Selection of a Parsimonious Empirical Correction Rule for a Deterministic Air Quality Model

UM > HENRY FOK PEARL JUBILEE COLLEGE

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	Selection of a Parsimonious Empirical Correction Rule for a Deterministic Air Quality Model
	Mok, K. M.; Hoi, K. I.; Yuen, K. V.; Miranda, A. I.; Borrego, C.; Ribeiro, I.
	2015-06-01
Source Publication	Proceedings of the 2015 International Conference on Earth Observations & Societal Impacts and ICLEI Resilience Forum
Publication Place	Kaohsiung
Publisher	National Kaohsiung Marine University
Abstract	Correction of a deterministic air-quality-model output based on data of monitoring stations is a recent trend in modeling. However, the rule of correction is empirical and there is no consensus about its most appropriate form. A complicated rule may achieve better accuracy, but it is more sensitive to modeling error compared to a simple one. Hence, the present study aims to find a parsimonious (efficient but robust) correction rule based on the Bayesian approach. This approach can allow users to evaluate different models through their occurring probability computed by an asymptotic expansion of the product of the likelihood (accuracy) and the Ockham factor (robustness). A parsimonious model is achieved through optimization of the model probability. The proposed methodology is applied to correct the 1-day ahead forecast of daily averaged [PM10] by a deterministic model WRF-EURAD at an urban traffic station of Porto, Portugal between 2012 and 2013. The selected correction rule gave good correction performance compared to other candidates. Hence the Bayesian approach is a promising tool to assist in correcting empirically results of deterministic models.
Keyword	Bayesian: empirical correction deterministic air quality model
Language	英語English
The Source to Article	PB_Publication
PUB ID	15592
Document Type	Conference paper
Collection	HENRY FOK PEARL JUBILEE COLLEGE
Corresponding Author	Mok, K. M.
Recommended Citation GB/T 7714	Mok, K. M.,Hoi, K. I.,Yuen, K. V.,et al. Selection of a Parsimonious Empirical Correction Rule for a Deterministic Air Quality Model[C], Kaohsiung:National Kaohsiung Marine University, 2015.
APA	Mok, K. M.., Hoi, K. I.., Yuen, K. V.., Miranda, A. I.., Borrego, C.., & Ribeiro, I. (2015). Selection of a Parsimonious Empirical Correction Rule for a Deterministic Air Quality Model. Proceedings of the 2015 International Conference on Earth Observations & Societal Impacts and ICLEI Resilience Forum.

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