scholarly journals Methane profiles from GOSAT thermal infrared spectra

2018 ◽  
Vol 11 (6) ◽  
pp. 3815-3828 ◽  
Author(s):  
Arno de Lange ◽  
Jochen Landgraf
Keyword(s):  
Lower Troposphere ◽  
Principal Component ◽  
Thermal Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Atmospheric Methane ◽  
Infrared Band ◽  
Correction Scheme ◽  
Infrared Measurements

Abstract. This paper discusses the retrieval of atmospheric methane profiles from the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) between 1210 and 1310 cm−1, using the RemoTeC analysis software. Approximately one degree of information on the vertical methane distribution is inferred from the measurements, with the main sensitivity at about 9 km altitude but little sensitivity to methane in the lower troposphere. For verification, we compare the GOSAT-TIR methane profile retrieval results with profiles from model fields provided by the Monitoring Atmospheric Composition and Climate (MACC) project, scaled to the total column measurements of the Total Carbon Column Observing Network (TCCON) at ground-based measurement sites. Without any radiometric corrections of GOSAT observations, differences between both data sets can be as large as 10 %. To mitigate these differences, we developed a correction scheme using a principal component analysis of spectral fit residuals and airborne observations of methane during the HIAPER pole-to-pole observations (HIPPO) campaign II and III. When the correction scheme is applied, the bias in the methane profile can be reduced to less than 2 % over the whole altitude range with respect to MACC model methane fields. Furthermore, we show that, with this correction, the retrievals result in smooth methane fields over land and ocean crossings and no differences can be discerned between daytime and nighttime measurements. Finally, a cloud filter is developed for the nighttime and ocean measurements. This filter is rooted in the GOSAT-TIR (thermal infrared) measurements and its performance, in terms of biases, is consistent with the cloud filter based on the GOSAT-SWIR (shortwave infrared) measurements. The TIR filter shows a higher acceptance rate of observations than the SWIR filter, at the cost of a higher uncertainty in the retrieved methane profiles.

scholarly journals Methane profiles from GOSAT thermal infrared spectra

2017 ◽  
Author(s):  
Arno de Lange ◽  
Jochen Landgraf
Keyword(s):  
Lower Troposphere ◽  
Principal Component ◽  
Thermal Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Atmospheric Methane ◽  
Infrared Band ◽  
Correction Scheme ◽  
Ocean Measurements

Abstract. This paper discusses the retrieval of atmospheric methane profiles from the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) between 1210 and 1310 cm−1, using the RemoTeC analysis software. Approximately one degree of information on the vertical methane distribution is inferred from the measurements with the main sensitivity at about 9 km altitude but little sensitivity to methane in the lower troposphere. For verification, we compare the GOSAT methane abundance at measurement sites of the Total Carbon Column Observing Network (TCCON) to methane profiles provided by the Monitoring Atmospheric Composition and Climate (MACC) model fields scaled to the total column observations at the sites. Without any radiometric corrections of GOSAT observations, differences between both data sets can be as large as 10 %. To mitigate these differences, we developed a correction scheme using a principal component analysis of spectral fit residuals and airborne observations of methane during the HIAPER Pole-to-Pole Observations (HIPPO) campaign II and III. When the correction scheme is applied, the bias in the methane profile can be reduced to less than 2 % over the whole altitude range with respect to MACC model methane fields. Furthermore, we show that, with this correction, the retrievals result in smooth methane fields over land and ocean crossings and no differences are to be discerned between daytime and nighttime measurements. Finally, a cloud filter is developed for the nighttime and ocean measurements. This filter is rooted in the GOSAT-TIR measurements and is consistent with the cloud filter based on the GOSAT-SWIR measurements, despite the fact that the TIR-filter is less stringent.

scholarly journals Increase of Atmospheric Methane Observed from Space-Borne and Ground-Based Measurements

2019 ◽  
Vol 11 (8) ◽  
pp. 964 ◽  
Author(s):  
Mingmin Zou ◽  
Xiaozhen Xiong ◽  
Zhaohua Wu ◽  
Shenshen Li ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Marine Boundary Layer ◽  
Lower Troposphere ◽  
Ensemble Empirical Mode Decomposition ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Atmospheric Methane ◽  
High Northern Latitude ◽  
Surface Emission ◽  
Mode Decomposition ◽  
Increase Rate

