Ground-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties
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hdl:2117/12315
Tipus de documentArticle
Data publicació2011-02-15
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The CALIOPE air quality modelling system, namely WRF-ARW/HERMESEMEP/
CMAQ/BSC-DREAM8b, has been used to perform the simulation of ground level
O3 concentration for the year 2004, over the Iberian Peninsula. We use this system to
study 5 the daily ground-level O3 maximum. We investigate the use of a post-processing
such as the Kalman Filter bias-adjustment technique to improve the simulated O3 maximum.
The Kalman Filter bias-adjustment technique is a recursive algorithm to optimally
estimate bias-adjustment terms from previous measurements and model results. The
bias-adjustment technique is found to improve the simulated O3 maximum for the en10
tire year and the whole domain. The corrected simulation presents improvements in
statistical indicators such as correlation, root mean square error, mean bias, standard
deviation, and gross error. After the post-processing the exceedances of O3 concentration
limits, as established by the European Directive 2008/50/CE, are better reproduced
and the uncertainty of the modelling system is reduced from 20% to 7.5%. Such un15
certainty in the model results is under the established EU limit of the 50%. Significant
improvements in the O3 average daily cycle and in its amplitude are also observed
after the post-processing. The systematic improvements in the O3 maximum simulations
suggest that the Kalman Filter post-processing method is a suitable technique to
reproduce accurate estimate of ground-level O3 concentration.
CitacióSicardi, V. [et al.]. Ground-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties. "Geoscientific model development discussions", 15 Febrer 2011, vol. 4, p. 343-384.
ISSN1991-9611
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