Global CO_2 fluxes inferred from surface air-sample measurements and from TCCON retrievals of the CO_2 total column

We present the first estimate of the global distribution of CO_2 surface fluxes from 14 stations of the Total Carbon Column Observing Network (TCCON). The evaluation of this inversion is based on 1) comparison with the fluxes from a classical inversion of surface air-sample-measurements, and 2) comparison of CO_2 mixing ratios calculated from the inverted fluxes with independent aircraft measurements made during the two years analyzed here, 2009 and 2010. The former test shows similar seasonal cycles in the northern hemisphere and consistent regional carbon budgets between inversions from the two datasets, even though the TCCON inversion appears to be less precise than the classical inversion. The latter test confirms that the TCCON inversion has improved the quality (i.e., reduced the uncertainty) of the surface fluxes compared to the assumed or prior fluxes. The consistency between the surface-air-sample-based and the TCCON-based inversions despite remaining flaws in transport models opens the possibility of increased accuracy and robustness of flux inversions based on the combination of both data sources and confirms the usefulness of space-borne monitoring of the CO_2 column

Process-evaluation of tropospheric humidity simulated by general circulation models using water vapor isotopologues: 1. Comparison between models and observations

The goal of this study is to determine how H_2O and HDO measurements in water vapor can be used to detect and diagnose biases in the representation of processes controlling tropospheric humidity in atmospheric general circulation models (GCMs). We analyze a large number of isotopic data sets (four satellite, sixteen ground-based remote-sensing, five surface in situ and three aircraft data sets) that are sensitive to different altitudes throughout the free troposphere. Despite significant differences between data sets, we identify some observed HDO/H_2O characteristics that are robust across data sets and that can be used to evaluate models. We evaluate the isotopic GCM LMDZ, accounting for the effects of spatiotemporal sampling and instrument sensitivity. We find that LMDZ reproduces the spatial patterns in the lower and mid troposphere remarkably well. However, it underestimates the amplitude of seasonal variations in isotopic composition at all levels in the subtropics and in midlatitudes, and this bias is consistent across all data sets. LMDZ also underestimates the observed meridional isotopic gradient and the contrast between dry and convective tropical regions compared to satellite data sets. Comparison with six other isotope-enabled GCMs from the SWING2 project shows that biases exhibited by LMDZ are common to all models. The SWING2 GCMs show a very large spread in isotopic behavior that is not obviously related to that of humidity, suggesting water vapor isotopic measurements could be used to expose model shortcomings. In a companion paper, the isotopic differences between models are interpreted in terms of biases in the representation of processes controlling humidity

GFIT2: an experimental algorithm for vertical profile retrieval from near-IR spectra

An algorithm for retrieval of vertical profiles from ground-based spectra in the near IR is described and tested. Known as GFIT2, the algorithm is primarily intended for CO₂, and is used exclusively for CO₂ in this paper. Retrieval of CO₂ vertical profiles from ground-based spectra is theoretically possible, would be very beneficial for carbon cycle studies and the validation of satellite measurements, and has been the focus of much research in recent years. GFIT2 is tested by application both to synthetic spectra and to measurements at two Total Carbon Column Observing Network (TCCON) sites. We demonstrate that there are approximately 3° of freedom for the CO2 profile, and the algorithm performs as expected on synthetic spectra. We show that the accuracy of retrievals of CO₂ from measurements in the 1.61μ (6220 cm⁻¹) spectral band is limited by small uncertainties in calculation of the atmospheric spectrum. We investigate several techniques to minimize the effect of these uncertainties in calculation of the spectrum. These techniques are somewhat effective but to date have not been demonstrated to produce CO₂ profile retrievals with sufficient precision for applications to carbon dynamics. We finish by discussing ongoing research which may allow CO₂ profile retrievals with sufficient accuracy to significantly improve the scientific value of the measurements from that achieved with column retrievals

Effects of atmospheric light scattering on spectroscopic observations of greenhouse gases from space. Part 2: Algorithm intercomparison in the GOSAT data processing for CO_2 retrievals over TCCON sites

This report is the second in a series of companion papers describing the effects of atmospheric light scattering in observations of atmospheric carbon dioxide (CO_2) by the Greenhouse gases Observing SATellite (GOSAT), in orbit since 23 January 2009. Here we summarize the retrievals from six previously published algorithms; retrieving column‐averaged dry air mole fractions of CO_2 (X_(CO2)) during 22 months of operation of GOSAT from June 2009. First, we compare data products from each algorithm with ground‐based remote sensing observations by Total Carbon Column Observing Network (TCCON). Our GOSAT‐TCCON coincidence criteria select satellite observations within a 5° radius of 11 TCCON sites. We have compared the GOSAT‐TCCON X_(CO2) regression slope, standard deviation, correlation and determination coefficients, and global and station‐to‐station biases. The best agreements with TCCON measurements were detected for NIES 02.xx and RemoTeC. Next, the impact of atmospheric light scattering on X_(CO2) retrievals was estimated for each data product using scan by scan retrievals of light path modification with the photon path length probability density function (PPDF) method. After a cloud pre‐filtering test, approximately 25% of GOSAT soundings processed by NIES 02.xx, ACOS B2.9, and UoL‐FP: 3G and 35% processed by RemoTeC were found to be contaminated by atmospheric light scattering. This study suggests that NIES 02.xx and ACOS B2.9 algorithms tend to overestimate aerosol amounts over bright surfaces, resulting in an underestimation of X_(CO2) for GOSAT observations. Cross‐comparison between algorithms shows that ACOS B2.9 agrees best with NIES 02.xx and UoL‐FP: 3G while RemoTeC X_(CO2) retrievals are in a best agreement with NIES PPDF‐D

