BlueSky Modeling Framework: Current application, user tools, and future additions

The BlueSky Smoke Modeling Framework (BlueSky) uses models, static and dynamic datasets, and real-time satellite data streams to simulated fuel consumption, smoke emissions, and plume rise and transport. BlueSky is a modular system that allows for addition and modification of the smoke modeling pathway with new models or datasets. BlueSky can be applied to: simulate smoke transport and air quality impacts over the next three-seven days; determine probable smoke behavior from a prescribed fire based on climatological data; estimate emissions from fire on a regional and national scale; and assess model pathway uncertainties, strengths, and weaknesses. BlueSky is embedded in many real-time smoke prediction systems including the U.S. National Weather Service’s Operational Smoke Predictions and the U.S. National Emissions Inventory uses BlueSky to estimate fire emissions. BlueSky is a framework that incorporates many different models at each modeling step ([Fuel loading]-[fuel Consumption]-[Time rate of consumption]-[Emissions]-[Plume rise]-[Transport and dispersion of smoke]). The underlying models are not changed from their original form or programming language, instead, they are surrounded by a Python wrapper. These wrappers serve as a standard interface throughout the framework and ensure that the models receive the data they require in the proper format. This unprecedented flexibility allows for the user to select models and datasets at each modeling step. BlueSky users can choose from over 3,000 different model pathway combinations. The utility of BlueSky is through its framework, for example, any model enabled within BlueSky can automatically be served in a web-services environment and used remotely. This enables novel applications for both the science and community end-user. We present current applications, decision support system tools and current research uses, and a discussion of future BlueSky framework development.