A Satellite-Based Model for Estimating Latent Heat Flux from Urban Vegetation

Abstract:

Cities make up a small fraction of global land area but have a disproportionately large influence on human quality of life and well-being. Urbanization modifies local climates with important implications for ecosystems and the public health of residents. The urban heat island (UHI) effect is perhaps the most well-studied urban climate phenomenon and can exacerbate the health impacts of extreme heat events. The UHI is primarily driven by disruptions to the surface energy balance via increases in impervious surface area (ISA), less vegetation, less moisture availability, and therefore less latent heat flux (λE). Here, we present a spatially explicit, remote sensing driven model to produce hourly estimates of urban λE from vegetation at 30m spatial resolution. The model iterates through three core equations that consider unique urban climatological and physiological characteristics, such as lower albedo due to the presence of buildings and urban canyons, persistent stomatal conductance at warmer temperatures, and higher vapor pressure deficits (VPD) driven by increased ISA. Surface conductance of water vapor is estimated as a function of photosynthesis and VPD using the Urban Vegetation Photosynthesis and Respiration Model and Medlyn stomatal conductance model. The Penman-Monteith model is used to produce estimates of λE, with meteorological inputs downscaled to 30m resolution based on empirical relationships between ISA and temperature/VPD. We find strong agreement between field observations and model estimates of λE across a range of ecosystem types, including cities. Cities are most susceptible to the threat of future increases in heat wave intensity but are also at the forefront in developing climate mitigation strategies. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetative cooling potential across cities and identify vulnerable populations at adequate resolution to inform policies combatting the effects of extreme heat events.