Aplicação dos Modelos de Interação Atmosférica e de Incêndio Florestal BRAMS-SFIRE no sul de Portugal

Menezes, Isilda; Freitas, Saulo R.; Lima, Rafael; Fonseca, Rafael M.; Oliveira, Valter; Braz, Rodrigo; Dias, Susana; Surový, Peter; Ribeiro, Nuno de Almeida

doi:10.1590/0102-77863630101

Cited by 5 publications

(5 citation statements)

References 37 publications

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“…The SFIRE model (Mandel et al, 2009(Mandel et al, , 2011 coupled to BRAMS (Freitas et al, 2017) by Menezes (2016Menezes ( , 2021a allows the analysis of surface fire behaviour taking into account the type of fuel bed and its moisture, the topography and the atmospheric wind. Under the FIRESMOKE project, the developments of BRAMS-SFIRE comprise the up-grade for the last version of SFIRE, the introduction of a mathematical model for predicting surface fire spread (Rothermel, 1972) for fire behaviour fuel model 10 (timber litter and understory) (Anderson, 1982) and of the conceptual model for predicting behaviour and size of crown fires from Rothermel (1991), including conditions for the crown fire starting and spreading for coniferous forest fuel types (Van Wagner, 1977), based on the research of Scott and Reinhardt (2001).…”

Section: Overview Of Ongoing Fire Developments On Bramsmentioning

confidence: 99%

“…The BRAMS-SFIRE system (Menezes et al, 2016(Menezes et al, , 2021aFreitas et al, 2017) aims at overcoming this challenge. BRAMS is continuously under development to better simulate atmospheric processes and the coupled SFIRE simultaneously simulates the interactions between the surface fire fluxes and the atmospheric environment, both on the mesoscale and micro-scale.…”

Section: Introductionmentioning

confidence: 99%

“…BRAMS is continuously under development to better simulate atmospheric processes and the coupled SFIRE simultaneously simulates the interactions between the surface fire fluxes and the atmospheric environment, both on the mesoscale and micro-scale. The BRAMS-SFIRE system, which is the representation of fire spread, presented excellent results in terms of the physics of the atmosphere and fire interaction (Menezes, 2016(Menezes, , 2021a promising a reliable performance for fire-smoke after the development of the crown fire spread model.…”

Section: Introductionmentioning

confidence: 99%

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

Menezes¹,

Rodrigues²,

Freitas³

et al. 2022

Advances in Forest Fire Research 2022

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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 â€œcrown fire potentialâ€ 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.

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Section: Overview Of Ongoing Fire Developments On Bramsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Menezes¹,

Rodrigues²,

Freitas³

et al. 2022

Advances in Forest Fire Research 2022

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“…(5) Quantities Q j and P i are intimately related to the study of terrain properties (an example can be found in the work [8]). In the absence of an external vectorial influence, such as wind or slope, which directly affects fire trajectory, ψ ij = 0 and therefore, ψ ij is not considered for the calculation of p ij .…”

Section: Homogeneous Gridmentioning

confidence: 99%

“…Fire behaves according to three interacting physical factors: fuel availability (morphological and physiological characteristics of vegetation), weather (wind speed and direction, temperature, and relative humidity) and terrain (slope and aspect) [7,8]-along this article we will refer to such factors as FWT conditions. Based on the knowledge of a land patch regarding these factors, and data on the initial fire condition it's possible to calculate an average value for the fire spreading rate [9].…”

Section: Introductionmentioning

confidence: 99%

Modelling Forest Fires Using Complex Networks

Perestrelo

Grácio

Ribeiro

et al. 2021

MCA

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Forest fires have been a major threat to the environment throughout history. In order to mitigate its consequences, we present, in a first of a series of works, a mathematical model with the purpose of predicting fire spreading in a given land portion divided into patches, considering the area and the rate of spread of each patch as inputs. The rate of spread can be estimated from previous knowledge on fuel availability, weather and terrain conditions. We compute the time duration of the spreading process in a land patch in order to construct and parametrize a landscape network, using cellular automata simulations. We use the multilayer network model to propose a network of networks at the landscape scale, where the nodes are the local patches, each with their own spreading dynamics. We compute some respective network measures and aim, in further work, for the establishment of a fire-break structure according to increasing accuracy simulation results.

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