We are a team with a product devoted to forecasting energy usage
for building management,
for utility management,
for energy harvesters.
It is our endeavor. It is our vision and direction.
For energy managers...
WeatherWatt Inc. provides on-demand building energy demand-forecasting for each of your building properties up to 72 hours into the future.
Our zero-touch predictive system allows stakeholders to manage their building energy options and stay on track with their energy management objectives with minimal up-front costs.
By identifying future usage conditons, we empower energy managers to proactively prepare options to reduce peak demand.
Our forecasts, specifically tuned to your building, are delivered to you either through our secure data portal, or at your discretion, by email.
Using our insight, energy managers can lower their electric costs, mitigate risks to their budget, and further improve their impact on improving sustainability within the urban environment.
Our team has a unique set of talents and interests, enabling us to focus on the aspects of building energy usage, and energy production forecast using advanced forecast modeling with state-of-the art computer systems.
The Weather Research and Forecasting (WRF) model, developed by NCAR, is the most widely used model for US Weather Forecasters. WeatherWatt uses a modified version (uWRF) that includes a multi-layer urban canopy parameterization (BEP; Martilli et al., 2002) and a building energy model (BEM; Salamanca and Martilli, 2009) to improve forecasts of weather conditions in New York City (NYC) for the next 72-h. BEP takes into account the impact of the buildings in the momentum, energy equations and the turbulent kinetic energy. Turbulence is vertically distributed from the surface to the top of the buildings. On the other hand, the BEM considers the diffusion of heat through walls, roofs and floor; natural ventilation; radiation exchange between indoor surfaces; generations of heat due to occupants and equipment and the consumption due to air conditioning systems.
The heterogeneity of New York's urban landscape is represented using the National Building Statistics Database at 1-km (Burian et al. 2008). Three two-way nested domains were constructed with spatial grid resolution of 9, 3, 1 kilometers with finer grid covering the five boroughs of the NYC (Manhattan, Brooklyn, Queens, Bronx, and Staten Island). Fifty one terrain following sigma vertical levels were defined with twenty levels in the first kilometer. The Bougeault-Lacarrere (1989) planetary boundary layer scheme was adopted for better use with BEP/BEM urban models. The initial and boundary conditions are obtained from the North American Mesoscale model (NAM) data sets with 12 km resolution at 3-h intervals with a spin up time of 12-h. The outputs for 2-m temperature, 10-m wind speed and 1-h rain accumulations are presented at 1-h intervals for a 72-h period.
These products are continuously validated thanks to the networks of ground and vertical sensors available in the New York City metropolitan area. A well-documented validation case is the heat wave of summer 2010 (Gutierrez et al. 2013). The multilayer parameterization BEP coupled with the AC system scheme BEM showed a more accurate representation of the temperature and wind fields in the urban canopy during this extreme event. Detailed high resolution building information constitutes an important factor to correctly simulate meteorological parameters close to the surface over NYC. The anthropogenic heat from AC systems strengthened turbulent kinetic energy mainly above roof tops, where maximum turbulence was reached. Further, improvements to the urban parameterization are in progress. The main goal is to improve the latent heat representation in the urban regions by implementing a cooling tower model and evaporation from horizontal urban surfaces after rain events. Further products will be made available to the public as they are validated, including storm predictions and energy forecasts.
The goal of our company is to provide community scale weather forecasting and climate analysis for densely populated cities in the US and worldwide.
The simulations are possible thanks to The CUNY High Performance Computing Center that provides the necessary computational resources as well as the technical support for model installation.
We will enjoy an opportunity to speak with you.