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We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the tnzuncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.

A portable Fourier transform spectrometer (FTS), model EM27/SUN, was deployed onboard the research vessel Polarstern to measure the column-average dry air mole fractions of carbon dioxide (XCO2) and methane (XCH4) by means of direct sunlight absorption spectrometry. We report on technical developments as well as data calibration and reduction measures required to achieve the targeted accuracy of fractions of a percent in retrieved XCO2 and XCH4 while operating the instrument under field conditions onboard the moving platform during a 6-week cruise on the Atlantic from Cape Town (South Africa, 34° S, 18° E; 5 March 2014) to Bremerhaven (Germany, 54° N, 19° E; 14 April 2014). We demonstrate that our solar tracker typically achieved a tracking precision of better than 0.05° toward the center of the sun throughout the ship cruise which facilitates accurate XCO2 and XCH4 retrievals even under harsh ambient wind conditions. We define several quality filters that screen spectra, e.g., when the field of view was partially obstructed by ship structures or when the lines-of-sight crossed the ship exhaust plume. The measurements in clean oceanic air, can be used to characterize a spurious air-mass dependency. After the campaign, deployment of the spectrometer alongside the TCCON (Total Carbon Column Observing Network) instrument at Karlsruhe, Germany, allowed for determining a calibration factor that makes the entire campaign record traceable to World Meteorological Organization (WMO) standards. Comparisons to observations of the GOSAT satellite and concentration fields modeled by the European Centre for Medium-Range Weather Forecasts (ECMWF) Copernicus Atmosphere Monitoring Service (CAMS) demonstrate that the observational setup is well suited to provide validation opportunities above the ocean and along interhemispheric transects. [ABSTRACT FROM AUTHOR]

We present 5 years of GOSAT XCH4 retrieved using the "proxy" approach. The Proxy XCH4 data are validated against ground-based TCCON observations and are found to be of high quality with a small bias of 4.8 ppb (~0:27 %) and a single-sounding precision of 13.4 ppb (~0:74 %). The station-to-station bias (a measure of the relative accuracy) is found to be 4.2 ppb. For the first time the XCH4 = XCO2 ratio component of the Proxy retrieval is validated (bias of 0.014 ppbppm-1 (~0:30 %), single-sounding precision of 0.033 ppbppm-1 (~0:72 %)). The uncertainty relating to the model XCO2 component of the Proxy XCH4 is assessed through the use of an ensemble of XCO2 models. While each individual XCO2 model is found to agree well with the TCCON validation data (r = 0:94-0.97), it is not possible to select one model as the best from our comparisons. The median XCO2 value of the ensemble has a smaller scatter against TCCON (a standard deviation of 0.92 ppm) than any of the individual models whilst maintaining a small bias (0.15 ppm). This model median XCO2 is used to calculate the Proxy XCH4 with the maximum deviation of the ensemble from the median used as an estimate of the uncertainty. We compare this uncertainty to the a posteriori retrieval error (which is assumed to reduce with sqrt(N)) and find typically that the model XCO2 uncertainty becomes significant during summer months when the a posteriori error is at its lowest due to the increase in signal related to increased summertime reflected sunlight. We assess the significance of these model and retrieval uncertainties on flux inversion by comparing the GOSAT XCH4 against modelled XCH4 from TM5-4DVAR constrained by NOAA surface observations (MACC reanalysis scenario S1- NOAA). We find that for the majority of regions the differences are much larger than the estimated uncertainties. Our findings show that useful information will be provided to the inversions for the majority of regions in addition to that already provided by the assimilated surface measurements. [ABSTRACT FROM AUTHOR]

Water vapour is one of the most important greenhouse gases. Long-term changes in the amount of water vapour in the atmosphere need to be monitored not only for its direct role as a greenhouse gas but also because of its role in amplifying other feedbacks such as clouds and albedo. In recent decades, monitoring of water vapour on a regular and continuous basis has become possible as a result of the steady increase in the number of deployed global positioning satellite (GPS) ground-based receivers. However, the Horn of Africa remained a data-void region in this regard until recently, when some GPS ground-receiver stations were deployed to monitor tectonic movements in the Great Rift Valley. This study seizes this opportunity and the installation of a Fourier transform infrared spectrometer (FTIR) at Addis Ababa to assess the quality and comparability of precipitable water vapour (PWV) from GPS, FTIR, radiosonde and interim ECMWF Re-Analysis (ERA-Interim) over Ethiopia. The PWV from the three instruments and the reanalysis show good correlation, with correlation coefficients in the range from 0.83 to 0.92. On average, GPS shows the highest PWV followed by FTIR and radiosonde observations. ERA-Interim is higher than all measurements with a bias of 4.6 mm compared to GPS. The intercomparison between GPS and ERA-Interim was extended to seven other GPS stations in the country. Only four out of eight GPS stations included simultaneous surface pressure observations. Uncertainty in the model surface pressure of 1 hPa can cause up to 0.35 mm error in GPS PWV. The gain obtained from using observed surface pressure in terms of reducing bias and strengthening correlation is significant but shows some variations among the GPS sites. The comparison between GPS and ERA-Interim PWV over the seven other GPS stations shows differences in the magnitude and sign of bias of ERA-Interim with respect to GPS PWV from station to station. This feature is also prevalent in diurnal and seasonal variabilities. The spatial variation in the relationship between the two data sets is partly linked to variation in the skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) model over different regions and seasons. This weakness in the model is related to poor observational constraints from this part of the globe and sensitivity of its convection scheme to orography and land surface features. This is consistent with observed wet bias over some highland stations and dry bias over few lowland stations. The skill of ECMWF in reproducing realistic PWV varies with time of the day and season, showing large positive bias during warm and wet summer at most of the GPS sites. [ABSTRACT FROM AUTHOR]

