Articles | Volume 9, issue 1
Geosci. Model Dev., 9, 393–412, 2016

Special issue: Coupled chemistry–meteorology modelling: status and...

Geosci. Model Dev., 9, 393–412, 2016
Model experiment description paper
29 Jan 2016
Model experiment description paper | 29 Jan 2016

A low-order coupled chemistry meteorology model for testing online and offline data assimilation schemes: L95-GRS (v1.0)

J.-M. Haussaire and M. Bocquet

Related authors

Deep learning of subgrid-scale parametrisations for short-term forecasting of sea-ice dynamics with a Maxwell-Elasto-Brittle rheology
Tobias Sebastian Finn, Charlotte Durand, Alban Farchi, Marc Bocquet, Yumeng Chen, Alberto Carrassi, and Véronique Dansereau
EGUsphere,,, 2023
Short summary
Segmentation of XCO2 images with deep learning: application to synthetic plumes from cities and power plants
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev. Discuss.,,, 2022
Preprint under review for GMD
Short summary
New plume comparison metrics for the inversion of passive gases emissions
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech. Discuss.,,, 2022
Revised manuscript under review for AMT
Short summary
A fast, single-iteration ensemble Kalman smoother for sequential data assimilation
Colin Grudzien and Marc Bocquet
Geosci. Model Dev., 15, 7641–7681,,, 2022
Short summary
Bayesian transdimensional inverse reconstruction of the 137Cs Fukushima-Daiichi release
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev. Discuss.,,, 2022
Revised manuscript accepted for GMD
Short summary

Related subject area

Numerical methods
The Intelligent Prospector v1.0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration
John Mern and Jef Caers
Geosci. Model Dev., 16, 289–313,,, 2023
Short summary
Predicting peak daily maximum 8 h ozone and linkages to emissions and meteorology in Southern California using machine learning methods (SoCAB-8HR V1.0)
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029,,, 2022
Short summary
Transfer learning for landslide susceptibility modeling using domain adaptation and case-based reasoning
Zhihao Wang, Jason Goetz, and Alexander Brenning
Geosci. Model Dev., 15, 8765–8784,,, 2022
Short summary
ISMIP-HOM benchmark experiments using Underworld
Till Sachau, Haibin Yang, Justin Lang, Paul D. Bons, and Louis Moresi
Geosci. Model Dev., 15, 8749–8764,,, 2022
Short summary
spyro: a Firedrake-based wave propagation and full-waveform-inversion finite-element solver
Keith J. Roberts, Alexandre Olender, Lucas Franceschini, Robert C. Kirby, Rafael S. Gioria, and Bruno S. Carmo
Geosci. Model Dev., 15, 8639–8667,,, 2022
Short summary

Cited articles

Azzi, M., Johnson, G. M., and Cope, M.: An introduction to the generic reaction set photochemical smog mechanism, Proceedings of the Eleventh International Conference of the Clean Air Society of Australia and New Zealand, 5–10 July 1992, Brisbane, Qld., Australia, 451–462, 1992.
Bocquet, M.: Reconstruction of an atmospheric tracer source using the principle of maximum entropy, I: Theory, Q. J. Roy. Meteor. Soc., 131, 2191–2208,, 2005.
Bocquet, M.: Ensemble Kalman filtering without the intrinsic need for inflation, Nonlin. Processes Geophys., 18, 735–750,, 2011.
Bocquet, M.: Parameter field estimation for atmospheric dispersion: Application to the Chernobyl accident using 4D-Var, Q. J. Roy. Meteor. Soc., 138, 664–681,, 2012.
Bocquet, M. and Sakov, P.: Combining inflation-free and iterative ensemble Kalman filters for strongly nonlinear systems, Nonlin. Processes Geophys., 19, 383–399,, 2012.
Short summary
The focus is on the development of low-order models of atmospheric transport and chemistry and their use for data assimilation purposes. A new low-order coupled chemistry meteorology model is developed. It consists of the Lorenz40-variable model used as a wind field coupled with a simple ozone photochemistry module. Advanced ensemble variational methods are applied to this model to obtain insights on the use of data assimilation with coupled models, in an offline mode or in an online mode.