ALBERT

Description: The TCCON (Total Carbon Column Observing Network) and most NDACC (Network for Detection of Atmospheric Composition Change) assume an ideal ILS (Instrumental line shape) in spectra retrieval and insert an attenuator or select a smaller entrance aperture to take some intensities away if incident radiation is too strong. These processes may alter the alignment of a high resolution FTIR (Fourier transform infrared) spectrometer and may result in biases due to ILS drift. In this paper, we first investigated the sensitivity of ILS monitoring with respect to various typical optical attenuators for ground-based high resolution FTIR spectrometers within the TCCON and NDACC networks. Both lamp and sun cell measurements were conducted in this analysis via the insertion of five different attenuators before and behind the interferometer. We compared the HCl profile retrievals using an ideal ILS with those using an actual measured ILS. The results showed that the total column amounts were under-estimated by about 0.4 % if the ME (modulation efficiency) amplitude deviates by about –3.5 %. Furthermore, the retrieval errors increased and the obvious profile deviations are shown in a height range with a high retrieval sensitivity. ILSs deduced from all scenarios of lamp cell measurements were compared, and were further used to derive the HCl profile from the same spectrum. As a result, the disturbances to the ILS of a high resolution FTIR spectrometer with respect to inserting different attenuators before and behind the interferometer are quantified. The resulting ILS errors propagation into gas retrievals were also analyzed. In conclusion, the alignment of the optical parts before the interferometer is more critical than those behind the interferometer, and the entrance aperture (the focus of the entrance parabolic/spherical mirror) exhibited the most critical influence. An optimum method to adapt the incident intensity of a detector was finally deduced.

Description: Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY onboard ENVISAT (March 2002–April 2012) and TANSO-FTS onboard GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System (IFS). We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r = 0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT-TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (±2 h, 10° × 10° around TCCON sites), i.e., the observed air masses are not exactly identical, but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.

Description: Throughout the last few years solar absorption Fourier Transform Spectrometry (FTS) has been further developed to measure the total columns of CO2 and CH4. The observations are performed at high spectral resolution, typically at 0.02 cm−1. The precision achieved is actually generally better than 0.25%. However, these high resolution instruments are quite large and need a dedicated room or container for installation. We performed these observations using a smaller commercial interferometer at its maximum possible resolution of 0.11 cm−1. The measurements have been performed at Bremen and have been compared to observations using our high resolution instrument also situated at the same location. The high resolution instrument has been successfully operated as part of the Total Carbon Column Observing Network (TCCON). The precision of the low resolution instrument is 0.32% for XCO2 and 0.46% for XCH4. A comparison of the measurements of both instruments yields an average deviation in the retrieved daily means of ≤0.2% for CO2. For CH4 an average bias between the instruments of 0.46% was observed. For test cases, spectra recorded by the high resolution instrument have been truncated to the resolution of 0.11 cm−1. This study gives an offset of 0.03% for CO2 and 0.26% for CH4. These results indicate that for CH4 more than 50% of the difference between the instruments results from the resolution dependant retrieval. We tentatively assign the offset to an incorrect a-priori concentration profile or the effect of interfering gases, which may not be treated correctly.

Description: Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO2) are required for carbon cycle and climate-related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched in January 2009), to retrieve XCO2, the column-averaged dry-air mole fraction of CO2. BESD has been initially developed for SCIAMACHY XCO2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO2 product. GOSAT BESD XCO2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System. We describe the modifications of the BESD algorithm needed in order to retrieve XCO2 from GOSAT and present detailed comparisons with ground-based observations of XCO2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between SCIAMACHY and GOSAT XCO2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT–SCIAMACHY (linear correlation coefficient r=0.82), −0.34 ± 1.37 ppm (r = 0.86) for GOSAT–TCCON and 0.10 ± 1.79 ppm (r = 0.75) for SCIAMACHY–TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (± 2 h, 10° x 10° around TCCON sites), i.e. the observed air masses are not exactly identical but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by also using data from other missions (e.g. OCO-2, GOSAT-2, CarbonSat) in the future.

