Izvorni znanstveni članak
EVALUATION OF METHODS FOR INTEGRATING MONITORING AND MODELLING DATA FOR REGULATORY AIR QUALITY ASSESSMENTS
Angela Ball
; Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3LN, UK.
Richard Hill
; Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3LN, UK.
Peter Jenkinson
; Westlakes Scientific Consulting Ltd, The Princess Royal Building, Westlakes Science and Technology Park, Moor Row, Cumbria, CA24 3LN, UK.
Sažetak
Measured and modelled SO2 concentration data from Kincaid, Illinois (USA) and the Aire Valley (UK) were used to
evaluate four data assimilation methods to determine their effectiveness in calibrating modelled air concentrations. The data
assimilation methods included two simple methods (linear regression and simple ratio), which resulted in a global adjustment of the
modelled concentration field and two complex methods (kriging of the ratio and kriging of the residual), which resulted in a
spatially varying calibration of the modelled concentration field. Prior to the analysis, the measured data were ‘sector-corrected’ to
remove the influence of external sources to ensure a direct comparison between the calibration methods. A cross-validation
technique, applying standard model evaluation statistics, was used to assess the performance of each calibration method. The simple
ratio method provided the most accurate model calibration for both the Kincaid and the Aire Valley data sets by minimising the
normalised mean square error and mean bias and maximising the fraction of modelled predictions within a factor of two of
measured predictions. The linear regression method performed to a similar level when using a high number of data points, although
the performance declined dramatically when just two monitoring points were used for calibration. The more complex kriging
methods were found to be less effective than the simple methods, despite offering a spatially varying model calibration. The analysis
of the Kincaid data set suggests that between 10 and 15 monitoring points may be necessary for the optimum calibration of a
modelled concentration field using the simple calibration methods reviewed in this study.
Ključne riječi
data assimilation; model calibration; sector-correction; kriging; cross-validation
Hrčak ID:
64289
URI
Datum izdavanja:
12.12.2008.
Posjeta: 1.210 *