A global network of ground-based Fourier transform spectrometers has been founded to remotely measure column abundances of CO_2, CO, CH_4, N_(2)O and other molecules that absorb in the near-infrared. These measurements are directly comparable with the near-infrared total column measurements from space-based instruments. With stringent requirements on the instrumentation, acquisition procedures, data processing and calibration, the Total Carbon Column Observing Network (TCCON) achieves an
accuracy and precision in total column measurements that is unprecedented for remotesensing observations (better than 0.25% for CO_2). This has enabled carbon-cycle science
investigations using the TCCON dataset, and allows the TCCON to provide a link between satellite measurements and the extensive ground-based in situ network.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2010.0240

The Total Carbon Column Observing Network

. We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in XCO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the observed correlation between free-tropospheric potential temperature and XCO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed.

/pdf/a-method-for-evaluating-bias-in-global-measurements-of-co-2-1fx35tcthj.pdf

A method for evaluating bias in global measurements of CO 2 total columns from space

NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X_(CO_2), in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X_(CO2) from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X_(CO_2) retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X_(CO_2) data quality throughout its mission.

/pdf/comparisons-of-the-orbiting-carbon-observatory-2-oco-2-x-co-3tfisu35qw.pdf

Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X CO 2 measurements with TCCON

. Here, we report preliminary estimates of the column averaged carbon dioxide (CO2) dry air mole fraction, XCO2, retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global XCO2 field, including its variation with latitude and season. However, low yields of retrieved XCO2 over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT XCO2 retrievals with XCO2 estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2% (7–8 parts per million, ppm, with respect to dry air) XCO2 bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global XCO2 bias is associated with a systematic, 1% overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT XCO2 retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O2 and CO2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in XCO2 on global scales as well as a ~30% reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit.

/pdf/the-acos-co-2-retrieval-algorithm-part-ii-global-x-co-2-data-2cszjoa6b1.pdf

The ACOS CO 2 retrieval algorithm – Part II: Global X CO 2 data characterization

. We use 2009–2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2–42.7 Tg a−1, as compared to 24.9–27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0–44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern–central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29–44 % of US anthropogenic methane emissions to livestock, 22–31 % to oil/gas, 20 % to landfills/wastewater, and 11–15 % to coal. Wetlands contribute an additional 9.0–10.1 Tg a−1.

/pdf/estimating-global-and-north-american-methane-emissions-with-29ea1o6fxs.pdf

Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

The Total Carbon Column Observing Network (TCCON) is a ground-based network of Fourier Transform Spectrometer (FTS) sites around the globe, where the column abundances of CO2, CH4, N2O, CO and O2 are measured. CO2 is constrained with a precision better than 0.25 % (1- ). To achieve a similarly high accuracy, calibration to World Meteorological Organization (WMO) standards is required. This paper introduces the first aircraft calibration campaign of five European TCCON sites and a mobile FTS instrument. A series of WMO standards in-situ profiles were obtained over European TCCON sites via aircraft and compared with retrievals of CO2 column amounts from the TCCON instru- ments. The results of the campaign show that the FTS mea- surements are consistently biased 1.1 %± 0.2 % low with re- spect to WMO standards, in agreement with previous TC- CON calibration campaigns. The standard a priori profile for the TCCON FTS retrievals is shown to not add a bias. The same calibration factor is generated using aircraft pro- files as a priori and with the TCCON standard a priori. With a calibration to WMO standards, the highly precise TCCON CO2 measurements of total column concentrations provide a

/pdf/calibration-of-tccon-column-averaged-co2-the-first-aircraft-2g6rkru14n.pdf

Calibration of TCCON column-averaged CO2: the first aircraft campaign over European TCCON sites

Total Column Carbon Observing Network (TCCON) Collection: GGG2014 Site: Bialystok

. The in situ boundary layer measurement site in Bialystok (Poland) has been upgraded with a fully automated observatory for total greenhouse gas column measurements. The automated Fourier Transform Spectrometer (FTS) complements the on-site in situ facilities and FTS solar absorption measurements have been recorded nearly continuously in clear and partially cloudy conditions since March 2009. Here, the FTS measurements are compared with the collocated tall tower data. Additionally, simulations of the Jena CO2 inversion model are evaluated with the Bialystok measurement facilities. The simulated seasonal CO2 cycle is slightly overestimated by a mean difference of 1.2 ppm ± 0.9 ppm (1σ) in comparison with the FTS measurements. CO2 concentrations at the surface, measured at the tall tower (5 m, 90 m, 300 m), are slightly underestimated by −1.5 ppm, −1.6 ppm, and −0.7 ppm respectively during the day and by −9.1 ppm, −5.9 ppm, and −1.3 ppm during the night. The comparison of the simulated CO2 profiles with low aircraft profiles shows a slight overestimation of the lower troposphere (by up to 1 ppm) and an underestimation in near-surface heights until 800 m (by up to 2.5 ppm). In an appendix the automated FTS observatory, including the hardware components and the automation software, is described in its basics.

/pdf/automated-ground-based-remote-sensing-measurements-of-2beu9vhr2c.pdf

Automated ground-based remote sensing measurements of greenhouse gases at the Białystok site in comparison with collocated in situ measurements and model data

. Since 2002 in situ airborne measurements of atmospheric CO2 mixing ratios have been performed regularly aboard a rental aircraft near Bialystok (53°08´ N, 23°09´ E), a city in northeastern Poland. Since August 2008, the in situ CO2 measurements have been made by a modified commercially available and fully automated non-dispersive infrared (NDIR) analyzer system. The response of the analyzer has been characterized and the CO2 mixing ratio stability of the associated calibration system has been fully tested, which results in an optimal calibration strategy and allows for an accuracy of the CO2 measurements within 0.2 ppm. Besides the in situ measurements, air samples have been collected in glass flasks and analyzed in the laboratory for CO2 and other trace gases. To validate the in situ CO2 measurements against reliable discrete flask measurements, we developed weighting functions that mimic the temporal averaging of the flask sampling process. Comparisons between in situ and flask CO2 measurements demonstrate that these weighting functions can compensate for atmospheric variability, and provide an effective method for validating airborne in situ CO2 measurements. In addition, we show the nine-year records of flask CO2 measurements. The new system, automated since August 2008, has eliminated the need for manual in-flight calibrations, and thus enables an additional vertical profile, 20 km away, to be sampled at no additional cost in terms of flight hours. This sampling strategy provides an opportunity to investigate both temporal and spatial variability on a regular basis.

/pdf/validation-of-routine-continuous-airborne-co2-observations-3qpdm6aesl.pdf

Krzysztof Katrynski

Papers

Calibration of TCCON column-averaged CO2: the first aircraft campaign over European TCCON sites

Total Column Carbon Observing Network (TCCON) Collection: GGG2014 Site: Bialystok

Automated ground-based remote sensing measurements of greenhouse gases at the Białystok site in comparison with collocated in situ measurements and model data

Validation of routine continuous airborne CO2 observations near the Bialystok Tall Tower

Total Column Carbon Observing Network (TCCON) Site: Bialystok