ALBERT

Description: The Tropospheric Monitoring Instrument (TROPOMI) onboard the European Space Agency Sentinel-5 Precursor mission is scheduled for launch in the last quarter of 2016. As part of its operational processing the mission will provide CH4 and CO total columns using backscattered sunlight in the shortwave infrared band (2.3 µm). By adapting the CO retrieval algorithm, we have developed a non-scattering algorithm to retrieve total column HDO and H2O from the same measurements under clear sky conditions. The isotopologue ratio HDO / H2O is a powerful diagnostic in the efforts to improve our understanding of the hydrological cycle and its role in climate change, as it provides insight in the source and transport history of water vapour, nature's strongest greenhouse gas. Due to the weak reflectivity over water surfaces we need to restrict the retrieval to cloud-free scenes over land. We exploit a novel two-band filter technique, using strong-vs-weak water or methane absorption bands, to pre-filter scenes with medium-to-high level clouds, cirrus or aerosol and to significantly reduce processing time. Scenes with cloud top heights ≤ 1 km or very low fractions of high-level clouds, or scenes with an aerosol layer above a high surface albedo are not filtered out. We use an ensemble of realistic measurement simulations for various conditions to show the efficiency of the cloud filter and to quantify the performance of the retrieval. The single measurement precision in terms of δD is better than 15–25 ‰ for even the lowest surface albedo 2–4 ‰ for high albedos), while a small bias remains possible of up to ∼ 20 ‰ due to remaining aerosol or up to ∼ 70 ‰ due to remaining cloud contamination. We also present an analysis of the sensitivity towards prior assumptions, which shows that the retrieval has a small but significant sensitivity to the a priori assumption of the atmospheric trace gas profiles. Averaging multiple measurements over time and space, however, will reduce these errors, due to the quasi-random nature of the profile uncertainties. The sensitivity of the retrieval with respect to instrumental parameters within the expected instrument performance is 〈 3 ‰, which represents only a small contribution to the overall error budget. Spectroscopic uncertainties of the water lines, however, can have a larger and more systematic impact on the performance of the retrieval and warrant further reassessment of the water line parameters. With TROPOMI's high radiometric sensitivity, wide swath (resulting in daily global coverage) and efficient cloud filtering, in combination with a spatial resolution of 7 x 7 km2, we will greatly increase the amount of useful data on HDO, H2O and their ratio HDO / H2O. We showcase the overall performance of the retrieval algorithm and cloud filter with an accurate simulation of TROPOMI measurements from a single overpass over parts of the USA and Mexico, based on MODIS satellite data and realistic conditions for the surface, atmosphere and chemistry (including isotopologues). This shows that TROPOMI will pave the way for new studies of the hydrological cycle, both globally and locally, on timescales of mere days and weeks instead of seasons and years, and will greatly extend the HDO / H2O datasets from the SCIAMACHY and GOSAT missions.

Description: Over the last-decade, global scale datasets of atmospheric water vapor isotopologues (HDO) have become available from different remote-sensing instruments. Due to the observational geometry and the spectral ranges that are used, only few satellites sample water isotopologues in the lower troposphere, where the bulk of hydrological processes within the atmosphere take place. Here, we compare three satellite HDO datasets, two from the Tropospheric Emission Spectrometer (TES retrieval version 4 and 5) and one from SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY), with results from the atmospheric global circulation model ECHAM4 (European Center HAMburg 4). We examine a list of known isotopologue effects to qualitatively benchmark the various observational datasets. TES version 5 (TESV5), TES version 4 (TESV4), SCIAMACHY, ECHAM, and ECHAM convoluted with averaging kernel of TES version 5 (ECHAMAK5) successfully reproduced a number of established isotopologue effects such as the latitude effect, the amount effect, and the continental effect, but to different extent. The improvement of TES version 5 over version 4 was confirmed by the steeper latitudinal gradient at higher latitudes in agreement with SCIAMACHY. Other features of the water isotopologue cycle such as the seasonally varying signal in the tropics due to the movement of the Inter Tropical Convergence Zone (ICTZ) are captured in TESV5 and SCIAMACHY. We suggest that the qualitative and quantitative tests carried out in this study could become benchmark tests for evaluation of future satellite isotopologue datasets.

