Articles | Volume 9, issue 8
https://doi.org/10.5194/gmd-9-2893-2016
https://doi.org/10.5194/gmd-9-2893-2016
Methods for assessment of models
 | 
26 Aug 2016
Methods for assessment of models |  | 26 Aug 2016

EnKF and 4D-Var data assimilation with chemical transport model BASCOE (version 05.06)

Sergey Skachko, Richard Ménard, Quentin Errera, Yves Christophe, and Simon Chabrillat

Related authors

Weakly coupled atmosphere–ocean data assimilation in the Canadian global prediction system (v1)
Sergey Skachko, Mark Buehner, Stéphane Laroche, Ervig Lapalme, Gregory Smith, François Roy, Dorina Surcel-Colan, Jean-Marc Bélanger, and Louis Garand
Geosci. Model Dev., 12, 5097–5112, https://doi.org/10.5194/gmd-12-5097-2019,https://doi.org/10.5194/gmd-12-5097-2019, 2019
Short summary
Technical note: Reanalysis of Aura MLS chemical observations
Quentin Errera, Simon Chabrillat, Yves Christophe, Jonas Debosscher, Daan Hubert, William Lahoz, Michelle L. Santee, Masato Shiotani, Sergey Skachko, Thomas von Clarmann, and Kaley Walker
Atmos. Chem. Phys., 19, 13647–13679, https://doi.org/10.5194/acp-19-13647-2019,https://doi.org/10.5194/acp-19-13647-2019, 2019
Short summary
Harmonisation and diagnostics of MIPAS ESA CH4 and N2O profiles using data assimilation
Quentin Errera, Simone Ceccherini, Yves Christophe, Simon Chabrillat, Michaela I. Hegglin, Alyn Lambert, Richard Ménard, Piera Raspollini, Sergey Skachko, Michiel van Weele, and Kaley A. Walker
Atmos. Meas. Tech., 9, 5895–5909, https://doi.org/10.5194/amt-9-5895-2016,https://doi.org/10.5194/amt-9-5895-2016, 2016
Short summary
Comparison of the ensemble Kalman filter and 4D-Var assimilation methods using a stratospheric tracer transport model
S. Skachko, Q. Errera, R. Ménard, Y. Christophe, and S. Chabrillat
Geosci. Model Dev., 7, 1451–1465, https://doi.org/10.5194/gmd-7-1451-2014,https://doi.org/10.5194/gmd-7-1451-2014, 2014

Related subject area

Numerical methods
Potential-based thermodynamics with consistent conservative cascade transport for implicit large eddy simulation: PTerodaC3TILES version 1.0
John Thuburn
Geosci. Model Dev., 18, 3331–3357, https://doi.org/10.5194/gmd-18-3331-2025,https://doi.org/10.5194/gmd-18-3331-2025, 2025
Short summary
Positive matrix factorization of large real-time atmospheric mass spectrometry datasets using error-weighted randomized hierarchical alternating least squares
Benjamin C. Sapper, Sean Youn, Daven K. Henze, Manjula Canagaratna, Harald Stark, and Jose L. Jimenez
Geosci. Model Dev., 18, 2891–2919, https://doi.org/10.5194/gmd-18-2891-2025,https://doi.org/10.5194/gmd-18-2891-2025, 2025
Short summary
CLAQC v1.0 – Country Level Air Quality Calculator: an empirical modeling approach
Stefania Renna, Francesco Granella, Lara Aleluia Reis, and Paulina Schulz-Antipa
Geosci. Model Dev., 18, 2373–2408, https://doi.org/10.5194/gmd-18-2373-2025,https://doi.org/10.5194/gmd-18-2373-2025, 2025
Short summary
Hydro-geomorphological modelling of leaky wooden dam efficacy from reach to catchment scale with CAESAR-Lisflood 1.9j
Joshua M. Wolstenholme, Christopher J. Skinner, David Milan, Robert E. Thomas, and Daniel R. Parsons
Geosci. Model Dev., 18, 1395–1411, https://doi.org/10.5194/gmd-18-1395-2025,https://doi.org/10.5194/gmd-18-1395-2025, 2025
Short summary
Stabilized two-phase material point method for hydromechanical coupling problems in solid-fluid porous media
Xiong Tang, Wei Liu, Siming He, Lei Zhu, Michel Jaboyedoff, Huanhuan Zhang, Yuqing Sun, and Zenan Huo
EGUsphere, https://doi.org/10.5194/egusphere-2025-707,https://doi.org/10.5194/egusphere-2025-707, 2025
Short summary

Cited articles

Anderson, E. and Järvinen, H.: Variational quality control, Q. J. Roy. Meteor. Soc., 125, 697–722, https://doi.org/10.1002/qj.49712555416, 1999.
Anderson, J. L.: Localization and Sampling Error Correction in Ensemble Kalman Filter Data Assimilation, Mon. Weather Rev., 140, 2359–2371, https://doi.org/10.1175/MWR-D-11-00013.1, 2012.
Bocquet, M., Elbern, H., Eskes, H., Hirtl, M., vZabkar, R., Carmichael, G. R., Flemming, J., Inness, A., Pagowski, M., Pérez Camaño, J. L., Saide, P. E., San Jose, R., Sofiev, M., Vira, J., Baklanov, A., Carnevale, C., Grell, G., and Seigneur, C.: Data assimilation in atmospheric chemistry models: current status and future prospects for coupled chemistry meteorology models, Atmos. Chem. Phys., 15, 5325–5358, https://doi.org/10.5194/acp-15-5325-2015, 2015.
Brasseur, G. and Solomon, S.: Aeronomy of the middle atmosphere: chemistry and physics of the stratosphere and mesosphere, Springer Netherlands, Dordrecht, Reidel, https://doi.org/10.1007/1-4020-3824-0, 1986, 2005.
Download
Short summary
In the present work, we performed a comparison of two broadly used data assimilation algorithms, 4D-Var and EnKF, applied to a state-of-the-art atmospheric chemistry transport model. The comparison is carried out using carefully calibrated error statistics. The paper discusses the advantages and disadvantages of each method applied to real-life conditions of a numerical atmospheric chemistry data assimilation.
Share