Limitations on the accuracy of model predictions of wildland fire behaviour: A state-of-the-knowledge overview

2013 ◽  
Vol 89 (03) ◽  
pp. 372-383 ◽  
Author(s):  
Martin E. Alexander ◽  
Miguel G. Cruz

The degree of accuracy in model predictions of wildland fire behaviour characteristics are dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data. While much progress has been made by fire behaviour research in the past 35 years or so in addressing these three sources of model error, the accuracy in model predictions are still very much at the mercy of our present understanding of the natural phenomena exhibited by free-burning wildland fires and the inherent temporal and spatial variability in the fire environment. This paper will serve as a state-of-the-art primer on the subject of error sources in model predictions of wildland fire behaviour and includes a short historical overview of wildland fire behaviour research as it relates to model development.

2018 ◽  
Vol 27 (11) ◽  
pp. 770 ◽  
Author(s):  
William Mell ◽  
Albert Simeoni ◽  
Dominique Morvan ◽  
J. Kevin Hiers ◽  
Nicholas Skowronski ◽  
...  

In a recent communication, Cruz et al. (2017) called attention to several recurring statements (mantras) in the wildland fire literature regarding empirical and physical fire behaviour models. Motivated by concern that these mantras have not been fully vetted and are repeated blindly, Cruz et al. (2017) sought to verify five mantras they identify. This is a worthy goal and here we seek to extend the discussion and provide clarification to several confusing aspects of the Cruz et al. (2017) communication. In particular, their treatment of what they call physical models is inconsistent, neglects to reference current research activity focussed on combined experimentation and model development, and misses an opportunity to discuss the potential use of physical models to fire behaviour outside the scope of empirical approaches.


2018 ◽  
Author(s):  
Anna Nikandrova ◽  
Ksenia Tabakova ◽  
Antti Manninen ◽  
Riikka Väänänen ◽  
Tuukka Petäjä ◽  
...  

Abstract. Understanding the distribution of aerosol layers is important for determining long range transport and aerosol radiative forcing. In this study we combine airborne in situ measurements of aerosol with data obtained by a ground-based High Spectral Resolution Lidar (HSRL) and radiosonde profiles to investigate the temporal and vertical variability of aerosol properties in the lower troposphere. The HSRL was deployed in Hyytiälä, Southern Finland, from January to September 2014 as a part of the US DoE ARM (Atmospheric Radiation Measurement) mobile facility during the BAECC (Biogenic Aerosols – Effects on Cloud and Climate) Campaign. Two flight campaigns took place in April and August 2014 with instruments measuring the aerosol size distribution from 10 nm to 10 µm at altitudes up to 3800 m. Two case studies from the flight campaigns, when several aerosol layers were identified, were selected for further investigation: one clear sky case, and one partly cloudy case. During the clear sky case, turbulent mixing ensured low temporal and spatial variability in the measured aerosol size distribution in the boundary layer whereas mixing was not as homogeneous in the boundary layer during the partly cloudy case. The elevated layers exhibited greater temporal and spatial variability in aerosol size distribution, indicating a lack of mixing. New particle formation was observed in the boundary layer during the clear sky case, and nucleation mode particles were also seen in the elevated layers that were not mixing with the boundary layer. Interpreting local measurements of elevated layers in terms of long-range transport can be achieved using back trajectories from Lagrangian models, but care should be taken in selecting appropriate arrival heights, since the modelled and observed layer heights did not always coincide. We conclude that higher confidence in attributing elevated aerosol layers with their air mass origin is attained when back trajectories are combined with lidar and radiosonde profiles.


2006 ◽  
Vol 26 (3) ◽  
pp. 351-362 ◽  
Author(s):  
T.J. Tolhurst ◽  
E.C. Defew ◽  
J.F.C. de Brouwer ◽  
K. Wolfstein ◽  
L.J. Stal ◽  
...  

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