Description: This work presents the operational methane retrieval algorithm for the Sentinel-5 Precursor (S5-P) satellite and its performance tested on realistic ensembles of simulated measurements. The target product is the column-averaged dry air volume mixing ratio of methane (XCH4), which will be retrieved simultaneously with scattering properties of the atmosphere. The algorithm attempts to fit spectra observed by the shortwave and near-infrared channels of the TROPOMI spectrometer aboard S5-P. The sensitivity of the retrieval performance to atmospheric scattering properties, atmospheric input data and instrument calibration errors is evaluated. Also, we investigate the effect of inhomogeneous slit illumination on the instrument spectral response function. Finally, we discuss the cloud filters to be used operationally and as backup. We show that the required accuracy and precision of 〈 1 % for the XCH4 product are met for clear sky measurements over land surfaces and after appropriate filtering of difficult scenes. The algorithm is very stable having a convergence rate of 99 %. The forward model error is less than 1 % for about 95 % of the valid retrievals. Model errors in the input profile of water do not influence the retrieval outcome noticeably. The methane product is expected to meet the requirements if errors in input profiles of pressure and temperature remain below 0.3 % and 2 K, respectively. We find further that, of all instrument calibration errors investigated here, our retrievals are the most sensitive to an error in the instrument spectral response function of the short-wave infrared channel.

Description: Satellite retrievals of methane weighted atmospheric columns are studied within a Bayesian inversion system to infer the global and regional methane emissions and sinks. 19-month inversions from June 2009 to December 2010 are independently computed from three different space-borne observing systems under various hypotheses for prior-flux and observation errors. Posterior methane emissions are inter-compared and evaluated with surface mole fraction measurements, via a chemistry-transport model. Sensitivity tests show that refining the assigned error statistics has a larger impact on the quality of the inverted fluxes than correcting for residual airmass-factor-dependent biases in the satellite retrievals. Improved configurations using TANSO-FTS, SCIAMACHY, IASI and surface measurements induce posterior methane global budgets of respectively, 568 ± 17 Tg yr−1, 603 ± 28 yr−1, 524 ± 16 yr−1 and 538 ± 20 yr−1 over the one-year period August 2009–July 2010. This consistency between some of these satellite retrievals and surface measurements is promising for future improvement of CH4 emission estimates by inversions.

Description: The relative abundance of the heavy water isotopologue HDO provides a deeper insight in the atmospheric hydrological cycle. The SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) allows global retrievals of the ratio HDO/H2O in the 2.3 micron wavelength range. However, the spectroscopy of water lines in this region remains a large source of uncertainty for these retrievals. We therefore evaluate and improve the water spectroscopy in the range 4174–4300 cm−1 and test if this reduces systematic uncertainties in the SCIAMACHY retrievals of HDO/H2O. We use a laboratory spectrum of water vapour to fit line intensity, air broadening and wavelength shift parameters. The improved spectroscopy is tested on a series of ground-based high resolution FTS spectra as well as on SCIAMACHY retrievals of H2O and the ratio HDO/H2O. We find that the improved spectroscopy leads to lower residuals in the FTS spectra compared to HITRAN 2008 and Jenouvrier et al. (2007) spectroscopy and the retrievals become more robust against changes in retrieval window. For both the FTS and SCIAMACHY measurements the retrieved total columns H2O decrease by 2–4 % and we find a negative shift of the HDO/H2O ratio, which for SCIAMACHY is partly compensated by changes in the retrieval setup and calibration software. The updated SCIAMACHY HDO/H2O product shows somewhat steeper latitudinal and temporal gradients and a steeper Rayleigh distillation curve, strengthening previous conclusions that current isotope-enabled general circulation models underestimate the variability in the near-surface HDO/H2O ratio.

Description: Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate feasibility of retrievals of the relative abundance of HDO (the HDO/H2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm−1 (1.56 μm) to retrieve vertical column amounts of H2O and HDO. Retrievals of H2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r2 = 0.96). Typical precision errors in the retrieved column averaged deuterium depletion (δD) are 20–40‰. We validate δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H2O and HDO column amounts and take this into account for a bias-correction of δD. Monthly averages of δD in the June 2009 to September 2011 time-frame are well correlated with TCCON (r2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 timeframe. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset.

Description: Beginning in 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument onboard the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent CH4 measurements were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument onboard ENVISAT. The GOSAT and SCIAMACHY XCH4 retrievals can be compared during their circa 32 month period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modeling system. Additionally, high-accuracy measurements from the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) global air sampling network are used, providing strong constraints of the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON)/Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. 2 year average emission maps show a~good overall agreement among all GOSAT-based inversions, and compared to the SCIAMACHY-based inversion, with consistent flux adjustment patterns, particularly across Equatorial Africa and North America. The inversions are validated against independent shipboard and aircraft observations, and XCH4 measurements available from the Total Carbon Column Observing Network (TCCON). All GOSAT and SCIAMACHY inversions show very similar validation performance.

