Articles | Volume 10, issue 3
Geosci. Model Dev., 10, 1199–1208, 2017
https://doi.org/10.5194/gmd-10-1199-2017
Geosci. Model Dev., 10, 1199–1208, 2017
https://doi.org/10.5194/gmd-10-1199-2017

Methods for assessment of models 17 Mar 2017

Methods for assessment of models | 17 Mar 2017

An alternative way to evaluate chemistry-transport model variability

Laurent Menut et al.

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Cited articles

Appel, K. W., Gilliam, R. C., Davis, N., Zubrow, A., and Howard, S. C.: Overview of the atmospheric model evaluation tool (AMET) v1.1 for evaluating meteorological and air quality models, Environ. Modell. Softw., 26, 434–443, https://doi.org/10.1016/j.envsoft.2010.09.007, 2011.
Baldridge, K. and Cox, W.: Evaluating air quality model performance, Environ. Softw., 1, 182–187, https://doi.org/10.1016/0266-9838(86)90023-7, 1986.
Campbell, P., Zhang, Y., Yahya, K., Wang, K., Hogrefe, C., Pouliot, G., Knote, C., Hodzic, A., Jose, R. S., Perez, J. L., Guerrero, P. J., Baro, R., and Makar, P.: A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) phase 2 over North America: Part I. Indicators of the sensitivity of O3 and PM2. 5 formation regimes, Atmos. Environ., 115, 569–586, https://doi.org/10.1016/j.atmosenv.2014.12.026, 2015.
Chang, J. and Hanna, S.: Air quality model performance evaluation, Meteorol. Atmos. Phys., 87, 167–196, https://doi.org/10.1007/s00703-003-0070-7, 2004.
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Short summary
A simple and complementary model evaluation technique for regional chemistry transport is discussed. The methodology is based on the concept that we can learn about model performance by comparing the simulation results with observational data available for time periods other than the period originally targeted.