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Quantifying the fluxes of carbon dioxide (CO2 ) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and transport model simulations. The applicability of the model's transport parameterization is confirmed using SF6 , CH4 and N2 O simulations for the CARIBIC datasets. The annual amplitude of carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37 ± 0.20 Pg C yr-1 (1 Pg C = 1015 g of carbon in CO2 ) for the years 2007 and 2008. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude over Asia aboard Japan Airlines passenger aircraft.

New automated observation systems for use in passenger aircraft to measure atmospheric carbon dioxide (CO2) and other trace species have been developed and are described in this paper. The Continuous CO2 Measuring Equipment (CME) is composed mainly of a nondispersive infrared analyzer, a datalogger, and two calibration cylinders for in situ CO2 measurements. The Automatic Air Sampling Equipment (ASE), on the other hand, is designed for flask sampling; the instrument, connected to a metal bellows pump, is made up of a specially designed control board and can accommodate 12 flasks. The CME platform can be used to conduct high-frequency measurements of CO2 for obtaining a detailed spatial observation over a wide area, while ASE, despite the limited flight frequency, can provide useful distributions not only of CO2 but also various trace gas species, as well as their isotopic ratios. ASE and CME are installed on the racks in the forward cargo compartment of the aircraft and the air bypass intake is mounted on the air-conditioning duct upstream of the recirculation fan. Both sets of sampling equipment are automatically controlled through input of relevant flight parameters from the aircraft data system. Their deployment in a Boeing 747-400 aircraft was approved by the aviation regulatory agencies in the United States and Japan through issuance of the supplemental type certificate (STC), while the approval for installation of CME in a Boeing 777-200ER was also obtained via STC. First measurement results of CO2 variations obtained by CME and ASE deployed on Japan Airlines (JAL) aircraft are reported herein.

Column-averaged dry air mole fractions of carbon dioxide (XCO2 ) retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations were validated with aircraft measurements by the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the HIAPER Pole-to-Pole Observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. To calculate XCO2 based on aircraft measurements (aircraft-based XCO2 ), tower measurements and model outputs were used for additional information near the surface and above the tropopause, respectively. Before validation, we investigated the impacts of GOSAT SWIR column averaging kernels (CAKs) and the shape of a priori profiles on the aircraft-based XCO2 calculation. The differences between aircraft-based XCO2 with and without the application of GOSAT CAK were evaluated to be less than ±0.4 ppm at most, and less than ±0.1 ppm on average. Therefore, we concluded that the GOSAT CAK produces only a minor effect on the aircraft-based XCO2 calculation in terms of the overall uncertainty of GOSAT XCO2 . We compared GOSAT data retrieved within ±2 or ±5° latitude/longitude boxes centered at each aircraft measurement site to aircraft-based data measured on a GOSAT overpass day. The results indicated that GOSAT XCO2 over land regions agreed with aircraft-based XCO2 , except that the former is biased by -0.68 ppm (-0.99 ppm) with a standard deviation of 2.56 ppm (2.51 ppm), whereas the averages of the differences between the GOSAT XCO2 over ocean and the aircraft-based XCO2 were -1.82 ppm (-2.27 ppm) with a standard deviation of 1.04 ppm (1.79 ppm) for ±2° (±5°) boxes.

This paper documents a global Bayesian variational inversion of CO2 surface fluxes during the period 1988–2008. Weekly fluxes are estimated on a 3.75° × 2.5° (longitude‐latitude) grid throughout the 21 years. The assimilated observations include 128 station records from three large data sets of surface CO2 mixing ratio measurements. A Monte Carlo approach rigorously quantifies the theoretical uncertainty of the inverted fluxes at various space and time scales, which is particularly important for proper interpretation of the inverted fluxes. Fluxes are evaluated indirectly against two independent CO2 vertical profile data sets constructed from aircraft measurements in the boundary layer and in the free troposphere. The skill of the inversion is evaluated by the improvement brought over a simple benchmark flux estimation based on the observed atmospheric growth rate. Our error analysis indicates that the carbon budget from the inversion should be more accurate than the a priori carbon budget by 20% to 60% for terrestrial fluxes aggregated at the scale of subcontinental regions in the Northern Hemisphere and over a year, but the inversion cannot clearly distinguish between the regional carbon budgets within a continent. On the basis of the independent observations, the inversion is seen to improve the fluxes compared to the benchmark: the atmospheric simulation of CO2 with the Bayesian inversion method is better by about 1 ppm than the benchmark in the free troposphere, despite possible systematic transport errors. The inversion achieves this improvement by changing the regional fluxes over land at the seasonal and at the interannual time scales.

