeling boundary-layer turbulence remains challenging, particularly over complex terrain. To address these challenges, this dissertation examines turbulence structure in the ABL and diurnal-scale boundary-layer evolution, using observational analysis, mesoscale simulations, and large-eddy simulations (LES) over the Eastern Snake River Plain (ESRP), Idaho. The first chapter investigates the asymptotic coefficients of the attached-eddy Model (AEM) in the limit of high Reynolds numbers, as derived from the adiabatic atmospheric surface layer (ASL). A 210-day dataset from the 62-m GRID3 meteorological tower in ESRP is used to examine the logarithmic behavior of streamwise velocity variance and the −1 scaling in streamwise velocity energy spectra. The results indicate that the Townsend-Perry coefficient (A₁) exhibits Reynolds number dependence due to mild non-stationarity but asymptotically converges to values between 1.0 and 1.25 at sufficiently high Reynolds numbers, consistent with laboratory experiments. These findings refine the understanding of boundary-layer turbulence scaling and confirm the similarity between ASL and the inertial subrange of canonical wall-bounded turbulent flows in laboratory settings. The second chapter evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating the diurnal slope flow system over ESRP. Using observations from the GRID3 tower and the NOAA/INL Mesonet network, the study assesses WRF’s ability to capture morning wind transition and temperature evolution. While the model reproduces key aspects of the diurnal cycle, it exhibits a persistent nighttime warm bias and an early wind transition. Sensitivity tests reveal that land surface models (LSMs) and forcing datasets primarily influence these biases, whereas planetary boundary layer (PBL) schemes and horizontal resolution have a smaller influence. These results emphasize the need for improved parameterization of land-atmosphere interactions in numerical weather prediction over complex terrain. The final chapter investigates the persistent nighttime warm bias in WRF simulations and assesses whether LES can improve temperature predictions at night. LES runs at 125 m and 25 m resolutions demonstrate that including the Nonlinear Backscatter and Anisotropy (NBA) scheme enhances dynamical cooling, shifting the dominant cooling mechanism from radiative to diffusive processes. This study underscores the importance of turbulence parameterization in stable boundary layers and highlights the compensating effects of different processes in governing nighttime temperature evolution. This dissertation contributes to improving fundamental understanding of turbulence in the ABL and its role in numerical models, with applications in weather forecasting, climate modeling, and environmental monitoring over complex terrain.
Description
2025
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Attribution 4.0 International