A ground-level ozone forecasting model for Santiago, Chile
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Date
2002
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Publisher
WILEY-BLACKWELL
Abstract
A physically based model for ground-level ozone forecasting is evaluated for Santiago, Chile. The model predicts the daily peak ozone concentration, with the daily rise of air temperature as input variable; weekends and rainy days appear as interventions. This model was used to analyse historical data, using the Linear Transfer Function/Finite Impulse Response (LTF/FIR) formalism; the Simultaneous Transfer Function (STF) method was used to analyse several monitoring stations together. Model evaluation showed a good forecasting performance across stations-for low and high ozone impacts-with power of detection (POD) values between 70 and 100%, Heidke's Skill Scores between 40% and 70% and low false alarm rates (FAR). The model consistently outperforms a pure persistence forecast. Model performance was not sensitive to different implementation options. The model performance degrades for two- and three-days ahead forecast, but is still acceptable for the purpose of developing an environmental warning system at Santiago. Copyright (C) 2002 John Wiley Sons, Ltd.
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Keywords
ground-level ozone forecast, forecast evaluation, FIR model, LTF model, STF model, NEURAL-NETWORK MODEL, TIME-SERIES ANALYSIS, LOWER FRASER VALLEY, LOS-ANGELES-BASIN, AIR-QUALITY DATA, MAXIMUM, POLLUTANTS, POLLUTION, AREA, IDENTIFICATION