Current knowledge about the European terrestrial biospheric carbon sink, from the Atlantic to the Urals, relies upon bottom-up inventory and surface flux inverse model estimates (e.g. 0.27±0.16 GtC a−1 for 2000–2005 (Schulze et al., 2009), 0.17±0.44 GtC a−1 for 2001–2007 (Peters et al., 2010), 0.45±0.40 GtC a−1 for 2010 (Chevallier et al., 2014), 0.40±0.42 GtC a−1 for 2001–2004 (Peylin et al., 2013)). Inverse models assimilate in situ CO2 atmospheric concentrations measured by surface-based air sampling networks. The intrinsic sparseness of these networks is one reason for the relatively large flux uncertainties (Peters et al., 2010; Bruhwiler et al., 2011). Satellite-based CO2 measurements have the potential to reduce these uncertainties (Miller et al., 2007; Chevallier et al., 2007). Global inversion experiments using independent models and independent GOSAT satellite data products consistently derived a considerably larger European sink (1.0–1.3 GtC a−1 for 09/2009–08/2010 (Basu et al., 2013), 1.2–1.8 GtC a−1 in 2010 (Chevallier et al., 2014)). However, these results have been considered unrealistic due to potential retrieval biases and/or transport errors (Chevallier et al., 2014) or have not been discussed at all (Basu et al., 2013; Takagi et al., 2014). Our analysis comprises a regional inversion approach using STILT (Gerbig et al., 2003; Lin et al., 2003) short-range (days) particle dispersion modelling, rendering it insensitive to large-scale retrieval biases and less sensitive to long-range transport errors. We show that the satellite-derived European terrestrial carbon sink is indeed much larger (1.02±0.30 GtC a−1 in 2010) than previously expected. This is qualitatively consistent among an ensemble of five different inversion set-ups and five independent satellite retrievals (BESD (Reuter et al., 2011) 2003–2010, ACOS (O’Dell et al., 2012) 2010, UoL-FP (Cogan et al., 2012) 2010, RemoTeC (Butz et al., 2011) 2010, and NIES (Yoshida et al., 2013) 2010) using data from two different instruments (SCIAMACHY (Bovensmann et al., 1999) and GOSAT (Kuze et al., 2009)). The difference to in situ based inversions (Peylin et al., 2013), whilst large with respect to the mean reported European carbon sink (0.4 GtC a−1 for 2001–2004), is similar in magnitude to the reported uncertainty (0.42 GtC a−1). The highest gain in information is obtained during the growing season when satellite observation conditions are advantageous, a priori uncertainties are largest, and the surface sink maximises; during the dormant season, the results are dominated by the a priori. Our results provide evidence that the current understanding of the European carbon sink has to be revisited.

