A comparison of different approaches for the prediction of wind fields in areas of complex orography

Wildland fire models and simulators are increasingly applied in different ecosystems and countries of the world to predict fire behaviour and effects, and to support fire prevention and management programs. In addition to the simplifications and preliminary assumptions of fire spread models, criticisms of fire simulators frequently concern the need of high resolution environmental data (fuel model maps, canopy cover, etc.), and, in particular, data of environmental variables that quickly change in space and time (e.g. wind speed and direction). The rapid increase in computational resources and numerical methods over the last few years helps to provide high temporal and spatial resolution data on wind fields in order to improve the accuracy of simulations at both local and regional scale. This work analyses the predicting capabilities of different approaches for wind flow simulation in an area characterized by a complex orography and compares them to experimental data collected by a network of weather stations specifically designed. Simulation methods include an in-house mass-consistent solver (which finds a divergence-free wind field using a finite-difference approach in combination with a multi-grid methodology) and a number of Computational Fluid Dynamics (CFD) approaches (commercial and open-source) with different turbulence closures.