Comparisons between SCIAMACHY and ground-based FTIR data for total columns of CO, CH_4, CO_2 and N_2O

Total column amounts of CO, CH_4, CO_2 and N_2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.5 for CO and CH_4 and version 0.4 for CO_2 and N_2O), IMAP-DOAS (version 1.1 and 0.9 (for CO)) and IMLM (version 6.3) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The present results indicate that the individual SCIAMACHY data obtained with the actual versions of the algorithms have been significantly improved, but that the quality requirements, for estimating emissions on regional scales, are not yet met. Nevertheless, possible directions for further algorithm upgrades have been identified which should result in more reliable data products in a near future

Disentangling chlorophyll fluorescence from atmospheric scattering effects in O_2 A‐band spectra of reflected sun‐light

Global retrieval of solar induced fluorescence emitted by terrestrial vegetation can provide an unprecedented measure for photosynthetic efficiency. The GOSAT (JAXA, launched Feb. 2009) and OCO-2 (NASA, to be launched 2013) satellites record high-resolution spectra in the O_2 A-band region, overlapping part of the chlorophyll fluorescence spectrum. We show that fluorescence cannot be unambiguously discriminated from atmospheric scattering effects using O_2 absorption lines. This can cause systematic biases in retrieved scattering parameters (aerosol optical thickness, aerosol height, surface pressure, surface albedo) if fluorescence is neglected. Hence, we demonstrate an efficient alternative fluorescence least-squares retrieval method based solely on strong Fraunhofer lines in the vicinity of the O_2 A-band, disentangling fluorescence from scattering effects. Not only does the Fraunhofer line fit produce a more accurate estimate of fluorescence emission, but it also allows improved retrievals of atmospheric aerosols from the O_2 A-band

Retrieval of CO from SCIAMACHY onboard ENVISAT: detection of strongly polluted areas and seasonal patterns in global CO abundances

SCIAMACHY onboard the European environmental research satellite ENVISAT is an UV/visible/near-infrared spectrometer providing 3 near infrared channels covering wavelengths from 1-1.75 µm, 1.94-2.04 µm and 2.26-2.38 µm with moderate spectral resolution (0.22-1.5nm). From their structured absorption in these spectral regions, we can quantitatively determine the total column densities of the greenhouse gases CO_2, CH_4, N_2O and H_2O as well as of CO. A modified DOAS algorithm based on optimal estimation (IMAP-DOAS) has been developed at the University of Heidelberg to account for the peculiarities of these absorbers. CO is a relatively weak absorber whose spectral signature is overlapped by strong CH_4 and H_2O absorptions. Hence, retrieval of CO from SCIAMACHY spectra (within 2.26-2.38 µm) is a challenging task. Therefore, the calibration of the raw spectra with respect to dark current issues and nonlinearity were analysed in detail and substantially improved to enable reasonable retrieval of CO. This paper focusses on first results of the CO retrieval where various sources like biomass burning events and their seasonal variability can be clearly identified

Iterative maximum a posteriori (IMAP)-DOAS for retrieval of strongly absorbing trace gases: Model studies for CH_4 and CO_2 retrieval from near infrared spectra of SCIAMACHY onboard ENVISAT

In the past, differential optical absorption spectroscopy (DOAS) has mostly been employed for atmospheric trace gas retrieval in the UV/Vis spectral region. New spectrometers such as SCIAMACHY onboard ENVISAT also provide near infrared channels and thus allow for the detection of greenhouse gases like CH_4, CO_2, or N_2O. However, modifications of the classical DOAS algorithm are necessary to account for the idiosyncrasies of this spectral region, i.e. the temperature and pressure dependence of the high resolution absorption lines. Furthermore, understanding the sensitivity of the measurement of these high resolution, strong absorption lines by means of a non-ideal device, i.e. having finite spectral resolution, is of special importance. This applies not only in the NIR, but can also prove to be an issue for the UV/Vis spectral region

Remote sensing of near-infrared chlorophyll fluorescence from space in scattering atmospheres: implications for its retrieval and interferences with atmospheric CO_2 retrievals

