Soil moisture links hydrologic and atmospheric processes and impacts important properties of the atmospheric boundary layer via turbulent land-atmosphere exchange. Research on land-atmosphere interactions and their impacts on the simulated boundary layer in semi-arid regions with substantial irrigation is relatively sparse. We use the Weather Research and Forecasting (WRF) model to evaluate the influence different land surface models (LSMs) and planetary boundary layer (PBL) schemes have on the performance of simulations through comparisons with multi-scale observations during a fifteen-day summertime period during 2016. The focus region for this study is the Central Valley (CV), California, which receives little to no rain in the summer and relies on widespread irrigation for agriculture. Results demonstrate that the LSM drives the differences between simulations, showing only minor variations with changing the PBL scheme. Simulations using the RUC (Rapid Update Cycle) and PX-NO (Pleim-Xu without soil moisture and soil temperature nudging) LSMs generated better comparisons with observed PBL depths. Contrasting RUC however, PX-NO better simulates surface fluxes and humidity, whereas Noah (Noah Unified) and Noah-MP (Noah Multiparameterization) simulate better temperatures despite relatively poor surface flux performance. For most quantities, indirect soil nudging in PX (Pleim-Xu) did not improve results compared to PX-NO, which may be related to soil moisture initialization, the nudging dataset, or a need for model improvements in arid regions. Despite these variations in performance statistics across simulations and quantities, we show that potential evapotranspiration (ETo) has robust performance statistics across simulations. This suggests that ETo depends more strongly on net radiation, which performs relatively well across simulations, than on wind, temperature, and humidity, and indicates a further disconnect between ETo and latent heat fluxes in WRF simulations. Finally, we suggest strategies to obtain the necessary observations to better understand the multi-scale dynamics in the CV and drive subsequent model development.

Daytime atmospheric boundary layer (ABL) dynamics—including potential temperature budgets, water vapour budgets, and entrainment rates—are presented from in situ flight data taken on six afternoons near Fresno in the San Joaquin Valley (SJV) of California during July/August 2016. The flights took place as a part of the California Baseline Ozone Transport Study aimed at investigating transport pathways of air entering the Central Valley from offshore and mixing down to the surface. Midday entrainment velocity estimates ranged from 0.8 to 5.4 cm s−1 and were derived from a combination of continuously determined ABL heights during each flight and model-derived subsidence rates, which averaged -2.0 cm s−1 in the flight region. A strong correlation was found between entrainment velocity (normalized by the convective velocity scale) and an inverse bulk ABL Richardson number, suggesting that wind shear at the ABL top plays a significant role in driving entrainment. Similarly, we found a strong correlation between the entrainment efficiency (the ratio of entrainment to surface heat fluxes with an average of 0.23 ± 0.15) and the wind speed at the ABL top. We explore the synoptic conditions that generate higher winds near the ABL top and propose that warm anomalies in the southern Sierra Nevada mountains promote increased entrainment. Additionally, a method is outlined to estimate turbulence kinetic energy, convective velocity scale (w*), and the surface sensible heat flux in the ABL from a slow, airborne wind measurement system using mixed-layer similarity theory.