New technique to analyse global distributions of CO₂ concentrations and fluxes from non-processed observational data

Abstract

We have developed a new observational screening technique for inverse model. This technique was applied to our transport models with re‐analysed meteorological data and the inverse model to estimate the global distribution of CO2 concentrations and fluxes. During the 1990s, we estimated a total CO2 uptake by the biosphere of 1.4–1.5 PgC yr−1 and a total CO2 uptake by the oceans of 1.7–1.8 PgC yr−1. The uncertainty of global CO2 flux estimation is about 0.3 PgC yr−1. We also obtained monthly surface CO2 concentrations in the marine boundary layer to precisions of 0.5–1.0 ppm. To utilize non‐processed (statistical monthly mean) observational data in our analysis, we developed a quality control procedure for such observational data including a repetition of inversion. This technique is suitable for other inversion setups. Observational data by ships were placed into grids and used in our analysis to add to the available data from fixed stations. The estimated global distributions are updated and extended every year.

Estimating Asian terrestrial carbon fluxes from CONTRAIL aircraft and surface CO<sub>2</sub> observations for the period 2006–2010

“…Knowledge of the terrestrial carbon sources and sinks is critically important for understanding and projecting the future atmospheric CO 2 levels and climate change. The global terrestrial ecosystems absorbed about 1-3 Pg carbon every year during the 2000s, with obvious interannual variations, offsetting 10-40 % of the anthropogenic emissions (Le Quéré et al, 2009;Maki et al, 2010;Saeki et al, 2013). However, estimates of the terrestrial carbon balance vary considerably when considering continental scales and smaller, as well as when estimating the CO 2 seasonal and inter-annual variability (Houghton, 2007;Peylin et al, 2013).…”

Nested atmospheric inversion for the terrestrial carbon sources and sinks in China

“…The optimization of the prior fluxes is made according to the difference between observed and simulated CO 2 concentrations. With this method, many studies have been conducted to estimate the global terrestrial carbon fluxes (e.g., Enting and Mansbridge, 1989;Rayner et al, 1999a;Ciais, et al, 2000;Gurney et al, 2002;Law et al, 2003;Rödenbeck et al, 2005;Patra et al, 2005a;Rayner et al, 2008;Maki et al, 2010), and most of these studies focused on the spatial pattern of the carbon sources and sinks and the inter-annual variations. In recent years, one of the research directions of atmospheric inversion is to estimate fluxes in finer spatial resolutions (e.g., Gerbig et al, 2003;Peylin et al, 2005;Peters, et al, 2007;Schuh et al, 2010).…”

The Impact of Ground-Based Observations on the Inverse Technique of Aeolian Dust Aerosol

“…Second, we should introduce as much quality-controlled observation data as possible, especially vertically resolved observation data (Sugimoto et al 2010). Finally, we should refine our inverse model system in regard to quality control of the observational platform (Maki et al 2010), prior information about observations and dust fluxes. In particular, to obtain a benefit of the inverse model over former models, we should set a constant flux where the dust model could not emit dust due to surface conditions (snow, soil wetness, and so on) to overcome the second issue that we have shown in the introduction.…”