Spatio-temporal statistical analysis of the carbon footprint of the terrestrial vegetation

The study of sources and sinks of carbon dioxide is of interest in many research disciplines and in political negotiations on climate change mitigations. The most important source/sink for the global carbon dioxide balance is the global vegetation, which acts as a sink during the photosynthesis and at the same time as a source of CO2 as plants use the produced chemical energy for building up biomass and for cell respiration. In natural science, the Gross Primary Productivity (GPP) of the terrestrial vegetation, in effect the produced chemical energy from photosynthesis has been analyzed frequently. However the net effect of vegetation on CO2 emissions (Net Primary Productivity (NPP)) on a global spatial scale and on an intra-annual time basis has not yet been well discovered. This study addresses this problem from a spatio-temporal statistical point of view. We make use of remotely sensed observations of the vertical profile of CO2 concentrations obtained from the Greenhouse Gases Observing Satellite (GOSAT) and observations of the GPP derived from data of the MODIS satellite mission on the primary production of vegetation. A space-time linear mixed effects model was fitted to the data, which is able to capture spatial and temporal auto-correlation of ground CO2 concentrations and as well the spatial and temporal cross-correlation between CO2 and the GPP through latent spatial and temporal random processes. In that way we were able to obtain spatio-temporal predictions of the influence of vegetation on surface CO2 concentrations and discover the source/sink activity of vegetation on a global spatial scale with 1◦ × 1◦ resolution and in a nearly weekly time resolution.