It has been found that the concentration of atmospheric methane (CH4) has rapidly increased since 2007 after a decade of nearly constant concentration in the atmosphere. As an important greenhouse gas, such an increase could enhance the threat of global warming. To better quantify this increasing trend, a novel statistic method, i.e. the Ensemble Empirical Mode Decomposition (EEMD) method, was used to analyze the CH4 trends from three different measurements: the mid–upper tropospheric CH4 (MUT) from the space-borne measurements by the Atmospheric Infrared Sounder (AIRS), the CH4 in the marine boundary layer (MBL) from NOAA ground-based in-situ measurements, and the column-averaged CH4 in the atmosphere (XCH4) from the ground-based up-looking Fourier Transform Spectrometers at Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC). Comparison of the CH4 trends in the mid–upper troposphere, lower troposphere, and the column average from these three data sets shows that, overall, these trends agree well in capturing the abrupt CH4 increase in 2007 (the first peak) and an even faster increase after 2013 (the second peak) over the globe. The increased rates of CH4 in the MUT, as observed by AIRS, are overall smaller than CH4 in MBL and the column-average CH4. During 2009–2011, there was a dip in the increase rate for CH4 in MBL, and the MUT-CH4 increase rate was almost negligible in the mid-high latitude regions. The increase of the column-average CH4 also reached the minimum during 2009–2011 accordingly, suggesting that the trends of CH4 are not only impacted by the surface emission, however that they also may be impacted by other processes like transport and chemical reaction loss associated with [OH]. One advantage of the EEMD analysis is to derive the monthly rate and the results show that the frequency of the variability of CH4 increase rates in the mid–high northern latitude regions is larger than those in the tropics and southern hemisphere.

scholarly journals Simulated Multispectral Temperature and Atmospheric Composition Retrievals for the JPL GEO-IR Sounder

2021 ◽  
Author(s):  
Vijay Natraj ◽  
Ming Luo ◽  
Jean-Francois Blavier ◽  
Vivienne H. Payne ◽  
Derek J. Posselt ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Thermal Emission ◽  
Weather Forecasting ◽  
Lower Troposphere ◽  
Atmospheric Temperature ◽  
Atmospheric Composition ◽  
Near Surface ◽  
Infrared Measurements ◽  
Infrared Spectral ◽  
Shortwave Infrared

Abstract. Satellite measurements enable quantification of atmospheric temperature, humidity, and trace gas vertical profiles. The majority of current instruments operate on polar orbiting satellites and either in the thermal/mid-wave or in the shortwave infrared spectral regions. We present a new multispectral instrument concept for improved measurements from geostationary orbit (GEO) with sensitivity to the boundary layer. The JPL GEO-IR sounder, which is an imaging Fourier Transform Spectrometer, uses a wide spectral range (1–15.4 μm), encompassing both reflected solar and thermal emission bands to improve sensitivity to the lower troposphere and boundary layer. We perform retrieval simulations for both clean and polluted scenarios that also encompass different temperature and humidity profiles. The results illustrate the benefits of combining shortwave and thermal infrared measurements. In particular, the former adds information in the boundary layer, while the latter helps to separate near-surface and mid-tropospheric variability. The performance of the JPL GEO-IR sounder is similar to or better than currently operational instruments. The proposed concept is expected to improve weather forecasting, severe storm tracking and forecasting, and also benefit local and global air quality and climate research.

scholarly journals Using XCO<sub>2</sub> retrievals for assessing the long-term consistency of NDACC/FTIR data sets

2014 ◽  
Vol 7 (10) ◽  
pp. 10513-10558
Author(s):  
S. Barthlott ◽  
M. Schneider ◽  
F. Hase ◽  
A. Wiegele ◽  
E. Christner ◽  
...  
Keyword(s):  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Mauna Loa ◽  
Simple Regression Model ◽  
Good Consistency ◽  
Term Data

Abstract. Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier–Transform InfraRed) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these data records. Our NDACC XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons and the bias is 25‰). As XCO2 model we developed and used a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in-situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3‰.

scholarly journals Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals

2015 ◽  
Vol 8 (10) ◽  
pp. 10549-10576
Author(s):  
M. Zou ◽  
X. Xiong ◽  
N. Saitoh ◽  
J. Warner ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
High Latitude ◽  
Near Infrared ◽  
Thermal Infrared ◽  
Satellite Observation ◽  
Spatial And Temporal Variation ◽  
Atmospheric Methane ◽  
Infrared Measurements ◽  
The Difference ◽  
Total Column