We evaluate the GEOS-Chem atmospheric transport model (v8-02-01) of CO2 over 2003-2006, driven by GEOS-4 and GEOS-5 meteorology from the NASA Goddard Global Modeling and Assimilation Office, using surface, aircraft and space-borne concentration measurements of CO2 . We use an established ensemble Kalman Filter to estimate a posteriori biospheric+biomass burning (BS + BB) and oceanic (OC) CO2 fluxes from 22 geographical regions, following the TransCom-3 protocol, using boundary layer CO2 data from a subset of GLOBALVIEW surface sites. Global annual net BS + BB + OC CO2 fluxes over 2004-2006 for GEOS-4 (GEOS-5) meteorology are -4.4 ± 0.9 (-4.2 ± 0.9), -3.9 ± 0.9 (-4.5 ± 0.9), and -5.2 ± 0.9 (-4.9 ± 0.9) PgC yr-1 , respectively. After taking into account anthropogenic fossil fuel and bio-fuel emissions, the global annual net CO2 emissions for 2004-2006 are estimated to be 4.0 ± 0.9 (4.2 ± 0.9), 4.8 ± 0.9 (4.2 ± 0.9), and 3.8 ± 0.9 (4.1 ± 0.9) PgC yr-1 , respectively. The estimated 3-yr total net emission for GEOS-4 (GEOS-5) meteorology is equal to 12.5 (12.4) PgC, agreeing with other recent top-down estimates (12-13 PgC). The regional a posteriori fluxes are broadly consistent in the sign and magnitude of the TransCom-3 study for 1992-1996, but we find larger net sinks over northern and southern continents. We find large departures from our a priori over Europe during summer 2003, over temperate Eurasia during 2004, and over North America during 2005, reflecting an incomplete description of terrestrial carbon dynamics. We find GEOS-4 (GEOS-5) a posteriori CO2 concentrations reproduce the observed surface trend of 1.91-2.43 ppm yr-1 (parts per million per year), depending on latitude, within 0.15 ppm yr-1 (0.2 ppm yr-1 ) and the seasonal cycle within 0.2 ppm (0.2 ppm) at all latitudes. We find the a posteriori model reproduces the aircraft vertical profile measurements of CO2 over North America and Siberia generally within 1.5 ppm in the free and upper troposphere but can be biased by up to 4-5 ppm in the boundary layer at the start and end of the growing season. The model has a small negative bias in the free troposphere CO2 trend (1.95-2.19 ppm yr-1 ) compared to AIRS data which has a trend of 2.21-2.63 ppm yr-1 during 2004-2006, consistent with surface data. Model CO2 concentrations in the upper troposphere, evaluated using CONTRAIL (Comprehensive Observation Network for TRace gases by AIrLiner) aircraft measurements, reproduce the magnitude and phase of the seasonal cycle of CO2 in both hemispheres. We generally find that the GEOS meteorology reproduces much of the observed tropospheric CO2 variability, suggesting that these meteorological fields will help make significant progress in understanding carbon fluxes as more data become available.

Current estimates of the terrestrial carbon fluxes in Asia show large uncertainties particularly in the boreal and mid-latitudes and in China. In this paper, we present an updated carbon flux estimate for Asia (\"Asia\" refers to lands as far west as the Urals and is divided into boreal Eurasia, temperate Eurasia and tropical Asia based on TransCom regions) by introducing aircraft CO2 measurements from the CONTRAIL (Comprehensive Observation Network for Trace gases by Airline) program into an inversion modeling system based on the CarbonTracker framework. We estimated the averaged annual total Asian terrestrial land CO2 sink was about -1.56 Pg C yr-1 over the period 2006–2010, which offsets about one-third of the fossil fuel emission from Asia (+4.15 Pg C yr-1). The uncertainty of the terrestrial uptake estimate was derived from a set of sensitivity tests and ranged from -1.07 to -1.80 Pg C yr-1, comparable to the formal Gaussian error of ±1.18 Pg C yr-1 (1-sigma). The largest sink was found in forests, predominantly in coniferous forests (-0.64 ± 0.70 Pg C yr-1) and mixed forests (-0.14 ± 0.27 Pg C yr-1); and the second and third large carbon sinks were found in grass/shrub lands and croplands, accounting for -0.44 ± 0.48 Pg C yr-1 and -0.20 ± 0.48 Pg C yr-1, respectively. The carbon fluxes per ecosystem type have large a priori Gaussian uncertainties, and the reduction of uncertainty based on assimilation of sparse observations over Asia is modest (8.7–25.5%) for most individual ecosystems. The ecosystem flux adjustments follow the detailed a priori spatial patterns by design, which further increases the reliance on the a priori biosphere exchange model. The peak-to-peak amplitude of inter-annual variability (IAV) was 0.57 Pg C yr-1 ranging from -1.71 Pg C yr-1 to -2.28 Pg C yr-1. The IAV analysis reveals that the Asian CO2 sink was sensitive to climate variations, with the lowest uptake in 2010 concurrent with a summer flood and autumn drought and the largest CO2 sink in 2009 owing to favorable temperature and plentiful precipitation conditions. We also found the inclusion of the CONTRAIL data in the inversion modeling system reduced the uncertainty by 11% over the whole Asian region, with a large reduction in the southeast of boreal Eurasia, southeast of temperate Eurasia and most tropical Asian areas.

