Capturing Plume Rise and Dispersion with a Coupled Large-Eddy Simulation: Case Study of a Prescribed Burn

Current understanding of the buoyant rise and subsequent dispersion of smoke due to wildfires has been limited by the complexity of interactions between fire behavior and atmospheric conditions, as well as the uncertainty in model evaluation data. To assess the feasibility of using numerical models to address this knowledge gap, we designed a large-eddy simulation of a real-life prescribed burn using a coupled semi-emperical fire–atmosphere model. We used observational data to evaluate the simulated smoke plume, as well as to identify sources of model biases. The results suggest that the rise and dispersion of fire emissions are reasonably captured by the model, subject to accurate surface thermal forcing and relatively steady atmospheric conditions. Overall, encouraging model performance and the high level of detail offered by simulated data may help inform future smoke plume modeling work, plume-rise parameterizations and field experiment designs

Episodic Ozone Pollution in the Lower Fraser Valley, BC: A Tale of Three Episodes

The spatiotemporal characteristics of episodic ozone pollution in the Lower Fraser Valley of British Columbia have changed markedly over the past two decades. These changes are documented by Ainslie and Steyn (2007), who hypothesize that they have come about because of reductions in ozone precursor emissions strength, driven by aggressive air quality management plans. This study sheds further light on this phenomenon by a parallel spatiotemporal analysis of three notable episodes, one in 1988, one in 1998 and one in 2009. These three episodes span the emissions reductions initiatives, and the analysis is designed to cast light on potential for future air quality management strategies. The analysis is based on a combined air quality and meteorological definition of an ozone episode. This paper investigates the particular meteorological conditions during each of these episodes, and shows that the most recent episode is characterized by record high temperatures, and suppression of the mixed layer, distinct from other episodes. In spite of reduced total emissions, the unusual meteorological conditions provide a context in which ozone pollution can still exceed applicable standards. The paper speculates on the implications for ozone pollution episodes in changed climates.Science, Faculty ofEarth and Ocean Sciences, Department ofUnreviewedUndergraduat

Capturing Plume Rise and Dispersion with a Coupled Large-Eddy Simulation: Case Study of a Prescribed Burn

Current understanding of the buoyant rise and subsequent dispersion of smoke due to wildfires has been limited by the complexity of interactions between fire behavior and atmospheric conditions, as well as the uncertainty in model evaluation data. To assess the feasibility of using numerical models to address this knowledge gap, we designed a large-eddy simulation of a real-life prescribed burn using a coupled semi-emperical fire–atmosphere model. We used observational data to evaluate the simulated smoke plume, as well as to identify sources of model biases. The results suggest that the rise and dispersion of fire emissions are reasonably captured by the model, subject to accurate surface thermal forcing and relatively steady atmospheric conditions. Overall, encouraging model performance and the high level of detail offered by simulated data may help inform future smoke plume modeling work, plume-rise parameterizations and field experiment designs.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofReviewedFacult

Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica

Rainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwater recharge and hydroelectricity production. We propose a novel model of rainfall in this region, the double-Gaussian model, which uses monthly total rainfall data collected from 1980 to 2020 from two meteorological observation stations. Our model provides an intuitive way of describing the seasonality of rainfall, the inter-annual variability of the cycle, and variability due to the monthly Oceanic Niño Index, ONI. We also consider two alternative models, a regression model with ARMA errors and a Tweedie model, as a means of assessing the robustness of our conclusions to violations of the assumptions of the double-Gaussian model. We found that the data provide strong evidence of an increase/decrease in rainfall in both temporal maxima during La Niña/El Niño (negative/positive ONI) conditions but no evidence of a decade-scale trend after accounting for ONI effects. Finally, we investigated the problem of forecasting future rainfall based on our three models. We found that when ONI is incorporated as a predictor variable, our models can produce substantial gains in prediction accuracy of spring, summer, and annual totals over naive methods based on monthly sample means or medians

Temporal and Spatial Variability of Annual Rainfall Patterns in Guanacaste, Costa Rica

We analyze a body of rainfall data covering 38 years from five meteorological stations in the Nicoya Peninsula of the Guanacaste Province, Costa Rica. The purpose of the analysis is to uncover spatial and temporal variability of rainfall in order to support research into water and sustainability under the FuturAgua project. We use a variety of statistical analysis and modelling techniques. The analysis uncovers a relatively suppressed spatial pattern of rainfall. Rainfall totals for periods shorter than two weeks are dominated by strong stochastic variability, while longer totalizing periods reveal systematic variation. Monthly totals show the strong double peak, and associated midsummer drought that has been previously reported. The annual cycle can be efficiently captured by a double Gaussian model. A simple application of this model to individual years shows large inter- annual variability, and a strong dependence of the second rainfall peak on the Oceanic Niño Index (ONI). A Bayesian analysis confirms the appropriateness of the double Gaussian model, and quantifies the strength of the dependence on ONI. We discuss the implications of our statistical analyses for research under the FuturAgua project.Science, Faculty ofNon UBCEarth, Ocean and Atmospheric Sciences, Department ofStatistics, Department ofUnreviewedFacult