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.

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 ◽  
Author(s):  
M. Kiel ◽  
F. Hase ◽  
T. Blumenstock ◽  
O. Kirner
Keyword(s):  
Standard Deviation ◽  
Absorption Band ◽  
Correction Factor ◽  
Spectral Region ◽  
Near Infrared ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Composition Change ◽  
Validation Data

Abstract. We present a comparison of Karlsruhe XCO records (April 2010–December 2014) from the Total Carbon Column Observing Network (TCCON) and retrieved 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 to record spectra in the mid-infrared (MIR) and near-infrared (NIR) spectral region simultaneously which makes Karlsruhe a favorable FTIR site to directly compare measurements from both spectral regions. We compare XCO retrieved from the fundamental absorption band at 4.5 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 (airmass-independent correction factor, airmass-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 estimated 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.

scholarly journals Construction of merged satellite total O<sub>3</sub> and NO<sub>2</sub> time series in the tropics for trend studies and evaluation by comparison to NDACC SAOZ measurements

2014 ◽  
Vol 7 (10) ◽  
pp. 3337-3354 ◽  
Author(s):  
M. Pastel ◽  
J.-P. Pommereau ◽  
F. Goutail ◽  
A. Richter ◽  
A. Pazmiño ◽  
...  
Keyword(s):  
Time Series ◽  
Lower Stratosphere ◽  
Atmospheric Composition ◽  
Data Sets ◽  
Composition Change ◽  
Long Time ◽  
Uv Visible ◽  
The Tropics ◽  
Lower Noise ◽  
Total Column

Abstract. Long time series of ozone and NO2 total column measurements in the southern tropics are available from two ground-based SAOZ (Système d'Analyse par Observation Zénithale) UV-visible spectrometers operated within the Network for the Detection of Atmospheric Composition Change (NDACC) in Bauru (22° S, 49° W) in S-E Brazil since 1995 and Reunion Island (21° S, 55° E) in the S-W Indian Ocean since 1993. Although the stations are located at the same latitude, significant differences are observed in the columns of both species, attributed to differences in tropospheric content and equivalent latitude in the lower stratosphere. These data are used to identify which satellites operating during the same period, are capturing the same features and are thus best suited for building reliable merged time series for trend studies. For ozone, the satellites series best matching SAOZ observations are EP-TOMS (1995–2004) and OMI-TOMS (2005–2011), whereas for NO2, best results are obtained by combining GOME version GDP5 (1996–2003) and SCIAMACHY – IUP (2003–2011), displaying lower noise and seasonality in reference to SAOZ. Both merged data sets are fully consistent with the larger columns of the two species above South America and the seasonality of the differences between the two stations, reported by SAOZ, providing reliable time series for further trend analyses and identification of sources of interannual variability in the future analysis.

scholarly journals Retrieval of xCO<sub>2</sub> from ground-based mid-infrared (NDACC) solar absorption spectra and comparison to TCCON

2016 ◽  
Vol 9 (2) ◽  
pp. 577-585 ◽  
Author(s):  
Matthias Buschmann ◽  
Nicholas M. Deutscher ◽  
Vanessa Sherlock ◽  
Mathias Palm ◽  
Thorsten Warneke ◽  
...  
Keyword(s):  
Absorption Spectra ◽  
Seasonal Cycle ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Solar Absorption ◽  
Mid Infrared ◽  
Infrared Spectral ◽  
Ftir Spectrometer ◽  
Total Column

Abstract. High-resolution solar absorption spectra, taken within the Network for the Detection of Atmospheric Composition Change Infrared Working Group (NDACC-IRWG) in the mid-infrared spectral region, are used to infer partial or total column abundances of many gases. In this paper we present the retrieval of a column-averaged mole fraction of carbon dioxide from NDACC-IRWG spectra taken with a Fourier transform infrared (FTIR) spectrometer at the site in Ny-Ålesund, Spitsbergen. The retrieved time series is compared to colocated standard TCCON (Total Carbon Column Observing Network) measurements of column-averaged dry-air mole fractions of CO2 (denoted by xCO2). Comparing the NDACC and TCCON retrievals, we find that the sensitivity of the NDACC retrieval is lower in the troposphere (by a factor of 2) and higher in the stratosphere, compared to TCCON. Thus, the NDACC retrieval is less sensitive to tropospheric changes (e.g., the seasonal cycle) in the column average.

