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The article presents a study that examines the usefulness of the desktop optical spectrum analyzer (OSA) for measuring atmospheric carbon dioxide and methane column densities at surface sites. It shows that OSA is a promising technology for measuring the densities due to its smaller physical size and lower cost. It expects that OSA will provide a supplemental measuring system to the existing fourier transform spectroscopy (FTS) network.

The article presents a study on the use of solar absorption spectrometry with a low resolution spectrometer for remote sensing of CO2 and CH4. The study measures the remote sensing using the precision of the low resolution instrument, 0.32 percent for XCO2 and 0.46 percent for XCH4. It reveals that XCO2 can be measured with a low resolution FTS instrument with sufficient precision and accuracy.

The article presents a study which explores the usability of optical spectrum analyzers (OSA) in measuring atmospheric carbon dioxide and methane column densities. It is inferred that carbon dioxide and methane are the highest contributors to overall global radiative forcing. Two measurement campaigns are outlined which involve high resolution Fourier transform spectroscopy (FTS) and calibration method against aircraft carbon dioxide profiles.

The article presents a study which looks into the remote sensing of carbon dioxide (CO) and atmospheric methane (CH4) through solar absorption spectrometry. The study operates the high resolution instrument as part of the Total Carbon Column Observing Network (TCCON). It concludes that a low resolution Fourier Transform Spectrometry (FTS) instrument is effective in measuring XCO2.

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 stationto- 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. [ABSTRACT FROM AUTHOR]

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 ‰. [ABSTRACT FROM AUTHOR]

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 ‰. [ABSTRACT FROM AUTHOR]

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, 743ma.s.l.), and Wollongong, Australia (34.41° S, 150.88° E, 30ma.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 timedependent a priori impact by using realistic site- and timedependent 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 sameday 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. [ABSTRACT FROM AUTHOR]

The article discusses the study that evaluates the IASI carbon monoxide (CO) total column product for 2008. It indicates that the IASI total columns generally show an equal distribution of under- and overestimation. It suggests the need for further work to identify the source of discrepancies observed on individual measurements, such as the specific contaminations due to fire pollution plumes.

The article presents a study which examines the carbon monoxide (CO) measurements at the Infrared Atmospheric Sounding Interferometer (IASI). The use of the Fast Optimal Retrievals on Layers for IASI (FORLI) software developed at the Université Libre de Bruxelles (ULB) in the CO measurements is highlighted. It also outlines the spectrometer sites from the Network for the Detection of Atmospheric Composition Change (NDACC).

The article presents a study which explores the intercalibration of column-averaged methane within the Network for the Detection of Atmospheric Composition Change (NDACC) which is complemented by Network for the Total Carbon Column Observing Network (TCCON). The study elaborates the aforementioned intercalibration method and the mid-infrared (MIR) and near-infrared (NIR) retrieval strategies. It also presents results of the intercalibration approach and gives conclusions.

The article focuses on a strategy for the retrieval of column-averaged dry-air mole fractions of atmospheric methane from mid-infrared ground-based solar fourier transform infrared spectroscopy (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC). It discusses the utility of NDACC methane data for satellite validation and for the inversion of regional-scale sources. The application of a first-order Tikhonov constraints is also discussed.

The article presents the MIR-GBM v1.0 strategy for retrieving atmospheric methane (CH4) from mid-infrared solar Fourier transform infrared (FTIR) measurements of the Network for the Detection of Atmospheric Composition Change (NDACC). It states that the NDACC methane data are used for satellite validation as well as for the inversion of regional-scale sources. It further cites the need of improved spectroscopic parameters for methane and deuterium oxide (HDO) in the spectral domain.

The article presents a study on the validation of Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) carbon monoxide (CO) total column measurements through ground-based spectrometer observations for a five year period 2003-2007. The validation of SCIAMACHY with ground-based spectrometer (GBS) observations have rendered satisfactory results. Including everything, a good agreement between SCIAMACHY and GBS is derived for both mean values and seasonal variations.

The article presents a validation of five-year SCIAMACHY CO observations from the iterative maximum likelihood method (IMLM) algorithm using 20 ground based spectrometer (GBS) stations. It mentions that the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography provides over five years of carbon monoxide data based on reflected sunlight measurements in the short-wave infrared. Further, the article discusses the IMLM retrieval algorithm, GBS measurements and the TM4 model.