In recent years, the continued increase in computing power has been combined with the availability of ever higher resolution geographic data (like topography, vegetation, ground cover, and soil type) to allow many universities, research consortia, and businesses to run highly tailored mesoscale computer models.
At present, the most common of these models include the Penn State/UCAR MM5 model and its successor, the Weather Research and Forecasting (WRF) model, developed by NCAR, NOAA NCEP, and others. These are extremely powerful and generalized modeling systems, designed to be applicable across a wide range of forecasting regimes and locales.
While this generalized approach is appropriate when attempting to develop broad solutions that can be implemented in multiple instances, it can be limiting when tackling smaller scale problems in specific locations. With this in mind, WeatherFlow chooses to develop modeling solutions that are tailored to the client’s specific needs and constraints. Thus WeatherFlow meteorologists and modelers can choose the most appropriate model for the task, whether it is WRF or WeatherFlow’s own proprietary WRAMS model. This greatly improves our ability to more accurately model very specific regimes like the coastal zone.