Estatio Gutierrez

Simulations of a Heat-Wave Event in New York City Using a Multilayer Urban Parameterization

AbstractThe Weather Research and Forecasting mesoscale model coupled to a multilayer urban canopy parameterization was used to evaluate the evolution of a 3-day heat wave in New York City, New York, during the summer of 2010. Results from three simulations with different degrees of urban modeling complexity and one with an absence of urban surfaces are compared with observations. To improve the city morphology representation, building information was assimilated and the land cover land-use classification was modified. The thermal and drag effects of buildings represented in the multilayer urban canopy model improve simulations over urban regions, giving better estimates of the surface temperature and wind speed. The accuracy of the simulation is further assessed against more simplified urban parameterizations models. The nighttime excessive cooling shown by the Building Energy Parameterization is compensated for when the Building Energy Model is activated. The turbulent kinetic energy is vertically distri...

On the Anthropogenic Heat Fluxes Using an Air Conditioning Evaporative Cooling Parameterization for Mesoscale Urban Canopy Models

An air conditioning evaporative cooling parameterization was implemented in a building effect parameterization/building energy model (BEP + BEM) to calculate the magnitude of the anthropogenic sensible and latent heat fluxes from buildings released to the atmosphere. The new heat flux formulation was tested in New York City (NYC) for the summer of 2010. Evaporative cooling technology diminishes between 80% and 90% of the anthropogenic sensible heat from air conditioning systems by transforming it into latent heat in commercial (COMM) areas over NYC. Average 2-m air temperature is reduced by 0.8 °C, while relative humidity is increased by 3% when cooling towers (CTs) are introduced. Additionally, CTs introduce stable atmospheric conditions in the urban canopy layer reducing turbulence production particularly during dry days.

On the Environmental Sensible/Latent Heat Fluxes From A/C Systems in Urban Dense Environments: A New Modeling Approach and Case Study

Recent trends for denser cities and associated levels of human activity reflected in energy demands are requiring new ways for quantifying human environmental impacts in cities. There is little information on human-induced environmental heat fluxes from very dense urban environments, and far less information on the anthropogenic sensible/latent heat flux partition. To address this, a surface energy model that takes into account evaporation from impervious surfaces and from cooling towers from buildings was implemented in the multilayer urban canopy model (BEP+BEM) of the Weather Forecasting Research (WRF) model to estimate the overall sensible/latent heat fluxes from urban surfaces and from air condition (A/C) systems from buildings in complex urban environments. The scenario used as case study was New York City (NYC) during summers (2010 & 2013). Urban canopy parameters from the Department of City Planning of NYC were assimilated into WRF with BEP+BEM at 250 meters horizontal resolution to have an accurate representation of the city topology. The modeling approach was calibrated with surface weather stations in NYC showing general good agreement with slight tendency to overestimate maximum temperatures and underestimate moisture content at nighttime. The A/C component was estimated in 150W/m2 latent heat due to cooling towers, and close to 40 W/m2 in sensible. Evaporative cooling technology diminishes between 80 and 90% the amount of sensible heat which is transformed into latent heat. Impacts of anthropogenic in the Planetary Boundary Layer (PBL) reflect warm season increases in the PBL height, and significant increases of atmospheric instability.Copyright

Building Peak Load Management With High Resolution Weather Data

Dense urban environments are exposed to the combined effects of rising global temperatures and urban heat islands. This combination is resulting in increasing trends of energy consumption in cities, associated mostly with air conditioning to maintain indoor human comfort conditions. During periods of extreme summer weather, electrical usage usually reaches peak loads, stressing the electrical grid. The purpose of this study is to explore the use of available, high resolution weather data by effectively preparing a building for peak load management.The subject of study is a 14 floor, 620,782 sq ft building located in uptown Manhattan, New York City (40.819257 N, −73.949288 W). To precisely quantify thermal loads of the buildings for the summer conditions; a single building energy model (SBEM), the US Department of Energy EnergyPlus™ was used. The SBEM was driven by a weather file built from weather data of the urbanized weather forecasting model (uWRF), a high resolution weather model coupled to a building energy model. The SBEM configuration and simulations were calibrated with winter actual gas and electricity data using 2010 as the benchmark year. In order to show the building peak load management, demand response techniques and technologies were implemented. The methods used to prepare the building included generator usage during high peak loads and use of a thermal storage system. An ensemble of cases was analyzed using current practice, use of high resolution weather data, and use of building preparation technologies. Results indicated an average summer peak savings of more than 30% with high resolution weather data.Copyright

Modeling Building HVAC Energy Consumption During an Extreme Heat Event in a Dense Urban Environment

Dense urban environments are exposed to the combined effects of rising global temperatures and urban heat islands, a thermal gradient between the urban centers and the less urbanized surroundings suburbs. This combination is resulting in increasing trends of energy consumption in cities, associated mostly to air conditioning to maintain indoor human comfort conditions. The energy demand is further magnified during extreme heat events to a point where the electrical grid may be at risk. Given the anticipated increased frequency of extreme heat events for the future, it is imperative to develop methodologies to quantify energy demands from buildings during extreme heat events.The purpose of this study is to precisely quantify thermal loads of buildings located in the very dense urban environment of New York City under an extreme heat event that took place in the summer of 2010 (July 4–8). Two approaches were used to quantify thermal loads of buildings for these conditions; a single building energy model (SBEM), such as the US Department of Energy eQUEST and EnergyPlus™, and an urbanized weather forecasting model (uWRF) coupled to a building energy model. The SBEM was driven by Typical Meteorological Year (TMY) weather file and by a customized weather file built from uWRF’s weather data for the specific days of the heat wave. A series of simulations were conducted with both SBEM software to model building energy consumption data due to air conditioning for two locations in Uptown and Midtown Manhattan, NY, which represented a low density and a high density building area within the city. Assumptions were made regarding the building’s floor plans and operation schedule to simplify the model and provide a close comparison to uWRF.Results of the ensemble of SBEM indicate there was an increase in energy consumption during the July 2010 heat-wave when compared with the central park TMY case. The uptown location consumed 137% more energy during the heat wave event, while the midtown location showed an increased in energy consumption of 125% when compared to a typical July three day period, reaching total loads of close to 9812 kWh for a 20 m height building. Comparison of the results directly from uWRF for the energy consumption for same locations, indicate that for the midtown location both SBEMs underestimated the total energy consumption within a factor of three. This may be due to the fact that uWRF energy model takes into account urban microclimate parameters such as anthropogenic sources and waste heat interactions between surrounding buildings.Copyright

A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities

The thermal response of a large city including the energy production aspects of it are explored for a large and complex city using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) mesocale model is coupled to a multi-layer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor-outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High resolution (250 m.) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multi-layer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the surface temperature and wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.© 2011 ASME