Abstract. Space-borne observations of atmospheric methane (CH4) have been made using the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua satellite since August 2002 and the Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT) since April 2009. This study compared the GOSAT TANSO-FTS thermal infrared (TIR) version 1.0 CH4 product with the collocated AIRS version 6 CH4 product using data from 1 August 2010 to 30 June 2012, including the CH4 mixing ratios and the total column amounts. The results show that at 300–600 hPa, where both AIRS and GOSAT-TIR CH4 have peak sensitivities, they agree very well, but GOSAT-TIR retrievals tend to be higher than AIRS in layer 200–300 hPa. At 300 hPa the CH4 mixing ratio from GOSAT-TIR is, on average, 10.3 ± 31.8 ppbv higher than that from AIRS, and at 600 hPa GOSAT-TIR retrieved CH4 is -16.2 ± 25.7 ppbv lower than AIRS CH4. Comparison of the total column amount of CH4 shows that GOSAT-TIR agrees with AIRS to within 1 % in the mid-latitude regions of Southern Hemisphere and in tropics. In the mid to high latitudes in the Northern Hemisphere, GOSAT-TIR is ~ 1–2 % lower than AIRS, and in the high-latitude regions of Southern Hemisphere the difference of GOSAT from AIRS varies from −3 % in October to +2 % in July. The difference between AIRS and GOSAT TANSO-FTS retrievals is mainly due to the difference in retrieval algorithms and instruments itself, and the larger difference in the high latitude regions is associated with the low information content and small degree of freedoms of the retrieval. The degree of freedom of GOSAT-TIR retrievals is lower than that of AIRS also indicates that the constraint in GOSAT-TIR retrieval may be too strong. From the good correlation between AIRS and GOSAT-TIR retrievals and the seasonal variation they observed we are confident that the thermal infrared measurements from AIRS and GOSAT-TIR can provide valuable information to capture the spatial and temporal variation of CH4, especially in the mid-upper troposphere, in most time and regions.

scholarly journals Using XCO<sub>2</sub> retrievals for assessing the long-term consistency of NDACC/FTIR data sets

2015 ◽  
Vol 8 (3) ◽  
pp. 1555-1573 ◽  
Author(s):  
S. Barthlott ◽  
M. Schneider ◽  
F. Hase ◽  
A. Wiegele ◽  
E. Christner ◽  
...  
Keyword(s):  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Mauna Loa ◽  
Simple Regression Model ◽  
Good Consistency ◽  
Term Data

Abstract. Within the NDACC (Network for the Detection of Atmospheric Composition Change), more than 20 FTIR (Fourier-transform infrared) spectrometers, spread worldwide, provide long-term data records of many atmospheric trace gases. We present a method that uses measured and modelled XCO2 for assessing the consistency of these NDACC data records. Our XCO2 retrieval setup is kept simple so that it can easily be adopted for any NDACC/FTIR-like measurement made since the late 1950s. By a comparison to coincident TCCON (Total Carbon Column Observing Network) measurements, we empirically demonstrate the useful quality of this suggested NDACC XCO2 product (empirically obtained scatter between TCCON and NDACC is about 4‰ for daily mean as well as monthly mean comparisons, and the bias is 25‰). Our XCO2 model is a simple regression model fitted to CarbonTracker results and the Mauna Loa CO2 in situ records. A comparison to TCCON data suggests an uncertainty of the model for monthly mean data of below 3‰. We apply the method to the NDACC/FTIR spectra that are used within the project MUSICA (multi-platform remote sensing of isotopologues for investigating the cycle of atmospheric water) and demonstrate that there is a good consistency for these globally representative set of spectra measured since 1996: the scatter between the modelled and measured XCO2 on a yearly time scale is only 3‰.

scholarly journals Satellite observation of atmospheric methane: intercomparison between AIRS and GOSAT TANSO-FTS retrievals

2016 ◽  
Vol 9 (8) ◽  
pp. 3567-3576 ◽  
Author(s):  
Mingmin Zou ◽  
Xiaozhen Xiong ◽  
Naoko Saitoh ◽  
Juying Warner ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
High Latitude ◽  
Degrees Of Freedom ◽  
Near Infrared ◽  
Thermal Infrared ◽  
Spatial And Temporal Variation ◽  
Atmospheric Methane ◽  
Infrared Measurements ◽  
The Difference ◽  
Total Column

