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Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification

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Abstract

Satellite retrievals of atmospheric composition provide a wealth of data on a global scale. These complement results from atmospheric chemistry-transport models (CTMs), and can be combined using data assimilation. We present two assimilation schemes coupled to the Danish Eulerian Hemispheric Model (DEHM), a three-dimensional, off-line CTM with full photochemistry: a variant on the ensemble Kalman filter and the three-dimensional variational scheme. The aim of this paper is to describe the two schemes and present an initial assessment of their impacts on model skill. Retrievals of multiple atmospheric trace gases are assimilated, namely: NO2 tropospheric column densities, CH4 total column densities, and partial column concentrations of O3, CO and CH4; these data are retrieved from four satellite sensors. Data for each species are assimilated independently of one another, and other species are only adjusted indirectly via the model’s chemistry and dynamics. Assimilation results are compared with measurements from surface monitoring stations and other satellite retrievals, and preliminary validation results are presented.Reference simulations (without assimilation) grossly underestimate surface CO concentrations, and both assimilation schemes eliminate this large and systematic model bias. The assimilation improves the spatial correlation of modelled CO with surface observations, and improves the spatial correlation between forecasts and retrievals for CO, NO2 and O3. Results for CH4 show a loss of skill due to a mismatch in model bias between two assimilated CH4 data-sets. Finally, we discuss differences in methodology and results between this paper and a recent study on multi-species chemical data assimilation. Joint optimisation of initial conditions and emission rates offers a promising direction for improving modelled boundary-layer concentrations.

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Notes

  1. Available at http://dss.ucar.edu

  2. http://macc-raq.gmes-atmosphere.eu/

  3. For details, see http://www.gmes-atmosphere.eu/about/project_structure/global/g_idas/g_idas_2/log_fbov/

  4. https://www2.acd.ucar.edu/mopitt

  5. www.eea.europa.eu/themes/air/airbase

  6. http://www.wmo.int/pages/prog/arep/gaw/measurements.html

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Acknowledgments

This study was funded by a program grant from the Danish Council for Technology and Innovation: Effects of climate changes on ecosystems – a global comparative analysis (ECOGLOBE). The final revisions to the manuscript were funded by a McKenzie Postdoctoral Fellowship at the University of Melbourne. P. Rayner is in receipt of an Australian Professorial Fellowship (DP1096309). The authors thank the institutions providing measurements, modelling and retrieval data: NASA, TEMIS, AirBase, NCEP, GAW, NCAR and IUP/IFE at the University of Bremen. Henk Eskes of KNMI provided useful feedback on a draft of the manuscript. We thank two anonymous reviewers for a range of constructive criticism on the text.

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  1. Department of Environmental Science, Aarhus University, 4000, Roskilde, Denmark

    Jeremy D. Silver, Jesper H. Christensen & Jørgen Brandt

  2. Swedish Meteorological and Hydrological Institute, 60176, Norrköping, Sweden

    Michael Kahnert & Lennart Robertson

  3. School of Earth Sciences, University of Melbourne, 3010, VIC, Melbourne, Australia

    Jeremy D. Silver & Peter J. Rayner

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Silver, J.D., Christensen, J.H., Kahnert, M. et al. Multi-species chemical data assimilation with the Danish Eulerian hemispheric model: system description and verification. J Atmos Chem 73, 261–302 (2016). https://doi.org/10.1007/s10874-015-9326-0

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