OZONE FORECASTING FROM METEOROLOGICAL VARIABLES PART II - DAILY MAXIMUM GROUND-LEVEL OZONE CONCENTRATION FROM LOCAL WEATHER FORECASTS

Citation
Bgj. Massart et al., OZONE FORECASTING FROM METEOROLOGICAL VARIABLES PART II - DAILY MAXIMUM GROUND-LEVEL OZONE CONCENTRATION FROM LOCAL WEATHER FORECASTS, Chemometrics and intelligent laboratory systems, 42(1-2), 1998, pp. 191-197
Citations number
21
Categorie Soggetti
Computer Science Artificial Intelligence","Robotics & Automatic Control","Instument & Instrumentation","Chemistry Analytical","Computer Science Artificial Intelligence","Robotics & Automatic Control
ISSN journal
01697439
Volume
42
Issue
1-2
Year of publication
1998
Pages
191 - 197
Database
ISI
SICI code
0169-7439(1998)42:1-2<191:OFFMVP>2.0.ZU;2-X
Abstract
A ground-level ozone concentration prediction procedure is tested unde r real-world circumstances. Models are constructed for measured meteor ological variables to predict ozone concentrations. Subsequently, a we ather forecast is used as input to the prediction in order to obtain a n estimate of the next day's maximum ozone concentration. The work inv estigates whether the additional variance, introduced by the use of we ather forecasts, still allows accurate ozone concentration predictions . Two simulation studies were performed in order to check the predicti ve ability and the effect of the weather forecast accuracy. Good predi ction accuracy was obtained. Only 2.6% of the predictions lead to resi duals exceeding 40 mu g/m(3). In addition, the influence of the uncert ainty in the weather forecasts is generally low in these cases (3.39 t o 3.75 mu g/m(3)). Real predictions in the region of Grenland, Norway, for the summer of 1996 showed good agreement between measured and cal culated maximum ozone levels. Only 3.5% of the predictions yielded res iduals exceeding 40 mu g/m(3). (C) 1998 Elsevier Science B.V. All righ ts reserved.