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]

This study examines the possibility of groundbased 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 longterm 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 groundbased FTIR experiments might contribute to global ozone databases. [ABSTRACT FROM AUTHOR]

Within the project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) ground- and space-based remote sensing as well as in situ data sets of tropospheric water vapour isotopologues are provided. The space-based remote-sensing data set is produced from spectra measured by the IASI (Infrared Atmospheric Sounding Interferometer) sensor and is potentially available on a global scale. Here, we present the MUSICA IASI data for three different geophysical locations (subtropics, midlatitudes, and Arctic), and we provide a comprehensive characterisation of the complex nature of such space-based isotopologue remotesensing products. The quality assessment study is complemented by a comparison to MUSICA's ground-based FTIR (Fourier Transform InfraRed) remote-sensing data retrieved from the spectra recorded at three different locations within the framework of NDACC (Network for the Detection of Atmospheric Composition Change). We confirm that IASI is able to measure tropospheric H2O profiles with a vertical resolution of about 4 km and a random error of about 10 %. In addition IASI can observe middle tropospheric δD that adds complementary value to IASI's middle tropospheric H2O observations. Our study presents theoretical and empirical proof that IASI has the capability for a global observation of middle tropospheric water vapour isotopologues on a daily timescale and at a quality that is sufficiently high for water cycle research purposes. [ABSTRACT FROM AUTHOR]

We present lower/middle tropospheric columnaveraged CH4 mole fraction time series measured by nine globally distributed ground-based FTIR (Fourier transform infrared) remote sensing experiments of the Network for the Detection of Atmospheric Composition Change (NDACC). We show that these data are well representative of the tropospheric regional-scale CH4 signal, largely independent of the local surface small-scale signals, and only weakly dependent on upper tropospheric/lower stratospheric (UTLS) CH4 variations. In order to achieve the weak dependency on the UTLS, we use an a posteriori correction method. We estimate a typical precision for daily mean values of about 0.5% and a systematic error of about 2.5 %. The theoretical assessments are complemented by an extensive empirical study. For this purpose, we use surface in situ CH4 measurements made within the Global Atmosphere Watch (GAW) network and compare them to the remote sensing data. We briefly discuss different filter methods for removing the local small-scale signals from the surface in situ data sets in order to obtain the in situ regional-scale signals. We find good agreement between the filtered in situ and the remote sensing data. The agreement is consistent for a variety of timescales that are interesting for CH4 source/sink research: day-to-day, monthly, and inter-annual. The comparison study confirms our theoretical estimations and proves that the NDACC FTIR measurements can provide valuable data for investigating the cycle of CH4. [ABSTRACT FROM AUTHOR]

Since May 2009, high-resolution Fourier Transform Infrared (FTIR) solar absorption spectra have been recorded at Addis Ababa (9.01° N latitude, 38.76° E longitude, 2443m altitude above sea level), Ethiopia. The vertical profiles and total column amounts of ozone (O3) are deduced from the spectra by using the retrieval code PROFFIT (V9.5) and regularly determined instrumental line shape (ILS). A detailed error analysis of the O3 retrieval is performed. Averaging kernels of the target gas shows that the major contribution to the retrieved information comes from the measurement. The degrees of freedom for signals is found to be 2.1 on average for the retrieval of O3 from the observed FTIR spectra. The ozone Volume Mixing Ratio (VMR) profiles and column amounts retrieved from FTIR spectra are compared with the coincident satellite observations of Microwave Limb Sounding (MLS), Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), Tropospheric Emission Spectrometer (TES), Ozone Monitoring Instrument (OMI), Atmospheric Infrared Sounding (AIRS) and Global Ozone Monitoring Experiment (GOME-2) instruments. The mean relative differences in ozone profiles of FTIR from MLS and MIPAS are generally lower than 15% within the altitude range of 27 to 36 km, whereas difference from TES is lower than 1 %. Comparisons of measurements of column amounts from the satellite and the ground-based FTIR show very good agreement as exhibited by relative differences within +0.2% to +2.8% for FTIR versus MLS and GOME-2; and -0.9 to -9.0% for FTIR versus OMI, TES and AIRS. The corresponding standard deviations are within 2.0 to 2.8% for FTIR versus MLS and GOME-2 comparisons whereas that of FTIR versus OMI, TES and AIRS are within 3.5 to 7.3 %. Thus, the retrieved O3 VMR and column amounts from a tropical site, Addis Ababa, is found to exhibit very good agreement with all coincident satellite observations over an approximate 3-yr period. [ABSTRACT FROM AUTHOR]

The article discusses a study that determines the total column dry air mole fraction (XCO) of the atmosphere by analysing direct solar radiation. It shows that the EM27 seems a very promising candidate for an instrument supporting the core Total Carbon Column Observation Network(TCCON) stations for increasing the global representativenes of greenhouse gas measurement. It notes that EM27 values found in this investigation is well inside the current network-wide TCCON accuracy of 0.25 %.

The article presents a study on the validation of the tropospheric methane (CH4) mole derived from ground-based Fourier Transform InfraRed (FTIR) (CH4) spectroscopy. It says that CH4 is important in atmospheric chemistry, affecting the oxidizing capacity of the atmosphere and serves as a precursor of tropospheric ozone (O3). The results showed that profile retrieval lets the direct estimation of the tropospheric column-averaged CH4 amounts.