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Technical Note: Four-dimensional Variational Data Assimilation for Inverse Modelling of Atmospheric Methane Emissions: Method and Comparison with Synthesis Inversion : Volume 8, Issue 3 (18/06/2008)

By Meirink, J. F.

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Book Id: WPLBN0003998149
Format Type: PDF Article :
File Size: Pages 30
Reproduction Date: 2015

Title: Technical Note: Four-dimensional Variational Data Assimilation for Inverse Modelling of Atmospheric Methane Emissions: Method and Comparison with Synthesis Inversion : Volume 8, Issue 3 (18/06/2008)  
Author: Meirink, J. F.
Volume: Vol. 8, Issue 3
Language: English
Subject: Science, Atmospheric, Chemistry
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2008
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

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Krol, M. C., Bergamaschi, P., & Meirink, J. F. (2008). Technical Note: Four-dimensional Variational Data Assimilation for Inverse Modelling of Atmospheric Methane Emissions: Method and Comparison with Synthesis Inversion : Volume 8, Issue 3 (18/06/2008). Retrieved from http://www.ebooklibrary.org/


Description
Description: Institute for Marine and Atmospheric research Utrecht (IMAU), University of Utrecht, Utrecht, The Netherlands. A four-dimensional variational (4D-var) data assimilation system for inverse modelling of atmospheric methane emissions is presented. The system is based on the TM5 atmospheric transport model. It can be used for assimilating large volumes of measurements, in particular satellite observations and quasi-continuous in-situ observations, and at the same time it enables the optimization of a large number of model parameters, specifically grid-scale emission rates. Furthermore, the variational method allows to estimate uncertainties in posterior emissions. Here, the system is applied to optimize monthly methane emissions over a 1-year time window on the basis of surface observations from the NOAA-ESRL network. The results are rigorously compared with an analogous inversion by Bergamaschi et al. (2007), which was based on the traditional synthesis approach. The posterior emissions as well as their uncertainties obtained in both inversions show a high degree of consistency. At the same time we illustrate the advantage of 4D-Var in reducing aggregation errors by optimizing emissions at the grid scale of the transport model. The full potential of the assimilation system is exploited in Meirink et al. (2008), who use satellite observations of column-averaged methane mixing ratios to optimize emissions at high spatial resolution, taking advantage of the zooming capability of the TM5 model.

Summary
Technical Note: Four-dimensional variational data assimilation for inverse modelling of atmospheric methane emissions: method and comparison with synthesis inversion

Excerpt
Baker, D F., Doney, S C., and Schimel, D S.: Variational data assimilation for atmospheric CO2, Tellus, 58B, 359–365, doi:10.1111/j.1600-0889.2006.00218.x, 2006.; Bergamaschi, P., Krol, M., Dentener, F., Vermeulen, A., Meinhardt, F., Graul, R., Ramonet, M., Peters, W., and Dlugokencky, E J.: Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5, Atmos. Chem. Phys., 5, 2431–2460, 2005.; Bergamaschi, P., Meirink, J F., Müller, J F., Körner, S., Heimann, M., Dlugokencky, E J., Kaminski, U., Marcazzan, G., Vecchi, R., Meinhardt, F., Ramonet, M., Sartorius, H., and Zahorowski, W.: Model inter-comparison on transport and chemistry – report on model inter-comparison performed within European Commission FP5 project EVERGREEN (Global satellite observation of greenhouse gas emissions), Sci. and Tech. Res. Ser. EUR 22241 EN, 53 pp., Eur. Comm., DG Joint Res. Cent., Inst. for Environ.\ and Sustainability, Ispra, Italy, 2006.; Bergamaschi, P., Frankenberg, C., Meirink, J F., Krol, M., Dentener, F., Wagner, T., Platt, U., Kaplan, J O., Körner, S., Heimann, M., Dlugokencky, E J., and Goede, A.: Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations, J. Geophys. Res., 112, D02304, doi:10.1029/2006JD007268, 2007.; Bousquet, P., Ciais, P., Miller, J. B., Dlugokencky, E. J., Hauglustaine, D. A., Prigent, C., van der Werf, G. R., Peylin, P., Brunke, E. G., Carouge, C., Langenfelds, R. L., Lathière, J., Papa, F., Ramonet, M., Schmidt, M., Steele, L. P., Tyler, S. C., and White, J.: Contribution of anthropogenic and natural sources to atmospheric methane variability, Nature, 443, 439–443, doi:10.1038/nature05132, 2006.; Buchwitz, M., de~Beek, R., Burrows, J. P., Bovensmann, H., Warneke, T., Notholt, J., Meirink, J. F., Goede, A. P. H., Bergamaschi, P., Körner, S., Heimann, M., and Schulz, A.: Atmospheric methane and carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transport models, Atmos. Chem. Phys., 5, 941–962, 2005.; Buchwitz, M., de~Beek, R., No\el, S., Burrows, J. P., Bovensmann, H., Schneising, O., Khlystova, I., Bruns, M., Bremer, H., Bergamaschi, P., Körner, S., and Heimann, M.: Atmospheric carbon gases retrieved from SCIAMACHY by WFM-DOAS: version 0.5 CO and CH4 and impact of calibration improvements on CO2 retrieval, Atmos. Chem. Phys., 6, 2727–2751, 2006.; Chen, Y.-H. and Prinn, R. G.: Estimation of atmospheric methane emissions between 1996 and 2001 using a three-dimensional global chemical transport model, J. Geophys. Res., 111, D10307, doi:10.1029/2005JD006058, 2006.; Chevallier, F., Fisher, M., Peylin, P., Serrar, S., Bousquet, P., Bréon, F.-M., Chédin, A., and Ciais, P.: Inferring CO2 sources and sinks from satellite observations: Method and application to TOVS data, J. Geophys. Res., 110, D24309, doi:10.1029/2005JD006390, 2005.; Chevallier, F., Bréon, F.-M., and Rayner, P. J.: Contribution of the Orbiting Carbon Observatory to the estimation of CO2 sources and sinks: Theoretical study in a variational data assimilation framework, J. Geophys. Res., 112, D09307, doi:10.1029/2006JD007375, 2007.; Courtier, P., Thépaut, J.-N., and Hollingsworth, A.: A strategy for operational implementation of 4D-Var, using an incremental approach, Q. J. Roy. Meteor. Soc., 120, 1367–1387, 1994.; Dlugokencky, E. J., Steele, L. P., Lang, P. M., and Masarie, K. A.: The growth rate and distribution of atmospheric methane, J. Geophys. Res., 99, 17 021–17 044, doi:10.1029/94JD01245, 1994.; Dlugokencky, E J., Houweling, S., Bruhwiler, L., Masarie, K A., Lang, P M., Miller, J B., and Tans, P P.: Atmospheric methane levels off: Temporary pause or a new steady-state?, Geophys. Res. Let., 30, 1992, doi:1

 

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