For CH4, already improved emission estimates have been obtained on the basis of SCIAMACHY data. An atmospheric general circulation model, in which the current knowledge of global sources is implemented, is used to model the worldwide CH4 distribution. The source terms in this model can be adjusted in magnitude, region and timing until the modelled distribution provides the best match with SCIAMACHY observations, thus obtaining inverted source estimates using satellite data (Meirink et al. 2008). Recent inversion studies (Bergamaschi et al. 2009) result in significant changes in the spatial patterns of emissions and their seasonality compared to the bottom-up inventories. Large CH4 emissions are attributed to various wetland regions in tropical South America and Africa, seasonally varying and opposite in phase with CH4 emissions from biomass burning. As obvious in fig. 3-2, India, China and South East Asia are characterised by pronounced emissions from rice paddies peaking in the third quarter of the year, in addition to further anthropogenic emissions throughout the year.
Water Vapour – H2O
Water is the key to the Earth’s climate system. As vapour, it is the strongest greenhouse gas and as precipitation, it is the essential ingredient for making our planet habitable. Water vapour is a highly variable component of the atmosphere with direct anthropogenic impact on its amount being usually negligible. Its contribution may reach up to 4% of the atmospheric volume in the tropics and amounts to less than 1% in dry air conditions. Due to the relation between temperature and humidity, water vapour acts as a positive feedback to anthropogenic radiative forcing and is thereby indirectly affected by human activity.
In contrast to microwave instruments, SCIAMACHY water vapour data is available over both land and ocean down to the surface for at least partly cloud-free scenes. Because of their independence from other in situ or remote sensing measurements, SCIAMACHY water vapour columns provide a new important global dataset (Noël et al. 2004, Schrijver et al. 2009). A combination of SCIAMACHY water vapour with corresponding data derived from GOME and follow-on instruments allows the study of water vapour long-term trends now already spanning more than 15 years, with the potential of extension until 2020 when GOME-2 data on METOP is considered.
Using linear and non-linear methods from time series analysis and standard statistics, the trends of H2O columns and their errors have been derived from GOME and SCIAMACHY for the years 1996 to 2007 (Mieruch et al. 2008). The trends clearly show elevated water vapour levels in years of strong El-Nino activity. How these trends are distributed on a global scale is further demonstrated in Fig. 3-3. Increasing long-term trends in water vapour have been observed for Greenland, Eastern Europe, Siberia and Oceania, whereas decreasing trends occur for the northwest US, Central America, Amazonia, Central Africa and the Arabian Peninsula. (fig. 3-3)