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 First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2012 ◽  
Vol 5 (1) ◽  
pp. 1355-1379
Author(s):  
F. Forster ◽  
R. Sussmann ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
D. W. T. Griffith ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
Calibration Factor ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar FTIR measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.) and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR time series shows a phase shift in XCH4 seasonality, i.e. a significant time-dependent bias leading to a standard deviation (stdv) of the difference time series (NIR-MIR) of 8.4 ppb. After eliminating differences in a prioris by using ACTM-simulated profiles as a common prior, the seasonalities of the (corrected) MIR and NIR time series agree within the noise (stdv = 5.2 ppb for the difference time series). The difference time series (NIR-MIR) do not show a significant trend. Therefore it is possible to use a simple scaling factor for the intercalibration without a time-dependent linear or seasonal component. Using the Garmisch and Wollongong data together, we obtain an overall calibration factor MIR/NIR = 0.9926(18). The individual calibration factors per station are 0.9940(14) for Garmisch and 0.9893(40) for Wollongong. They agree within their error bars with the overall calibration factor which can therefore be used for both stations. Our results suggest that after applying the proposed intercalibration concept to all stations performing both NIR and MIR measurements, it should be possible to obtain one refined overall intercalibration factor for the two networks. This would allow to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

scholarly journals Validation of SCIAMACHY HDO/H<sub>2</sub>O measurements using the TCCON and NDACC-MUSICA networks

2015 ◽  
Vol 8 (4) ◽  
pp. 1799-1818 ◽  
Author(s):  
R. A. Scheepmaker ◽  
C. Frankenberg ◽  
N. M. Deutscher ◽  
M. Schneider ◽  
S. Barthlott ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Hydrological Cycle ◽  
Source Region ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
The Tibetan Plateau ◽  
Wet Season ◽  
Data Set ◽  
The Mean ◽  
The Impact

Abstract. Measurements of the atmospheric HDO/H2O ratio help us to better understand the hydrological cycle and improve models to correctly simulate tropospheric humidity and therefore climate change. We present an updated version of the column-averaged HDO/H2O ratio data set from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). The data set is extended with 2 additional years, now covering 2003–2007, and is validated against co-located ground-based total column δD measurements from Fourier transform spectrometers (FTS) of the Total Carbon Column Observing Network (TCCON) and the Network for the Detection of Atmospheric Composition Change (NDACC, produced within the framework of the MUSICA project). Even though the time overlap among the available data is not yet ideal, we determined a mean negative bias in SCIAMACHY δD of −35 ± 30‰ compared to TCCON and −69 ± 15‰ compared to MUSICA (the uncertainty indicating the station-to-station standard deviation). The bias shows a latitudinal dependency, being largest (∼ −60 to −80‰) at the highest latitudes and smallest (∼ −20 to −30‰) at the lowest latitudes. We have tested the impact of an offset correction to the SCIAMACHY HDO and H2O columns. This correction leads to a humidity- and latitude-dependent shift in δD and an improvement of the bias by 27‰, although it does not lead to an improved correlation with the FTS measurements nor to a strong reduction of the latitudinal dependency of the bias. The correction might be an improvement for dry, high-altitude areas, such as the Tibetan Plateau and the Andes region. For these areas, however, validation is currently impossible due to a lack of ground stations. The mean standard deviation of single-sounding SCIAMACHY–FTS differences is ∼ 115‰, which is reduced by a factor ∼ 2 when we consider monthly means. When we relax the strict matching of individual measurements and focus on the mean seasonalities using all available FTS data, we find that the correlation coefficients between SCIAMACHY and the FTS networks improve from 0.2 to 0.7–0.8. Certain ground stations show a clear asymmetry in δD during the transition from the dry to the wet season and back, which is also detected by SCIAMACHY. This asymmetry points to a transition in the source region temperature or location of the water vapour and shows the added information that HDO/H2O measurements provide when used in combination with variations in humidity.