Abstract. Space-borne observations of atmospheric methane (CH4) have been made using the Atmospheric Infrared Sounder (AIRS) on the EOS/Aqua satellite since August 2002 and the Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) on the Greenhouse Gases Observing Satellite (GOSAT) since April 2009. This study compared the GOSAT TANSO-FTS thermal infrared (TIR) version 1.0 CH4 product with the collocated AIRS version 6 CH4 product using data from 1 August 2010 to 30 June 2012, including the CH4 mixing ratios and the total column amounts. The results show that at 300–600 hPa, where both AIRS and GOSAT-TIR CH4 have peak sensitivities, they agree very well, but GOSAT-TIR retrievals tend to be higher than AIRS in layer 200–300 hPa. At 300 hPa the CH4 mixing ratio from GOSAT-TIR is, on average, 10.3 ± 31.8 ppbv higher than that from AIRS, and at 600 hPa GOSAT-TIR retrieved CH4 is −16.2 ± 25.7 ppbv lower than AIRS CH4. Comparison of the total column amount of CH4 shows that GOSAT-TIR agrees with AIRS to within 1 % in the mid-latitude regions of the Southern Hemisphere and in the tropics. In the mid to high latitudes in the Northern Hemisphere, comparison shows that GOSAT-TIR is  ∼  1–2 % lower than AIRS, and in the high-latitude regions of the Southern Hemisphere the difference of GOSAT from AIRS varies from −3 % in October to +2 % in July. The difference between AIRS and GOSAT TANSO-FTS retrievals is mainly due to the difference in retrieval algorithms and instruments themselves, and the larger difference in the high-latitude regions is associated with the low information content and small degrees of freedom of the retrieval. The degrees of freedom of GOSAT-TIR retrievals are lower than that of AIRS, which also indicates that the constraint in GOSAT-TIR retrievals may be too strong. From the good correlation between AIRS and GOSAT-TIR retrievals and the seasonal variation they observed, we are confident that the thermal infrared measurements from AIRS and GOSAT-TIR can provide valuable information to capture the spatial and temporal variation of CH4, especially in the mid-upper troposphere, in most periods and regions.

scholarly journals Assimilation of atmospheric methane products in the MACC-II system: from SCIAMACHY to TANSO and IASI

2014 ◽  
Vol 14 (2) ◽  
pp. 2553-2599
Author(s):  
S. Massart ◽  
A. Agusti-Panareda ◽  
I. Aben ◽  
A. Butz ◽  
F. Chevallier ◽  
...  
Keyword(s):  
Near Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Winter Period ◽  
Tropical Region ◽  
Atmospheric Methane ◽  
Atmospheric Sounding ◽  
Scanning Imaging ◽  
Global Bias ◽  
The Impact

Abstract. The Monitoring Atmospheric Composition and Climate Interim Implementation (MACC-II) delayed-mode (DM) system has been producing an atmospheric methane (CH4) analysis 6 months behind real time since June 2009. This analysis used to rely on the assimilation of the CH4 product from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on board Envisat. Recently the \\textit{Laboratoire de Météorologie Dynamique} (LMD) CH4 products from the Infrared Atmospheric Sounding Interferometer (IASI) and the SRON Netherlands Institute for Space Research CH4 products from the Thermal And Near-infrared Sensor for carbon Observation (TANSO) were added to the DM system. With the loss of Envisat in April 2012, the DM system has to now rely on the assimilation of methane data from TANSO and IASI. This paper documents the impact of this change in the observing system on the methane tropospheric analysis. It is based on four experiments: one free run and three analyses from respectively the assimilation of SCIAMACHY, TANSO and a combination of TANSO and IASI CH4 products in the MACC-II system. The period between December 2010 and April 2012 is studied. This corresponds to a period during which the performance of SCIAMACHY was deteriorating. The SCIAMACHY experiment globally underestimates the tropospheric methane by 35 part per billion (ppb) compared to the HIAPER Pole-to-Pole Observations (HIPPO) data and the methane column by 23 ppb compared the Total Carbon Column Observing Network (TCCON) data, when the global bias of the free run against the same HIPPO and TCCON data is respectively −5 ppb and 4 ppb. The assimilated TANSO product changed in October 2011 from version v.1 to version v.2.0. The analysis of version v.1 globally underestimates the tropospheric methane by 18 ppb compared to the HIPPO data and the column by 11 ppb compared to the TCCON data. In contrast, the analysis of version v.2.0 globally overestimates the column by 10 ppb. When the high density IASI data are added in the tropical region between 30° N and 30° S, the resulting analysis is slightly less biased in the troposphere than the TANSO analysis when compared to the HIPPO data. In the meantime, this IASI plus TANSO analysis presents the worst correlation with the HIPPO data. In terms of column, the addition of the IASI data to the version v.2.0 of the TANSO data has a significant impact, mainly over extratropical regions, reducing the global bias to 6 ppb. The analysis based on the assimilation of the combination of TANSO and IASI products as well as the SCIAMACHY analysis should nevertheless be used with caution when looking at the seasonal cycle or inter-hemispheric gradient because of the unavailability of the measurements over large regions during the local winter period.