Improvement of the retrieval algorithm for GOSAT SWIR XCO_2 and XCH_4 and their validation using TCCON data

The column-averaged dry-air mole fractions of carbon dioxide and methane (XCO_2 and XCH_4) have been retrieved from Greenhouse gases Observing SATellite (GOSAT) Short-Wavelength InfraRed (SWIR) observations and released as a SWIR L2 product from the National Institute for Environmental Studies (NIES). XCO_2 and XCH_4 retrieved using the version 01.xx retrieval algorithm showed large negative biases and standard deviations (−8.85 and 4.75 ppm for XCO_2 and −20.4 and 18.9 ppb for XCH_4, respectively) compared with data of the Total Carbon Column Observing Network (TCCON). Multiple reasons for these error characteristics (e.g., solar irradiance database, handling of aerosol scattering) are identified and corrected in a revised version of the retrieval algorithm (version 02.xx). The improved retrieval algorithm shows much smaller biases and standard deviations (−1.48 and 2.09 ppm for XCO_2 and −5.9 and 12.6 ppb for XCH_4, respectively) than the version 01.xx. Also, the number of post-screened measurements is increased, especially at northern mid- and high-latitudinal areas

Methane observations from the Greenhouse Gases Observing SATellite: Comparison to ground‐based TCCON data and model calculations

We report new short-wave infrared (SWIR) column retrievals of atmospheric methane (X_(CH4)) from the Japanese Greenhouse Gases Observing SATellite (GOSAT) and compare observed spatial and temporal variations with correlative ground-based measurements from the Total Carbon Column Observing Network (TCCON) and with the global 3-D GEOS-Chem chemistry transport model. GOSAT X_(CH4) retrievals are compared with daily TCCON observations at six sites between April 2009 and July 2010 (Bialystok, Park Falls, Lamont, Orleans, Darwin and Wollongong). GOSAT reproduces the site-dependent seasonal cycles as observed by TCCON with correlations typically between 0.5 and 0.7 with an estimated single-sounding precision between 0.4–0.8%. We find a latitudinal-dependent difference between the X_(CH4) retrievals from GOSAT and TCCON which ranges from 17.9 ppb at the most northerly site (Bialystok) to −14.6 ppb at the site with the lowest latitude (Darwin). We estimate that the mean smoothing error difference included in the GOSAT to TCCON comparisons can account for 15.7 to 17.4 ppb for the northerly sites and for 1.1 ppb at the lowest latitude site. The GOSAT X_(CH4) retrievals agree well with the GEOS-Chem model on annual (August 2009 – July 2010) and monthly timescales, capturing over 80% of the zonal variability. Differences between model and observed X_(CH4) are found over key source regions such as Southeast Asia and central Africa which will be further investigated using a formal inverse model analysis

Towards constraints on fossil fuel emissions from total column carbon dioxide

We assess the large-scale, top-down constraints on regional fossil fuel emissions provided by observations of atmospheric total column CO_2, X_CO_2. Using an atmospheric general circulation model (GCM) with underlying fossil emissions, we determine the influence of regional fossil fuel emissions on global X_CO_2 fields. We quantify the regional contrasts between source and upwind regions and probe the sensitivity of atmospheric X_CO_2 to changes in fossil fuel emissions. Regional fossil fuel X_CO_2 contrasts can exceed 0.7 ppm based on 2007 emission estimates, but have large seasonal variations due to biospheric fluxes. Contamination by clouds reduces the discernible fossil signatures. Nevertheless, our simulations show that atmospheric fossil X_CO_2 can be tied to its source region and that changes in the regional X_CO_2 contrasts scale linearly with emissions. We test the GCM results against X_CO_2 data from the GOSAT satellite. Regional X_CO_2 contrasts in GOSAT data generally scale with the predictions from the GCM, but the comparison is limited by the moderate precision of and relatively few observations from the satellite. We discuss how this approach may be useful as a policy tool to verify national fossil emissions, as it provides an independent, observational constraint

Balloon-borne radiometer measurement of Northern Hemisphere mid-latitude stratospheric HNO3 profiles spanning 12 years

Low-resolution atmospheric thermal emission spectra collected by balloon-borne radiometers over the time span of 1990–2002 are used to retrieve vertical profiles of HNO3, CFC-11 and CFC-12 volume mixing ratios between approximately 10 and 35 km altitude. All of the data analyzed have been collected from launches from a Northern Hemisphere mid-latitude site, during late summer, when stratospheric dynamic variability is at a minimum. The retrieval technique incorporates detailed forward modeling of the instrument and the radiative properties of the atmosphere, and obtains a best fit between modeled and measured spectra through a combination of onion-peeling and global optimization steps. The retrieved HNO3 profiles are consistent over the 12-year period, and are consistent with recent measurements by the Atmospheric Chemistry Experiment-Fourier transform spectrometer satellite instrument. This suggests that, to within the errors of the 1990 measurements, there has been no significant change in the HNO3 summer mid-latitude profile