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David J. Sailor

Abstract

Three-dimensional meteorological simulations have been conducted to investigate the potential impact of urban surface characteristic modifications on local climate. Results for a base case simulation for the Los Angeles basin are compared to results from cases in which urban albedo or vegetative cover are increased. The methodology for determining the distribution and magnitude of these simulated surface modifications is presented. Increasing albedo over downtown Los Angeles by 0.14 and over the entire basin by an average of 0.08 decreased peak summertime temperatures by as much as 1.5°C. This level of albedo augmentation also lowered boundary layer heights by more than 50 m and reduced the magnitude and penetration of the sea breeze. A second simulation, in which vegetative cover was increased, showed qualitatively similar impacts. The results from these simulations indicate a potential to reduce urban energy demand and atmospheric pollution by 5%–10% through application of reasonable surface modification strategies.

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David J. Sailor and Xiangshang Li

Abstract

A statistical downscaling approach is developed for generating regional temperature change predictions from GCM results. The approach utilizes GCM free atmosphere output and surface observations in a framework conceptually similar to the model output statistics approach common in the forecasting community. The appropriateness of this approach is demonstrated through a comparison of GCM and observed free atmosphere variables. Seasonal downscaling models are presented for eight sites within four community climate model (CCM) grid cells in the United States. The majority of these models are capable of explaining more than 90% of the variance in the temperature time series. The results indicate a wide range of differences between downscaled climate change predictions and grid cell–level CCM predictions.

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Ashley M. Broadbent, E. Scott Krayenhoff, Matei Georgescu, and David J. Sailor

Abstract

Utility-scale solar power plants are a rapidly growing component of the renewable energy sector. While most agree that solar power can decrease greenhouse gas emissions, the effects of photovoltaic (PV) systems on surface energy exchanges and near-surface meteorology are not well understood. This study presents data from two eddy covariance observational towers, placed within and adjacent to a utility-scale PV array in southern Arizona. The observational period (October 2017–July 2018) includes the full range of annual temperature variation. Average daily maximum 1.5-m air temperature at the PV array was 1.3°C warmer than the reference (i.e., non-PV) site, whereas no significant difference in 1.5-m nocturnal air temperature was observed. PV modules captured the majority of solar radiation and were the primary energetically active surface during the day. Despite the removal of energy by electricity production, the modules increased daytime net radiation Q* available for partitioning by reducing surface albedo. The PV modules shift surface energy balance partitioning away from upward longwave radiation and heat storage and toward sensible heat flux Q H because of their low emissivity, low heat capacity, and increased surface area and roughness, which facilitates more efficient Q H from the surface. The PV modules significantly reduce ground heat flux Q G storage and nocturnal release, as the soil beneath the modules is well shaded. Our work demonstrates the importance of targeted observational campaigns to inform process-based understanding associated with PV systems. It further establishes a basis for observationally based PV energy balance models that may be used to examine climatic effects due to large-scale deployment.

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Jason Ching, Michael Brown, Steven Burian, Fei Chen, Ron Cionco, Adel Hanna, Torrin Hultgren, Timothy McPherson, David Sailor, Haider Taha, and David Williams

Based on the need for advanced treatments of high-resolution urban morphological features (e.g., buildings and trees) in meteorological, dispersion, air quality, and human-exposure modeling systems for future urban applications, a new project was launched called the National Urban Database and Access Portal Tool (NUDAPT). NUDAPT is sponsored by the U.S. Environmental Protection Agency (U.S. EPA) and involves collaborations and contributions from many groups, including federal and state agencies, and from private and academic institutions here and in other countries. It is designed to produce and provide gridded fields of urban canopy parameters for various new and advanced descriptions of model physics to improve urban simulations, given the availability of new high-resolution data of buildings, vegetation, and land use. Additional information, including gridded anthropogenic heating (AH) and population data, is incorporated to further improve urban simulations and to encourage and facilitate decision support and application linkages to human exposure models. An important core-design feature is the utilization of Web portal technology to enable NUDAPT to be a “community” based system. This Web-based portal technology will facilitate the customizing of data handling and retrievals (www.nudapt.org). This article provides an overview of NUDAPT and several example applications.

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