This article investigates the effect of air conditioning (AC) systems on air temperature and examines their electricity consumption for a semiarid urban environment. We simulate a 10 day extreme heat period over the Phoenix metropolitan area (U.S.) with the Weather Research and Forecasting model coupled to a multilayer building energy scheme. The performance of the modeling system is evaluated against 10 Arizona Meteorological Network weather stations and one weather station maintained by the National Weather Service for air temperature, wind speed, and wind direction. We show that explicit representation of waste heat from air conditioning systems improved the 2 m air temperature correspondence to observations. Waste heat release from AC systems was maximum during the day, but the mean effect was negligible near the surface. However, during the night, heat emitted from AC systems increased the mean 2 m air temperature by more than 1°C for some urban locations. The AC systems modified the thermal stratification of the urban boundary layer, promoting vertical mixing during nighttime hours. The anthropogenic processes examined here (i.e., explicit representation of urban energy consumption processes due to AC systems) require incorporation in future meteorological and climate investigations to improve weather and climate predictability. Our results demonstrate that releasing waste heat into the ambient environment exacerbates the nocturnal urban heat island and increases cooling demands.

Large-scale cultivation of perennial bioenergy crops (e.g., miscanthus and switchgrass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. The hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States are quantified using the Weather Research and Forecasting Model dynamically coupled to a land surface model (LSM). A suite of continuous (2000-09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted using seasonally evolving biophysical representation of perennial bioenergy cropping systems within the LSM based on observational data. Deployment is carried out only over suitable abandoned and degraded farmlands to avoid competition with existing food cropping systems. Results show that near-surface cooling (locally, up to 5°C) is greatest during the growing season over portions of the central United States. For some regions, principal impacts are restricted to a reduction in near-surface temperature (e.g., eastern portions of the United States), whereas for other regions deployment leads to soil moisture reduction in excess of 0.15-0.2 m 3 m −3 during the simulated 10-yr period (e.g., western Great Plains). This reduction (~25%-30% of available soil moisture) manifests as a progressively decreasing trend over time. The large-scale focus of this research demonstrates the long-term hydroclimatic sustainability of large-scale deployment of perennial bioenergy crops across the continental United States, revealing potential hot spots of suitable deployment and regions to avoid. RightsWorks produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted. ABSTRACT Large-scale cultivation of perennial bioenergy crops (e.g., miscanthus and switchgrass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. The hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States are quantified using the Weather Research and Forecasting Model dynamically coupled to a land surface model (LSM). A suite of continuous (2000-09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted using seasonally evolving biophysical representation of perennial bioenergy cropping syst...