Quantifying the Effects of Surface Thermal Heterogeneity on Dispersive Fluxes in an Idealized Environment

In the planetary boundary layer, diurnal variations in solar heating spawnturbulent mixing that modifies the distribution of state variables. The turbulence contribution to state variable redistribution can be quantified by including a turbulence term in the governing equations. The complexity in airflow dynamics caused by turbulence is further increased by the presence of surface heterogeneities. Spatial heterogeneities of albedo, temperature, moisture and roughness contribute to variability in surface fluxes. The combined effects of these heterogeneities further increase the difficulty in determining the individual effects. The Idealized Planar-Array for Quantifying Surface Heterogeneity (IPAQS) project was conducted during summers 2018 and 2019 in the Great Salt Lake Desert Playa at the Dugway Proving Ground’s Surface Layer Turbulence and Environmental Test location. Complexity was reduced by choosing a site that was flat and nonvegetated, with limited moisture availability. Heterogeneity was expressed by small-scale differences in albedo, which cause surface temperature differences following solar heating. A 5-km distributed temperature sensing (DTS) system was used to measure surface temperatures at a spatial resolution of 12.5 cm and a temporal resolution of roughly 3 s. A spatial array of ultrasonic anemometers placed in a 200 × 200 m grid pattern measured air temperature and wind speed that were used to calculate turbulent fluxes. The spatial mean (SMEAN) of surface temperature reached maximum values of roughly 40 °C in the early afternoon. The air temperature SMEAN occurred roughly two hours later with maximum values of roughly 35 °C. Surface temperature spatial variation as measured by the surface temperature spatial standard deviation (SSTD) reached maximum daily values in the early afternoon. Air temperature SSTD did not change significantly during the day. The SMEAN of wind speed was generally below 4 m s-1 during the convective period on sunny days. A decorrelation length scale was calculated by finding the minimum distance at which the autocorrelation value dropped below 0.1. The decorrelation length scale increased in the late morning and peaked in the early afternoon, with a value of roughly 35 m on sunny days. These variables were combined to create a heterogeneity parameter which represents the impact of surface thermal heterogeneity on surface layer fluxes. Dispersive fluxes were found to increase slightly with increasing heterogeneity parameter values during convective periods. Both surface temperature variation and the vertical temperature gradient decreased with increasing wind speed during convective periods. These results quantitatively illustrate the complex interaction between surface thermal heterogeneities and wind. Surface temperature variations drive air flow in low wind conditions, while stronger winds decrease the intensity of thermal heterogeneities