Coupled atmosphere-wildland fire modeling with WRF-Fire

We describe the physical model, numerical algorithms, and software structure of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the level-set method, coupled with the Weather Research and Forecasting model. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. The level-set method allows submesh representation of the burning region and flexible implementation of various ignition modes. WRF-Fire is distributed as a part of WRF and it uses the WRF parallel infrastructure for parallel computing.Comment: Version 3.3, 41 pages, 2 tables, 12 figures. As published in Discussions, under review for Geoscientific Model Developmen

Evaluation of WRF-Sfire Performance with Field Observations from the FireFlux experiment

This study uses in-situ measurements collected during the FireFlux field experiment to evaluate and improve the performance of coupled atmosphere-fire model WRF-Sfire. The simulation by WRF-Sfire of the experimental burn shows that WRF-Sfire is capable of providing realistic head fire rate-of-spread and the vertical temperature structure of the fire plume, and, up to 10 m above ground level, fire-induced surface flow and vertical velocities within the plume. The model captured the changes in wind speed and direction before, during, and after fire front passage, along with arrival times of wind speed, temperature, and updraft maximae, at the two instrumented flux towers used in FireFlux. The model overestimated vertical velocities and underestimated horizontal wind speeds measured at tower heights above the 10 m, and it is hypothesized that the limited model resolution over estimated the fire front depth, leading to too high a heat release and, subsequently, too strong an updraft. However, on the whole, WRF-Sfire fire plume behavior is consistent with the interpretation of FireFlux observations. The study suggests optimal experimental pre-planning, design, and execution of future field campaigns that are needed for further coupled atmosphere-fire model development and evaluation

Model simulations of complex dust emissions over the Sahara during the West African monsoon onset

The existing limitations in ground-based observations in remote areas in West Africa determine the dependence on numerical models to represent the atmospheric mechanisms that contribute to dust outbreaks at different space-time scales. In this work, the ability of the Weather Research and Forecasting model coupled with the Chemistry (WRF-Chem) model using the GOCART dust scheme is evaluated. The period comprises the West African Monsoon onset phase (the 7th to 12th of June, 2006) coinciding with the AMMA Special Observing Period (SOP). Different features in the horizontal and vertical dynamical structure of the Saharan atmosphere are analyzed with a combination of satellite and ground-based observations and model experimentation at 10 and 30 km model resolution. The main features of key Saharan dust processes during summer are identifiable, and WRF-CHEM replicates these adequately. Observations and model analyses have shown that cold pools (haboobs) contributed a substantial proportion of total dust during the study period. The comparative analysis between observations and WRF-Chem simulations demonstrates the model efficiency to simulate the spatial and 3D structure of dust transport over the Sahara and Sahel. There is, therefore, a strong basis for accurate forecasting of dust events associated with synoptic scale events when model dust emission parameterization is suitably calibrated

Fast Fourier Transform Ensemble Kalman Filter with Application to a Coupled Atmosphere-Wildland Fire Model

We propose a new type of the Ensemble Kalman Filter (EnKF), which uses the Fast Fourier Transform (FFT) for covariance estimation from a very small ensemble with automatic tapering, and for a fast computation of the analysis ensemble by convolution, avoiding the need to solve a sparse system with the tapered matrix. The FFT EnKF is combined with the morphing EnKF to enable the correction of position errors, in addition to amplitude errors, and demonstrated on WRF-Fire, the Weather Research Forecasting (WRF) model coupled with a fire spread model implemented by the level set method.Comment: 8 page