Title: Satellite Chartography of Atmospheric Methane from SCIAMACHY Onboard ENVISAT: (II) Evaluation Based on Inverse Model Simulations
Authors: BERGAMASCHI PETERFRANKENBERG C.MEIRINK Jan FokkeKROL M.DENTENER FRANCISCUSWAGNER T.PLATT U.KAPLAN J. O.KOERNER S.HEIMANN M.DLUGOKENCKY EdwardGOEDE Albert
Citation: JOURNAL OF GEOPHYSICAL RESEARCH vol. 112 p. D02304
Publisher: AMER GEOPHYSICAL UNION
Publication Year: 2007
JRC N°: JRC34440
ISSN: 0148-0227
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC34440
DOI: 10.1029/2006JD007268
Type: Articles in Journals
Abstract: We extend the analysis of a global CH4 dataset retrieved from SCIAMACHY [Frankenberg et al., 2006] by making a detailed comparison with inverse model simulations for the year 2003. Using high accuracy CH4 surface measurements from the NOAA global cooperative air sampling network, we perform a global synthesis inversion based on the TM5 model. The optimized global 3D CH4 model fields show a high degree of consistency with the surface observations. The comparison of column averaged mixing ratios over remote continental and oceanic regions shows that major features of the atmospheric CH4 distribution are consistent between SCIAMACHY observations and model simulations. However, the analysis suggests that SCIAMACHY CH4 retrievals may have some bias that depends on latitude and season (up to ~30 ppb), which might be partly related to systematic errors of the retrievals correlating with solar zenith angle. Over source regions, large enhancements of column averaged CH4 mixing ratios are observed and modelled (~50 – 100 ppb enhancement over large scale tropical sources), but model simulations strongly depend on the spatio-temporal distribution of applied emission inventories. Therefore, global satellite observations are very valuable for a comprehensive global validation of assumed emission inventories. We apply a new wetland inventory that is based on new, high-resolution land cover maps, resulting in a significantly different spatial emission distribution, particularly over South America, compared to previously used emission inventories. This new inventory leads to excellent agreement between model simulations and SCIAMACHY data over South America, especially during the first half of the year. However, very high CH4 mixing ratios observed by SCIAMACHY over Venezuela and Columbia between October and December are not reproduced by the model simulations, and their origin remains unexplained. Very large CH4 enhancements are measured by SCIAMACHY over India and South East Asia, largely consistent with model simulations, and to a large extent due to emissions from rice paddies in particular between July and September. Furthermore, we present an initial coupled inversion that simultaneously uses the surface and satellite observations and that allows the inverse system to compensate for the potential systematic bias. The results suggest significantly greater tropical emissions compared to either the a priori estimates or the inversion based on the surface measurements only. Emissions from rice paddies in India and South East Asian are relatively well constrained by the SCIAMACHY data and are slightly reduced by the inversion.
JRC Institute:Institute for Environment and Sustainability

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