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 First intercalibration of column-averaged methane from the Total Carbon Column Observing Network and the Network for the Detection of Atmospheric Composition Change

2013 ◽  
Vol 6 (2) ◽  
pp. 397-418 ◽  
Author(s):  
R. Sussmann ◽  
A. Ostler ◽  
F. Forster ◽  
M. Rettinger ◽  
N. M. Deutscher ◽  
...  
Keyword(s):  
Time Series ◽  
Near Infrared ◽  
A Priori ◽  
Time Dependent ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
Composition Change ◽  
Data Set ◽  
The Difference ◽  
Difference Time

Abstract. We present the first intercalibration of dry-air column-averaged mole fractions of methane (XCH4) retrieved from solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC) in the mid-infrared (MIR) versus near-infrared (NIR) soundings from the Total Carbon Column Observing Network (TCCON). The study uses multi-annual quasi-coincident MIR and NIR measurements from the stations Garmisch, Germany (47.48° N, 11.06° E, 743 m a.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30 m a.s.l.). Direct comparison of the retrieved MIR and NIR XCH4 time series for Garmisch shows a quasi-periodic seasonal bias leading to a standard deviation (stdv) of the difference time series (NIR–MIR) of 7.2 ppb. After reducing time-dependent a priori impact by using realistic site- and time-dependent ACTM-simulated profiles as a common prior, the seasonal bias is reduced (stdv = 5.2 ppb). A linear fit to the MIR/NIR scatter plot of monthly means based on same-day coincidences does not show a y-intercept that is statistically different from zero, and the MIR/NIR intercalibration factor is found to be close to ideal within 2-σ uncertainty, i.e. 0.9996(8). The difference time series (NIR–MIR) do not show a significant trend. The same basic findings hold for Wollongong. In particular an overall MIR/NIR intercalibration factor close to the ideal 1 is found within 2-σ uncertainty. At Wollongong the seasonal cycle of methane is less pronounced and corresponding smoothing errors are not as significant, enabling standard MIR and NIR retrievals to be used directly, without correction to a common a priori. Our results suggest that it is possible to set up a harmonized NDACC and TCCON XCH4 data set which can be exploited for joint trend studies, satellite validation, or the inverse modeling of sources and sinks.

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 Quality assessment of ozone total column amounts as monitored by ground-based solar absorption spectrometry in the near infrared (> 3000 cm<sup>−1</sup>)

2014 ◽  
Vol 7 (9) ◽  
pp. 3071-3084 ◽  
Author(s):  
O. E. García ◽  
M. Schneider ◽  
F. Hase ◽  
T. Blumenstock ◽  
E. Sepúlveda ◽  
...  
Keyword(s):  
Spectral Region ◽  
Near Infrared ◽  
Systematic Difference ◽  
Total Carbon ◽  
Atmospheric Composition ◽  
High Spectral Resolution ◽  
Wave Number ◽  
Solar Absorption ◽  
Total Column

Abstract. This study examines the possibility of ground-based remote-sensing ozone total column amounts (OTC) from spectral signatures at 3040 and 4030 cm−1. These spectral regions are routinely measured by the NDACC (Network for the Detection of Atmospheric Composition Change) ground-based FTIR (Fourier transform infraRed) experiments. In addition, they are potentially detectable by the TCCON (Total Carbon Column Observing Network) FTIR instruments. The ozone retrieval strategy presented here estimates the OTC from NDACC FTIR high-resolution spectra with a theoretical precision of about 2 and 5% in the 3040 and 4030 cm−1 regions, respectively. Empirically, these OTC products are validated by inter-comparison to FTIR OTC reference retrievals in the 1000 cm−1 spectral region (standard reference for NDACC ozone products), using an 8-year FTIR time series (2005–2012) taken at the subtropical ozone supersite of the Izaña Atmospheric Observatory (Tenerife, Spain). Associated with the weaker ozone signatures at the higher wave number regions, the 3040 and 4030 cm−1 retrievals show lower vertical sensitivity than the 1000 cm−1 retrievals. Nevertheless, we observe that the rather consistent variations are detected: the variances of the 3040 cm−1 and the 4030 cm−1 retrievals agree within 90 and 75%, respectively, with the variance of the 1000 cm−1 standard retrieval. Furthermore, all three retrievals show very similar annual cycles. However, we observe a large systematic difference of about 7% between the OTC obtained at 1000 and 3040 cm−1, indicating a significant inconsistency between the spectroscopic ozone parameters (HITRAN, 2012) of both regions. Between the 1000 cm and the 4030 cm−1 retrieval the systematic difference is only 2–3%. Finally, the long-term stability of the OTC retrievals has also been examined, observing that both near-infrared retrievals can monitor the long-term OTC evolution, consistent with the 1000 cm−1 reference data. These findings demonstrate that recording the solar absorption spectra in the 3000 cm−1 spectral region at high spectral resolution (about 0.005 cm−1) might be useful for TCCON sites. Hence, both NDACC and TCCON ground-based FTIR experiments might contribute to global ozone databases.

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