ALBERT

Description: Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of ~2% agreement with TM5 is typically within 1–2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA's CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005) we find significantly higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. Concerning inter-annual variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurements.

Description: Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 minute per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2). In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS) XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with global XCO2 fields obtained from NOAA's CO2 assimilation system CarbonTracker. For the Northern Hemisphere we find good agreement with the reference data for the CO2 seasonal cycle and the CO2 annual increase. For the Southern Hemisphere, where significantly less data are available for averaging compared to the Northern Hemisphere, the CO2 annual increase is also in good agreement with CarbonTracker but the amplitude and phase of the seasonal cycle show systematic differences up to a few ppm arising partially from the O2 normalization. The retrieved XCO2 regional pattern at monthly resolution over various regions show clear corrrelations with CarbonTracker but also significant differences. Typically the retrieved variability is about 4 ppm (1% of 380 ppm) higher but depending on time and location differences can reach or even exceed 8 ppm. Based on the error analysis and on the comparison with the reference data we conclude that the XCO2 data set can be characterized by a single measurement retrieval precision (random error) of 1–2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1–2% for monthly averages at a spatial resolution of about 7°×7°. When averaging the SCIAMACHY XCO2 over all three years we find reasonable correlation with EDGAR anthropogenic CO2 emissions for Germany, The Netherlands and Belgium indicating that regionally elevated CO2 arising from regional anthropogenic CO2 emissions can be detected from space.

Description: Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCH4 data set. The XCO2 data set is discussed in a separate paper (Part 1). For 2003 we present detailed comparisons with the TM5 model which has been optimally matched to highly accurate but sparse methane surface observations. After accounting for a systematic low bias of ~2% agreement with TM5 is typically within 1–2%. We investigated to what extent the SCIAMACHY XCH4 is influenced by the variability of atmospheric CO2 using global CO2 fields from NOAA's CO2 assimilation system CarbonTracker. We show that the CO2 corrected and uncorrected XCH4 spatio-temporal pattern are very similar but that agreement with TM5 is better for the CarbonTracker CO2 corrected XCH4. In line with previous studies (e.g., Frankenberg et al., 2005b) we find higher methane over the tropics compared to the model. We show that tropical methane is also higher when normalizing the CH4 columns with retrieved O2 columns instead of CO2. In consistency with recent results of Frankenberg et al. (2008b) it is shown that the magnitude of the retrieved tropical methane is sensitive to the choice of the spectroscopic line parameters of water vapour. Concerning inter-annual variability we find similar methane spatio-temporal pattern for 2003 and 2004. For 2005 the retrieved methane shows significantly higher variability compared to the two previous years, most likely due to somewhat larger noise of the spectral measurements.

Description: The three carbon gases carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) are important atmospheric constituents affecting air quality and climate. The near-infrared nadir spectra measured by SCIAMACHY on ENVISAT contain information on the vertical columns of these gases which we retrieve using a modified DOAS algorithm (WFM-DOAS or WFMD). Our main data products are CO vertical columns and dry-air column averaged mixing ratios of methane (CH4) and CO2 (denoted XCH4 and XCO2). For CO and CH4 we present new results for the year 2003 obtained with an improved version of WFM-DOAS (WFMDv0.5) retrieved from Level 1 version 4 (Lv1v4) spectra. This data set has recently been compared with a network of ground based FTIR stations. Here we describe the WFMDv0.5 algorithm, present global and regional maps, and comparisons with global reference data. We show that major problems of the previous versions (v0.4 and v0.41) related to the varying ice-layer on the SCIAMACHY channel 8 detector have been solved. Compared to MOPITT the SCIAMACHY CO columns are on average higher by about 10–20%. Regionally, however, especially over central South America, differences can be much larger. For methane we present global and regional maps which are compared to TM5 model simulations performed using standard methane emission inventories. We show that methane source regions can be clearly detected with SCIAMACHY. We also show that the methane data product can be significantly further improved using Lv1v5 spectra with improved calibration. For CO2 we present three years of SCIAMACHY CO2 measurements over Park Falls, Wisconsin, USA, retrieved from Lv1v5. We show that the quality of CO2 retrieved from these spectra is significantly higher compared to WFMDv0.4 XCO2 retrieved from Lv1v4.