Description: This study was performed to examine the relationship between isotopic composition in near-surface vapor (δ18Ov) over West Africa during the monsoon season and El Niño–Southern Oscillation (ENSO) activity using the Isotope-incorporated Global Spectral Model. The model was evaluated using a satellite and in situ observations at intraseasonal to interannual timescales. The model provided an accurate simulation of the spatial pattern and seasonal and interannual variations of isotopic composition in column and surface vapor and precipitation over West Africa. Encouraged by this result, a simulation stretching 34 years (1979–2012) was conducted to investigate the relation between atmospheric environment and isotopic signature at the interannual time scale. The simulation indicated that the depletion in the monsoon season does not appear every year at Niamey. The major difference between the composite fields with and without depletion was in the amount of precipitation in the upstream area of Niamey. As the interannual variation of the precipitation amount is influenced by the ENSO, we regressed the monsoon season averaged δ18Ov from the model and annually averaged NINO3 index, and found a statistically significant correlation (R = 0.56, P 〈 0.01) at Niamey. This relation suggests that there is a possibility of reconstructing past West African monsoon activity and ENSO using climate proxies.

Description: The relative abundance of the heavy water isotopologue HDO provides a deeper insight into the atmospheric hydrological cycle. The SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) allows for global retrievals of the ratio HDO/H2O in the 2.3 micron wavelength range. However, the spectroscopy of water lines in this region remains a large source of uncertainty for these retrievals. We therefore evaluate and improve the water spectroscopy in the range 4174–4300 cm−1 and test if this reduces systematic uncertainties in the SCIAMACHY retrievals of HDO/H2O. We use a laboratory spectrum of water vapour to fit line intensity, air broadening and wavelength shift parameters. The improved spectroscopy is tested on a series of ground-based high resolution FTS spectra as well as on SCIAMACHY retrievals of H2O and the ratio HDO/H2O. We find that the improved spectroscopy leads to lower residuals in the FTS spectra compared to HITRAN 2008 and Jenouvrier et al. (2007) spectroscopy, and the retrievals become more robust against changes in the retrieval window. For both the FTS and SCIAMACHY measurements, the retrieved total H2O columns decrease by 2–4% and we find a negative shift of the HDO/H2O ratio, which for SCIAMACHY is partly compensated by changes in the retrieval setup and calibration software. The updated SCIAMACHY HDO/H2O product shows somewhat steeper latitudinal and temporal gradients and a steeper Rayleigh distillation curve, strengthening previous conclusions that current isotope-enabled general circulation models underestimate the variability in the near-surface HDO/H2O ratio.

Description: Remote sensing of the isotopic composition of water vapor can provide valuable information on the hydrological cycle. Here, we demonstrate the feasibility of retrievals of the relative abundance of HDO (the HDO/H2O ratio) from the Japanese GOSAT satellite. For this purpose, we use high spectral resolution nadir radiances around 6400 cm−1 (1.56 μm) to retrieve vertical column amounts of H2O and HDO. Retrievals of H2O correlate well with ECMWF (European Centre for Medium-Range Weather Forecasts) integrated profiles (r2 = 0.96). Typical precision errors in the retrieved column-averaged deuterium depletion (δD) are 20–40‰. We compare δD against a TCCON (Total Carbon Column Observing Network) ground-based station in Lamont, Oklahoma. Using retrievals in very dry areas over Antarctica, we detect a small systematic offset in retrieved H2O and HDO column amounts and take this into account for a bias correction of δD. Monthly averages of δD in the June 2009 to September 2011 time frame are well correlated with TCCON (r2 = 0.79) and exhibit a slope of 0.98 (1.23 if not bias corrected). We also compare seasonal averages on the global scale with results from the SCIAMACHY instrument in the 2003–2005 time frame. Despite the lack of temporal overlap, seasonal averages in general agree well, with spatial correlations (r2) ranging from 0.62 in September through November to 0.83 in June through August. However, we observe higher variability in GOSAT δD, indicated by fitted slopes between 1.2 and 1.46. The discrepancies are likely related to differences in vertical sensitivities but warrant further validation of both GOSAT and SCIAMACHY and an extension of the validation dataset.