Description: Throughout the last few years solar absorption Fourier Transform Spectrometry (FTS) has been further developed to measure the total columns of CO2 and CH4. The observations are performed at high spectral resolution, typically at 0.02 cm−1. The precision currently achieved is generally better than 0.25%. However, these high resolution instruments are quite large and need a dedicated room or container for installation. We performed these observations using a smaller commercial interferometer at its maximum possible resolution of 0.11 cm−1. The measurements have been performed at Bremen and have been compared to observations using our high resolution instrument also situated at the same location. The high resolution instrument has been successfully operated as part of the Total Carbon Column Observing Network (TCCON). The precision of the low resolution instrument is 0.32% for XCO2 and 0.46% for XCH4. A comparison of the measurements of both instruments yields an average deviation in the retrieved daily means of ≤0.2% for CO2. For CH4 an average bias between the instruments of 0.47% was observed. For test cases, spectra recorded by the high resolution instrument have been truncated to the resolution of 0.11 cm−1. This study gives an offset of 0.03% for CO2 and 0.26% for CH4. These results indicate that for CH4 more than 50% of the difference between the instruments results from the resolution dependent retrieval. We tentatively assign the offset to an incorrect a-priori concentration profile or the effect of interfering gases, which may not be treated correctly.

Description: This paper investigates the scientific value of retrieving H218O and HDO columns in addition to H216O columns from high-resolution ground-based near-infrared spectra. We present a set of refined H216O, H218O, and HDO spectral windows. The retrieved H216O, H218O, and HDO columns are used for an a posteriori calculation of columnar δD and δ18O. We estimate the uncertainties for the so-calculated columnar δD and δ18O values. These estimations include uncertainties due to the measurement noise, errors in the a priori data, and uncertainties in spectroscopic parameters. Time series of δ18O obtained from ground-based FTIR (Fourier transform infrared) spectra are presented for the first time. For our study we use a full physics isotopic general circulation model (ECHAM5-wiso). We show that the full physics simulation of HDO and H218O can already be reasonably predicted from the H216O columns by a simple linear regression model (scatter values between full physics and linear regression simulations are 35 and 4‰ for HDO and H218O, respectively). We document that the columnar δD and δ18O values as calculated a posteriori from the retrievals of H216O, H218O, and HDO show a better agreement with the ECHAM5-wiso simulation than the δD and δ18O values as calculated from the H216O retrievals and the simple linear regression model. This suggests that the H218O and HDO column retrievals add complementary information to the H216O retrievals. However, these data have to be used carefully, because of the different vertical sensitivity of the H216O, H218O, and HDO columnar retrievals. Furthermore, we have to note that the retrievals use reanalysis humidity profiles as a priori input and the results are thus not independent of the reanalysis data.

Description: This paper investigates the possibility of retrieving isotopic composition of atmospheric water vapour from high-resolution ground based measurements of atmospheric transmittance spectra in the near-infrared region (4000–11 000 cm−1). Simulated measurements of atmospheric transmittance were analyzed in order to find clear spectral signatures of H218O, HDO and H216O. Appropriate signals of the species of interest were found and also identified in measured spectra recorded by ground-based Fourier transform infrared spectrometer (FTIR) at the Institute of Environmental Physics of Bremen University. A set of H218O, HDO and H216O spectroscopic windows is presented. Theoretical estimations of the retrieval precision indicate that spectra recorded by ground-based FTIR spectrometers can be used to measure the seasonal cycle of δ18O and δD in the atmosphere. Studying the influence of the a priori on retrieval results shows low sensitivity to a priori assumptions. Impact of the uncertainties in spectroscopic line parameters of water isotopologues on precision of the retrieval of δ18O and δD is investigated. Time series of δ18O retrieved from ground-based FTIR spectra are represented for the first time. Comparison with the results of ECHAM5-wiso isotopic general circulation model simulations demonstrates a good agreement for "summer" measurements. Conversely, the comparison of "winter" measurements and modeling result show a discrepancy that demonstrate worse agreement that may be connected with incorrect temperature dependence of spectroscopic parameters.