Description: Carbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases. SCIAMACHY on ENVISAT is the first satellite instrument whose measurements are sensitive to concentration changes of the two gases at all altitude levels down to the Earth's surface where the source/sink signals are largest. We have processed three years (2003–2005) of SCIAMACHY near-infrared nadir measurements to simultaneously retrieve vertical columns of CO2 (from the 1.58 μm absorption band), CH4 (1.66 μm) and oxygen (O2 A-band at 0.76 μm) using the scientific retrieval algorithm WFM-DOAS. We show that the latest version of WFM-DOAS, version 1.0, which is used for this study, has been significantly improved with respect to its accuracy compared to the previous versions while essentially maintaining its high processing speed (~1 min per orbit, corresponding to ~6000 single measurements, and per gas on a standard PC). The greenhouse gas columns are converted to dry air column-averaged mole fractions, denoted XCO2 (in ppm) and XCH4 (in ppb), by dividing the greenhouse gas columns by simultaneously retrieved dry air columns. For XCO2 dry air columns are obtained from the retrieved O2 columns. For XCH4 dry air columns are obtained from the retrieved CO2 columns because of better cancellation of light path related errors compared to using O2 columns retrieved from the spectrally distant O2 A-band. Here we focus on a discussion of the XCO2 data set. The XCH4 data set is discussed in a separate paper (Part 2). In order to assess the quality of the retrieved XCO2 we present comparisons with Fourier Transform Spectroscopy (FTS) XCO2 measurements at two northern hemispheric mid-latitude ground stations. To assess the quality globally, we present detailed comparisons with global XCO2 fields obtained from NOAA's CO2 assimilation system CarbonTracker. For the Northern Hemisphere we find good agreement with the reference data for the CO2 seasonal cycle and the CO2 annual increase. For the Southern Hemisphere, where significantly less data are available for averaging compared to the Northern Hemisphere, the CO2 annual increase is also in good agreement with CarbonTracker but the amplitude and phase of the seasonal cycle show systematic differences (up to several ppm) arising partially from the O2 normalization most likely caused by unconsidered scattering effects due to subvisual cirrus clouds. The retrieved XCO2 regional pattern at monthly resolution over various regions show clear correlations with CarbonTracker but also significant differences. Typically the retrieved variability is about 4 ppm (1% of 380 ppm) higher but depending on time and location differences can reach or even exceed 8 ppm. Based on the error analysis and on the comparison with the reference data we conclude that the XCO2 data set can be characterized by a single measurement retrieval precision (random error) of 1–2%, a systematic low bias of about 1.5%, and by a relative accuracy of about 1–2% for monthly averages at a spatial resolution of about 7°×7°. When averaging the SCIAMACHY XCO2 over all three years we find elevated CO2 over the highly populated region of western central Germany and parts of the Netherlands ("Rhine-Main area") reasonably well correlated with EDGAR anthropogenic CO2 emissions. On average the regional enhancement is 2.7 ppm including an estimated contribution of 1–1.5 ppm due to aerosol related errors and sampling.

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: Indonesia experienced an exceptional number of fires in 2015 as a result of droughts related to the recent El Niño event and human activities. These fires released large amounts of carbon dioxide (CO2) into the atmosphere. Emission databases such as the Global Fire Assimilation System version 1.2 and the Global Fire Emission Database version 4s estimated the CO2 emission to be approximately 1100 MtCO2 in the time period from July to November 2015. This emission was indirectly estimated by using parameters like burned area, fire radiative power, and emission factors. In the study presented in this paper, we estimate the Indonesian fire CO2 emission by using the column-averaged dry air mole fraction of CO2, XCO2, derived from measurements of the Orbiting Carbon Observatory-2 satellite mission. The estimated CO2 emission is 748 ± 209 MtCO2, which is about 30% lower than provided by the emission databases. ©2017. American Geophysical Union. All Rights Reserved.