scholarly journals Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI

2014 ◽  
Vol 14 (12) ◽  
pp. 6139-6158 ◽  
Author(s):  
S. Massart ◽  
A. Agusti-Panareda ◽  
I. Aben ◽  
A. Butz ◽  
F. Chevallier ◽  
...  
Keyword(s):  
Near Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Tropical Region ◽  
Atmospheric Methane ◽  
Infrared Sensor ◽  
Atmospheric Sounding ◽  
Scanning Imaging ◽  
The Tropics ◽  
The Impact

Abstract. The Monitoring Atmospheric Composition and Climate Interim Implementation (MACC-II) delayed-mode (DM) system has been producing an atmospheric methane (CH4) analysis 6 months behind real time since June 2009. This analysis used to rely on the assimilation of the CH4 product from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument onboard Envisat. Recently the Laboratoire de Météorologie Dynamique (LMD) CH4 products from the Infrared Atmospheric Sounding Interferometer (IASI) and the SRON Netherlands Institute for Space Research CH4 products from the Thermal And Near-infrared Sensor for carbon Observation (TANSO) were added to the DM system. With the loss of Envisat in April 2012, the DM system now has to rely on the assimilation of methane data from TANSO and IASI. This paper documents the impact of this change in the observing system on the methane tropospheric analysis. It is based on four experiments: one free run and three analyses from respectively the assimilation of SCIAMACHY, TANSO and a combination of TANSO and IASI CH4 products in the MACC-II system. The period between December 2010 and April 2012 is studied. The SCIAMACHY experiment globally underestimates the tropospheric methane by 35 part per billion (ppb) compared to the HIAPER Pole-to-Pole Observations (HIPPO) data and by 28 ppb compared the Total Carbon Column Observing Network (TCCON) data, while the free run presents an underestimation of 5 ppb and 1 ppb against the same HIPPO and TCCON data, respectively. The assimilated TANSO product changed in October 2011 from version v.1 to version v.2.0. The analysis of version v.1 globally underestimates the tropospheric methane by 18 ppb compared to the HIPPO data and by 15 ppb compared to the TCCON data. In contrast, the analysis of version v.2.0 globally overestimates the column by 3 ppb. When the high density IASI data are added in the tropical region between 30° N and 30° S, their impact is mainly positive but more pronounced and effective when combined with version v.2.0 of the TANSO products. The resulting analysis globally underestimates the column-averaged dry-air mole fractions of methane (xCH4) just under 1 ppb on average compared to the TCCON data, whereas in the tropics it overestimates xCH4 by about 3 ppb. The random error is estimated to be less than 7 ppb when compared to TCCON data.

scholarly journals Comparison of XCO abundances from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change measured in Karlsruhe

2016 ◽  
Vol 9 (5) ◽  
pp. 2223-2239 ◽  
Author(s):  
Matthäus Kiel ◽  
Frank Hase ◽  
Thomas Blumenstock ◽  
Oliver Kirner
Keyword(s):  
Standard Deviation ◽  
Absorption Band ◽  
Correction Factor ◽  
Spectral Region ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Composition Change ◽  
Validation Data ◽  
Air Mass

Abstract. We present a comparison of Karlsruhe XCO records (April 2010–December 2014) from the Total Carbon Column Observing Network (TCCON) and from the spectral region covered by the Network for the Detection of Atmospheric Composition Change (NDACC). The Karlsruhe TCCON Fourier transform infrared (FTIR) spectrometer allows us to record spectra in the mid-infrared (MIR) and near-infrared (NIR) spectral region simultaneously, which makes Karlsruhe a favourable FTIR site to directly compare measurements from both spectral regions. We compare XCO retrieved from the fundamental absorption band at 4.7 µm (as used by NDACC) and first overtone absorption band at 2.3 µm (TCCON-style measurements). We observe a bias of (4.47 ± 0.17) ppb between both data sets with a standard deviation of 2.39 ppb in seasonal variation. This corresponds to a relative bias of (4.76 ± 0.18) % and a standard deviation of 2.28 %. We identify different sources which contribute to the observed bias (air-mass-independent correction factor, air-mass-dependent correction factor, isotopic identities, differing a priori volume mixing ratio profiles) and quantify their contributions. We show that the seasonality in the residual of NDACC and TCCON XCO can be largely explained by the smoothing effect caused by differing averaging kernel sensitivities between the MIR and NIR spectral region. This study aims to improve the comparability of NDACC and TCCON XCO validation data sets as desired for potential future satellite missions and model studies.

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