Modeling the climate of urban areas is of interest for studying urban heat islands (UHIs). Reliable assessment of the primary causes of UHIs and the efficacy of various heat mitigation strategies requires accurate prediction of urban temperatures and realistic representation of land surface physical characteristics in models. In this study, we expand the capabilities of the Weather Research and Forecasting (WRF) model by implementing high‐resolution, real‐time satellite observations of green vegetation fraction (GVF) and albedo. Satellite‐based GVF and albedo replace constant values that are assumed for urban pixels in the default version of WRF. Simulations of urban meteorology in Los Angeles using the improved model show marked improvements relative to the default model. The largest improvements are for nocturnal air temperatures, with a reduction in root‐mean‐square deviation between simulations and observations from 3.8 to 1.9°C. Utilizing the improved model, we quantify relationships between surface and 2 m air temperatures versus urban fraction, GVF, albedo, distance from the ocean, and elevation. Distance from the ocean is found to be the main contributor to variations in temperatures around Los Angeles. After conditionally sampling pixels to minimize the influence of distance from the ocean and elevation, we find that variations in GVF and urban fraction are responsible for up to 58 and 27% of the variance in temperatures. The satellite‐supported meteorological modeling framework reported here can be used for studying UHIs in other cities and can serve as a foundation for testing the efficacy of various heat mitigation strategies.

The climate warming effects of accelerated urbanization along with projected global climate change raise an urgent need for sustainable mitigation and adaptation strategies to cool urban climates. Our modeling results show that historical urbanization in the Los Angeles and San Diego metropolitan areas has increased daytime urban air temperature by 1.3°C, in part due to a weakening of the onshore sea breeze circulation. We find that metropolis-wide adoption of cool roofs can meaningfully offset this daytime warming, reducing temperatures by 0.9°C relative to a case without cool roofs. Residential cool roofs were responsible for 67% of the cooling. Nocturnal temperature increases of 3.1°C from urbanization were larger than daytime warming, while nocturnal temperature reductions from cool roofs of 0.5°C were weaker than corresponding daytime reductions. We further show that cool roof deployment could partially counter the local impacts of global climate change in the Los Angeles metropolitan area. Assuming a scenario in which there are dramatic decreases in greenhouse gas emissions in the 21st century (RCP2.6), mid-and end-of-century temperature increases from global change relative to current climate are similarly reduced by cool roofs from 1.4°C to 0.6°C. Assuming a scenario with continued emissions increases throughout the century (RCP8.5), midcentury warming is significantly reduced by cool roofs from 2.0°C to 1.0°C. The end-century warming, however, is significantly offset only in small localized areas containing mostly industrial/ commercial buildings where cool roofs with the highest albedo are adopted. We conclude that metropolis-wide adoption of cool roofs can play an important role in mitigating the urban heat island effect, and offsetting near-term local warming from global climate change. Global-scale reductions in greenhouse gas emissions are the only way of avoiding long-term warming, however. We further suggest that both climate mitigation and adaptation can be pursued simultaneously using 'cool photovoltaics'.

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 km 2 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 256 and 290 mm month 21 for July 2003 and 2004, respectively, while these values decline to 26 and 211 mm month 21 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 28C 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.

The California drought of 2012–2016 was a record‐breaking event with extensive social, political, and economic repercussions. The impacts were widespread and exposed the difficulty in preparing for the effects of prolonged dry conditions. Although the lessons from this drought drove important changes to state law and policy, there is little doubt that climate change will only exacerbate future droughts. To understand the character of future drought, this paper examines this recent drought period retrospectively and prospectively, that is, as it occurred historically and if similar dynamical conditions to the historical period were to arise 30 years later (2042–2046) subject to the effects of climate change. Simulations were conducted using the Weather Research and Forecasting model using the pseudo global warming method. The simulated historical and future droughts are contrasted in terms of temperature, precipitation, snowpack, soil moisture, evapotranspiration, and forest health. Overall, the midcentury drought is observed to be significantly worse, with many more extreme heat days, record‐low snowpack, increased soil drying, and record‐high forest mortality. With these findings in mind, the data sets developed in this study provide a means to structure future drought planning around a drought scenario that is realistic and modeled after a memorable historical analog.

During 2012–2014, drought in California resulted in policies to reduce water consumption. One measure pursued was replacing lawns with landscapes that minimize water consumption, such as drought‐tolerant vegetation. If implemented at broad scale, this strategy would result in reductions in irrigation and changes in land surface characteristics. In this study, we employ a modified regional climate model to assess the climatic consequences of adopting drought‐tolerant vegetation over the Los Angeles metropolitan area. Transforming lawns to drought‐tolerant vegetation resulted in daytime warming of up to 1.9°C, largely due to decreases in irrigation that shifted surface energy partitioning toward higher sensible and lower latent heat flux. During nighttime, however, adopting drought‐tolerant vegetation caused mean cooling of 3.2°C, due to changes in soil thermodynamic properties and heat exchange dynamics between the surface and subsurface. Our results show that nocturnal cooling effects, which are larger in magnitude and of great importance for public health during heat events, could counterbalance the daytime warming attributed to the studied water conservation strategy. A more aggressive implementation, assuming all urban vegetation was replaced with drought‐tolerant vegetation, resulted in an average daytime cooling of 0.2°C, largely due to strengthened sea breeze patterns, highlighting the important role of land surface roughness in this coastal megacity.