Abstract

The spatiotemporal distribution of Land Surface Temperature (LST) is linked to the partitioning of the coupled surface water and energy budgets. In watersheds with a strong seasonality in precipitation and vegetation cover, the temporal evolution of LST patterns are a signature of the interaction... Show moreThe spatiotemporal distribution of Land Surface Temperature (LST) is linked to the partitioning of the coupled surface water and energy budgets. In watersheds with a strong seasonality in precipitation and vegetation cover, the temporal evolution of LST patterns are a signature of the interactions between the land surface and atmosphere. Nevertheless, few studies have sought to understand the topographical and ecohydrological controls on LST in regions of complex terrain. Numerical watershed models, tested against spatially distributed field and remote sensing data, can aid in linking the seasonal evolution of LST to meteorology, terrain, soil, and vegetation. In this study, we use a distributed hydrologic model to explore LST patterns in a semiarid mountain basin during the transition from a dry spring to the wetter North American monsoon (NAM). By accounting for vegetation greening through remotely sensed parameters, the model reproduces LST and surface soil moisture observations derived from ground, aircraft, and satellite platforms with good accuracy at individual sites and as spatial basin patterns. Distributed simulations reveal how LST varies with elevation, slope, and aspect and the role played by the seasonal vegetation canopy in cooling the land surface and increasing the spatial variability in LST. As a result, LST is shown to track well with ecosystem-specific changes in vegetation cover, evapotranspiration, and soil moisture during the NAM. Furthermore, vegetation greening is shown to modulate the spatial heterogeneity of LST during the NAM that should be considered in subsequent atmospheric studies in regions of complex terrain. Show less