Articles | Volume 10, issue 3
https://doi.org/10.5194/gmd-10-1199-2017
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, Sylvain Mailler, Bertrand Bessagnet, Guillaume Siour, Augustin Colette, Florian Couvidat, and Frédérik Meleux

Related authors

Air quality modeling intercomparison and multi-scale ensemble chain for Latin America
Jorge E. Pachon, Mariel Opazo, Pablo Lichtig, Nicolas Hunneus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Laura Dawidowski, Nestor Y. Rojas, Maria de Fatima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
EGUsphere, https://doi.org/10.5194/egusphere-2024-815,https://doi.org/10.5194/egusphere-2024-815, 2024
Short summary
An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023,https://doi.org/10.5194/gmd-16-7509-2023, 2023
Short summary
Impact of the Guinea coast upwelling on atmospheric dynamics, precipitation and pollutant transport over southern West Africa
Gaëlle de Coëtlogon, Adrien Deroubaix, Cyrille Flamant, Laurent Menut, and Marco Gaetani
Atmos. Chem. Phys., 23, 15507–15521, https://doi.org/10.5194/acp-23-15507-2023,https://doi.org/10.5194/acp-23-15507-2023, 2023
Short summary
New straightforward formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
EGUsphere, https://doi.org/10.5194/egusphere-2023-2637,https://doi.org/10.5194/egusphere-2023-2637, 2023
Short summary
Variability and combination as an ensemble of mineral dust forecasts during the 2021 CADDIWA experiment using the WRF 3.7.1 and CHIMERE v2020r3 models
Laurent Menut
Geosci. Model Dev., 16, 4265–4281, https://doi.org/10.5194/gmd-16-4265-2023,https://doi.org/10.5194/gmd-16-4265-2023, 2023
Short summary

Related subject area

Atmospheric sciences
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024,https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024,https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024,https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024,https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024,https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary

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.
Download
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.