A North-South gradient of CDIAC CO2 Mixing Ratios compared with Data from Atmospheric Remote Sensing of CO2

Considering Arctic-Antarctic (North-South) carbon dioxide (CO₂) dynamics over time, one can see a ripple of a Vegetation Signal [VRi] on an increasing baseline trend [BTr]. The VRi gradually disappears when moving southwards (towards the Antarctic). It is observed in CDIAC data that the [VRi], superposed on an increasing CO₂ baseline trend increase disappears when traveling southwards. How so?

The observation is intuitively obvious, since the Northern hemisphere contains approximately 68% of the Earth's landmass and is home to about 90% of the global population. In contrast the Southern hemisphere is left with 32% landmass and a tiny 10% of the global population. Due to these differences in landmass and population, the North South dynamics of carbon dioxide mixing ratios is primarily determined by the differences in vegetation density, human population density, and atmospheric circulation patterns, including a variety of factors of less impact on atmospheric CO₂ dynamics.

More sources of CO₂ in the Northern hemisphere determine the global CO₂ trend line over time on the condition that the atmosphere is well mixed in a short time interval. The Intertropical Convergence Zone (ITCZ)  acts as a barrier to the mixing of air masses from the Northern and Southern Hemispheres. This makes CO₂ dynamics in each hemisphere more distinct in a short-term time frame (seasons). The [BTr] is determined more by long-term CO₂ emissions from anthropogenic origin (years).

When comparing global trends in CO₂ mixing ratios obtained with remote sensing estimates by NASA's Orbiting Carbon Observatory (OCO) with measurements from the CDIAC CO₂ monitoring stations over several years, the separation of [VRi] from [BTr] leads to interesting results. 

Ensuring the data are consistent, one is required to remove outliers and perform gap-filling if necessary. Subsequently one has to decompose the CDIAC CO₂ time series into its [VRi] and [BTr] components. This can be done using techniques such as seasonal numerical decomposition of time series. The seasonal component [VRi] represents a regular annual cycle driven essentially by vegetation photosynthesis and respiration. The increasing trend component [BTr], reflects the more long-term changes in CO₂ mixing ratio’s driven by anthropogenic and other sources of CO₂ emissions. A harmonic model is fitted to the deseasonalized and detrended data to quantify the seasonal amplitude and phase of [VRi]. The seasonal amplitude represents the strength of [VRi] due to carbon fixation, while the phase indicates the timing of maximum uptake and release of CO₂, depending on the latitude in the Northern and Southern hemispheres. To validate atmospheric CO₂ dynamics of remotely sensed CO₂ mixing ratios, the CDIAC measured CO₂ mixing ratios are used in a comparison of both types of CO₂ data. Only then, factors, such as climate, land cover and human population densities, can be understood better. It may allow to model the forcing processes determining RS observed and measured trends and variations of CO₂ mixing ratios, and their impact on changes in climate.