With the advent of dedicated greenhouse gas space-borne spectrometers sporting high resolution spectra in the O_2 A-band spectral region (755–774 nm), the retrieval of chlorophyll fluorescence has become feasible on a global scale. If unaccounted for, however, fluorescence can indirectly perturb the greenhouse gas retrievals as it perturbs the oxygen absorption features. As atmospheric CO_2 measurements are used to invert net fluxes at the land–atmosphere interface, a bias caused by fluorescence can be crucial as it will spatially correlate with the fluxes to be inverted. Avoiding a bias and retrieving fluorescence accurately will provide additional constraints on both the net and gross fluxes in the global carbon cycle. We show that chlorophyll fluorescence, if neglected, systematically interferes with full-physics multi-band X_(CO_2) retrievals using the O_2 A-band. Systematic biases in X_(CO_2) can amount to +1 ppm if fluorescence constitutes 1% to the continuum level radiance. We show that this bias can be largely eliminated by simultaneously fitting fluorescence in a full-physics based retrieval. If fluorescence is the primary target, a dedicated but very simple retrieval based purely on Fraunhofer lines is shown to be more accurate and very robust even in the presence of large scattering optical depths. We find that about 80% of the surface fluorescence is retained at the top-of-atmosphere, even for cloud optical thicknesses around 2–5. We further show that small instrument modifications to future O_2 A-band spectrometer spectral ranges can result in largely reduced random errors in chlorophyll fluorescence, paving the way towards a more dedicated instrument exploiting solar absorption features only

Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide

In recent years, space-borne observations of atmospheric carbon dioxide (CO_2) have been increasingly used in global carbon-cycle studies. In order to obtain added value from space-borne measurements, they have to suffice stringent accuracy and precision requirements, with the latter being less crucial as it can be reduced by just enhanced sample size. Validation of CO_2 column-averaged dry air mole fractions (XCO_2) heavily relies on measurements of the Total Carbon Column Observing Network (TCCON). Owing to the sparseness of the network and the requirements imposed on space-based measurements, independent additional validation is highly valuable. Here, we use observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) flights from 01/2009 through 09/2011 to validate CO_2 measurements from satellites (Greenhouse Gases Observing Satellite – GOSAT, Thermal Emission Sounder – TES, Atmospheric Infrared Sounder – AIRS) and atmospheric inversion models (CarbonTracker CT2013B, Monitoring Atmospheric Composition and Climate (MACC) v13r1). We find that the atmospheric models capture the XCO_2 variability observed in HIPPO flights very well, with correlation coefficients (r^2) of 0.93 and 0.95 for CT2013B and MACC, respectively. Some larger discrepancies can be observed in profile comparisons at higher latitudes, in particular at 300 hPa during the peaks of either carbon uptake or release. These deviations can be up to 4 ppm and hint at misrepresentation of vertical transport. Comparisons with the GOSAT satellite are of comparable quality, with an r^2 of 0.85, a mean bias μ of −0.06 ppm, and a standard deviation σ of 0.45 ppm. TES exhibits an r^2 of 0.75, μ of 0.34 ppm, and σ of 1.13 ppm. For AIRS, we find an r^2 of 0.37, μ of 1.11 ppm, and σ of 1.46 ppm, with latitude-dependent biases. For these comparisons at least 6, 20, and 50 atmospheric soundings have been averaged for GOSAT, TES, and AIRS, respectively. Overall, we find that GOSAT soundings over the remote Pacific Ocean mostly meet the stringent accuracy requirements of about 0.5 ppm for space-based CO_2 observations

Aerosol information content analysis of multi-angle high spectral resolution measurements and its benefit for high accuracy greenhouse gas retrievals

New generations of space-borne spectrometers for the retrieval of atmospheric abundances of greenhouse gases require unprecedented accuracies as atmospheric variability of long-lived gases is very low. These instruments, such as GOSAT and OCO-2, typically use a high spectral resolution oxygen channel (O_2 A-band) in addition to CO_2 and CH_4 channels to discriminate changes in the photon path-length distribution from actual trace gas amount changes. Inaccurate knowledge of the photon path-length distribution, determined by scatterers in the atmosphere, is the prime source of systematic biases in the retrieval. In this paper, we investigate the combined aerosol and greenhouse gas retrieval using multiple satellite viewing angles simultaneously. We find that this method, hitherto only applied in multi-angle imagery such as from POLDER or MISR, greatly enhances the ability to retrieve aerosol properties by 2–3 degrees of freedom. We find that the improved capability to retrieve aerosol parameters significantly reduces interference errors introduced into retrieved CO_2 and CH_4 total column averages. Instead of focussing solely on improvements in spectral and spatial resolution, signal-to-noise ratios or sampling frequency, multiple angles reduce uncertainty in space based greenhouse gas retrievals more effectively and provide a new potential for dedicated aerosols retrievals