We present carbon dioxide (CO2 ) estimates from the Tropospheric Emission Spectrometer (TES) on the EOS-Aura satellite launched in 2004. For observations between 40° S and 45° N, we find about 1 degree of freedom with peak sensitivity at 511 hPa. The estimated error is ~10 ppm for a single target and 1.3-2.3 ppm for monthly averages on spatial scales of 20°×30°. Monthly spatially-averaged TES data from 2005-2008 processed with a uniform initial guess and prior are compared to CONTRAIL aircraft data over the Pacific ocean, aircraft data at the Southern Great Plains (SGP) ARM site in the southern US, and the Mauna Loa and Samoa surface stations. Comparisons to Mauna Loa data show a correlation of 0.92, a standard deviation of 1.3 ppm, a predicted error of 1.2 ppm, and a ~2% low bias, which is subsequently corrected. Comparisons to SGP aircraft data over land show a correlation of 0.67 and a standard deviation of 2.3 ppm. TES data between 40° S and 45° N for 2006-2007 are compared to surface flask data, GLOBALVIEW, the Atmospheric Infrared Sounder (AIRS), and CarbonTracker. Comparison to GLOBALVIEW-CO2 ocean surface sites shows a correlation of 0.60 which drops when TES is offset in latitude, longitude, or time. At these same locations, TES shows a 0.62 and 0.67 correlation to CarbonTracker at the surface and 5 km, respectively. We also conducted an observing system simulation experiment to assess the potential utility of the TES data for inverse modeling of CO2 fluxes. We find that if biases in the data and model are well characterized, the averaged data have the potential to provide sufficient information to significantly reduce uncertainty on annual estimates of regional CO2 sources and sinks. Averaged pseudo-data at 10°×10° reduced uncertainty in flux estimates by as much as 70% for some tropical regions.

Since July 2007, monthly averages of mid-tropospheric methane have been retrieved in the tropics over land and sea, by day and night, from IASI onboard MetOp-A, yielding a complete view of the geographical distribution, seasonality and long-term tendency of methane in the mid-troposphere. Retrieved methane displays a clear seasonal cycle of ~25 ppbv in the northern tropics, with a maximum in November and a minimum in April–May, a more complex cycle of ~15 ppbv in the southern tropics, and a south-to-north latitudinal variation of ~30 ppbv – in good agreement with regular aircraft measurements of the CONTRAIL program. Comparisons with CARIBIC aircraft measurements made at ~11 km yield an averaged difference between collocated IASI estimates and CARIBIC measurements of 7.2 ppbv with a standard deviation of 13.1 ppbv. Comparisons with aircraft measurements made above 6 km during five HIPPO campaigns give an averaged difference between collocated IASI estimates and HIPPO measurements of 5.1 ppbv with a standard deviation of 16.3 ppbv. These comparisons show that IASI captures well the evolution of mid-tropospheric methane. In particular, in 2007 and 2008, IASI shows an increase of mid-tropospheric methane in the tropical region of 9.5 ± 2.8 and 6.3 ± 1.7 ppbv yr−1, respectively – in excellent agreement with the rate of increase measured at the surface after almost a decade of near-zero growth. IASI also indicates a slowing down of this increase in the following years to ~2 ppbv yr−1, with the highest increase in 2010. Assuming that the recent evolution of methane is mostly due to an increase in surface emissions, IASI might indicate a decrease in tropical wetland emissions for the period 2009–2011 compared to 2007–2008, in agreement with decreasing tropical precipitation over this period, together with an increase in biomass burning emissions in 2010 in the southern tropics.

The Total Carbon Column Observing Network (TCCON) produces precise measurements of the column average dry-air mole fractions of CO2, CO, CH4, N2O and H2O at a variety of sites worldwide. These observations rely on spectroscopic parameters that are not known with sufficient accuracy to compute total columns that can be used in combination with in situ measurements. The TCCON must therefore be calibrated to World Meteorological Organization (WMO) in situ trace gas measurement scales. We present a calibration of TCCON data using WMO-scale instrumentation aboard aircraft that measured profiles over four TCCON stations during 2008 and 2009. These calibrations are compared with similar observations made in 2004 and 2006. The results indicate that a single, global calibration factor for each gas accurately captures the TCCON total column data within error.