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August 2003 Statistical Assessment of Numerical Models
Montserrat Fuentes, Peter Guttorp, Peter Challenor
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Internat. Statist. Rev. 71(2): 201-221 (August 2003).

Abstract

Evaluation of physically based computer models for air quality applications is crucial to assist in control strategy selection. The high risk of getting the wrong control strategy has costly economic and social consequences. The objective comparison of modeled concentrations with observed field data is one approach to assessment of model performance. For dry deposition fluxes and concentrations of air pollutants there is a very limited supply of evaluation data sets. We develop a formal method for evaluation of the performance of numerical models, which can be implemented even when the field measurements are very sparse. This approach is applied to a current U.S. Environmental Protection Agency air quality model. In other cases, exemplified by an ozone study from the California Central Valley, the observed field is relatively data rich, and more or less standard geostatistical tools can be used to compare model to data. Yet another situation is when the cost of model runs is prohibitive, and a statistical approach to approximating the model output is needed. We describe two ways of obtaining such approximations.

footnote: This research was sponsored by a National Science Foundation grant DMS 0002790 and by a US EPA award R-8287801.

A common technical issue in the assessment of environmental numerical models is the need for tools to estimate nonstationary spatial covariance structures. We describe in detail two such approaches.

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Montserrat Fuentes. Peter Guttorp. Peter Challenor. "Statistical Assessment of Numerical Models." Internat. Statist. Rev. 71 (2) 201 - 221, August 2003.

Information

Published: August 2003
First available in Project Euclid: 18 November 2003

zbMATH: 1114.62365

Rights: Copyright © 2003 International Statistical Institute

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Vol.71 • No. 2 • August 2003
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