ALBERT

Description: Projecting the spatiotemporal changes in water resources under a no-analog future climate requires physically based integrated hydrologic models which simulate the transfer of water and energy across the earth's surface. These models show promise in the context of unprecedented climate extremes given their reliance on the underlying physics of the system as opposed to empirical relationships. However, these techniques are plagued by several sources of uncertainty, including the inaccuracy of input datasets such as meteorological forcing. These datasets, usually derived from climate models or satellite-based products, are typically only resolved on the order of tens to hundreds of kilometers, while hydrologic variables of interest (e.g., discharge and groundwater levels) require a resolution at much smaller scales. In this work, a high-resolution hydrologic model is forced with various resolutions of meteorological forcing (0.5 to 40.5 km) generated by a dynamical downscaling analysis from the regional climate model Weather Research and Forecasting (WRF). The Cosumnes watershed, which spans the Sierra Nevada and Central Valley interface of California (USA), exhibits semi-natural flow conditions due to its rare undammed river basin and is used here as a test bed to illustrate potential impacts of various resolutions of meteorological forcing on snow accumulation and snowmelt, surface runoff, infiltration, evapotranspiration, and groundwater levels. Results show that the errors in spatial distribution patterns impact land surface processes and can be delayed in time. Localized biases in groundwater levels can be as large as 5–10 m and 3 m in surface water. Most hydrologic variables reveal that biases are seasonally and spatially dependent, which can have serious implications for model calibration and ultimately water management decisions.

Description: The installation of roofing materials with increased solar reflectance (i.e., “cool roofs”) can mitigate the urban heat island effect and reduce energy use. In addition, meteorological changes, along with the possibility of enhanced UV reflection from these surfaces, can have complex impacts on ozone and PM2.5 concentrations. We aim to evaluate the air-quality impacts of widespread cool-roof installations prescribed by California’s Title 24 building energy efficiency standards within the heavily populated and polluted South Coast Air Basin (SoCAB). Development of a comprehensive rooftop area database and evaluation of spectral reflectance measurements of roofing materials allows us to project potential future changes in solar and UV reflectance for simulations using the Weather Research Forecast and Community Multiscale Air Quality (CMAQ) models. 2012 meteorological simulations indicate a decrease in daily maximum temperatures, daily maximum boundary layer heights, and ventilation coefficients throughout the SoCAB upon widespread installation of cool roofs. CMAQ simulations show significant increases in PM2.5 concentrations and policy-relevant design values. Changes in 8-h ozone concentrations depend on the potential change in UV reflectance, ranging from a decrease in population-weighted concentrations when UV reflectance remains unchanged to an increase when changes in UV reflectance are at an upper bound. However, 8-h policy-relevant ozone design values increase in all cases. Although the other benefits of cool roofs could outweigh small air-quality penalties, UV reflectance standards for cool roofing materials could mitigate these negative consequences. Results of this study motivate the careful consideration of future rooftop and pavement solar reflectance modification policies.

Description: The current research examines the influence of irrigation on urban hydrological cycles through the development of an irrigation scheme within the Noah land surface model (LSM)–Single Layer Urban Canopy Model (SLUCM) system. The model is run at a 30-m resolution for a 2-yr period over a 49 km2 urban domain in the Los Angeles metropolitan area. A sensitivity analysis indicates significant sensitivity relative to both the amount and timing of irrigation on diurnal and monthly energy budgets, hydrological fluxes, and state variables. Monthly residential water use data and three estimates of outdoor water consumption are used to calibrate the developed irrigation scheme. Model performance is evaluated using a previously developed MODIS–Landsat evapotranspiration (ET) and Landsat land surface temperature (LST) products as well as hourly ET observations through the California Irrigation Management Information System (CIMIS). Results show that the Noah LSM–SLUCM realistically simulates the diurnal and seasonal variations of ET when the irrigation module is incorporated. However, without irrigation, the model produces large biases in ET simulations. The ET errors for the nonirrigation simulations are −56 and −90 mm month−1 for July 2003 and 2004, respectively, while these values decline to −6 and −11 mm month−1 over the same 2 months when the proposed irrigation scheme is adopted. Results show that the irrigation-induced increase in latent heat flux leads to a decrease in LST of about 2°C in urban parks. The developed modeling framework can be utilized for a number of applications, ranging from outdoor water use estimation to climate change impact assessments.

Description: More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban environment, and hence it is critical to understand the interactive effects of urban microclimate and building heat emissions in terms of the urban energy balance. Here we developed a coupled-simulation approach to quantify these effects, mapping urban environmental data generated by the mesoscale Weather Research and Forecasting (WRF) coupled to Urban Canopy Model (UCM) to urban building energy models (UBEM). We conducted a case study in the city of Los Angeles, California, during a five-day heat wave event in September 2009. We analyzed the surge in city-scale building heat emission and energy use during the extreme heat event. We first simulated the urban microclimate at a high resolution (500 m by 500 m) using WRF-UCM. We then generated grid-level building heat emission profiles and aggregated them using prototype building energy models informed by spatially disaggregated urban land use and urban building density data. The spatial patterns of anthropogenic heat discharge from the building sector were analyzed, and the quantitative relationship with weather conditions and urban land-use dynamics were assessed at the grid level. The simulation results indicate that the dispersion of anthropogenic heat from urban buildings to the urban environment increases by up to 20% on average and varies significantly, both in time and space, during the heat wave event. The heat dispersion from the air-conditioning heat rejection contributes most (86.5%) of the total waste heat from the buildings to the urban environment. We also found that the waste heat discharge in inland, dense urban districts is more sensitive to extreme events than it is in coastal or suburban areas. The generated anthropogenic heat profiles can be used in urban microclimate models to provide a more accurate estimation of urban air temperature rises during heat waves.