Development of a fire-smoke modelling system to integrate crown fire behaviour

Abstract

Over the last decades, several real-time smoke prediction systems have been developed worldwide for air quality forecast to support decision making to control and manage anthropogenic pollutantions and smoke impacts. In Portugal, smoke modelling, as well as air quality forecast, has been developed by the research group GEMAC at the University of Aveiro, Portugal. However, the current forecast system does not integrate wildfire emissions. The ability from modelling to predict the behaviour of fire smoke in rural areas is an effective way to improve the efficiency of air quality and to prevent public health consequences. From 1980 to 2017, 4.4 Mha of cumulative burned area in rural fires, accounting for roughly half of Portugal's continental area, causing damage to infrastructure and lives. Hence, the forecast of smoke emissions has become of vital importance. There is a wide variety of models available to simulate fire-smoke phenomena. Nonetheless, it is necessary to consider computational aspects, resources, and goals to choose a suitable model to fit the purpose. In the ongoing FIRESMOKE project, developed by the GEMAC research group from University of Aveiro in Portugal, and GMAI from the Center for Weather Forecasting and Climate Studies in Brazil, the meteorological weather forecast model BRAMS-SFIRE is implemented to be part of the new version 5.6.2 of BRAMS. BRAMS-SFIRE model was coupled to simulate a broad integration between the surface fire fluxes and the atmospheric environment and presented a good accuracy in terms of the physics of the atmosphere and fire interaction. This project aims to improve the SFIRE model to include the crown fire behaviour. The goal is the incorporation of some formulations of the “crown fire potential” by linking models of surface and crown fire behaviour from Scott and Reinhardt (2001) and injecting fire smoke into the chemistry module of BRAMS. These developments are part of a whole system for forecasting and monitoring forest fire smoke emissions that incorporates other anthropogenic and biogenic sources of air pollution, to provide a public access service of atmospheric scope, over the domain of continental Portugal.