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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]

Sentinel-5 (S5) and its precursor (S5P) are future European satellite missions aiming at global monitoring of methane (CH4) column-average dry air mole fractions (XCH4). The spectrometers to be deployed onboard the satellites record spectra of sunlight backscattered from the Earth's surface and atmosphere. In particular, they exploit CH4 absorption in the shortwave infrared spectral range around 1.65 µm (S5 only) and 2.35 µm (both S5 and S5P) wavelength. Given an accuracy goal of better than 2% for XCH4 to be delivered on regional scales, assessment and reduction of potential sources of systematic error such as spectroscopic uncertainties is crucial. Here, we investigate how spectroscopic errors propagate into retrieval errors on the global scale. To this end, absorption spectra of a groundbased Fourier transform spectrometer (FTS) operating at very high spectral resolution serve as estimate for the quality of the spectroscopic parameters. Feeding the FTS fitting residuals as a perturbation into a global ensemble of simulated S5- and S5P-like spectra at relatively low spectral resolution, XCH4 retrieval errors exceed 0.6% in large parts of the world and show systematic correlations on regional scales, calling for improved spectroscopic parameters. [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]

We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to constrain global and North American inversions of methane emissions with 4° × 5° and up to 50 km × 50 km spatial resolution, respectively. The GOSAT data are first evaluated with atmospheric methane observations from surface networks (NOAA, TCCON) and aircraft (NOAA/DOE, HIPPO), using the GEOSChem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOSChem that we correct via quadratic regression. The surface and aircraft data are subsequently used for independent evaluation of the methane source inversions. Our global adjoint-based inversion yields a total methane source of 539Tga-1 and points to a large East Asian overestimate in the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide full error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tga-1, as compared to 24.9-27.0 Tga-1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tga-1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the South-Central US, the Central Valley of California, and Florida wetlands, large isolated point sources such as the US Four Corners also contribute. We attribute 29-44% of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20% to landfills/waste water, and 11-15% to coal with an additional 9.0-10.1 Tga-1 source from wetlands. [ABSTRACT FROM AUTHOR]

The article presents a study which focuses on the extent of the comparison between scanning imaging absorption spectrometer for atmospheric cartography (SCIAMACHY) and CarbonTracker XCO2. The study uses the retrieval algorithms to minimize scattering related errors. Results show that a significant fraction of the difference between SCIAMACHY WFMDv2.1 XCO2 and CarbonTracker over the southern hemisphere is explained by the presence of thin clouds.

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00± 0.16 ppm yr-1 compared to 1.94±0.03 ppm yr-1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1-1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10-20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements. [ABSTRACT FROM AUTHOR]

The article presents a study which determines errors of power plant annual emission estimates by a CarbonSat constellation. Two types of errors are quantified in the study, the systematic error of annual emissions from sparse sampling of emission and the wind speed dependent random errors caused by instrument detector noise. The significance of power plant emissions monitoring in fighting against global warming is discussed.

SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the SCIAMACHY and CarbonTracker carbon dioxide annual increases (2.00 ± 0.16 ppm yr-1 compared to 1.94±0.03 ppm yr-1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision of about 2.2 ppm and a relative accuracy of 1.1-1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb with respect to model simulations for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and less methane retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10-20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements. [ABSTRACT FROM AUTHOR]

Water plays a major role in the chemistry and radiative budget of the stratosphere. Air enters the stratosphere predominantly in the tropics, where the very low temperatures around the tropopause constrain water vapour mixing ratios to a few parts per million. Observations of stratospheric water vapour show a large positive long-term trend, which can not be explained by change in tropopause temperatures. Trends in the partitioning between vapour and ice of water entering the stratosphere have been suggested to resolve this conundrum. We present measurements of stratospheric H2O, HDO, CH4 and CH3D in the period 1991-2007 to evaluate this hypothesis. Because of fractionation processes during phase changes, the hydrogen isotopic composition of H2O is a sensitive indicator of changes in the partitioning of vapour and ice. We find that the seasonal variations of H2O are mirrored in the variation of the ratio of HDO to H2O with a slope of the correlation consistent with water entering the stratosphere mainly as vapour. The variability in the fractionation over the entire observation period is well explained by variations in H2O. The isotopic data allow concluding that the trend in ice arising from particulate water is no more than (0.01±0.13) ppmv/decade in the observation period. Our observations suggest that between 1991 and 2007 the contribution from changes in particulate water transported through the tropopause plays only a minor role in altering in the amount of water entering the stratosphere. [ABSTRACT FROM AUTHOR]

Water plays a major role in the chemistry and radiative budget of the stratosphere. Air enters the stratosphere predominantly in the tropics, where the very low temperatures around the tropopause constrain water vapour mixing ratios to a few parts per million. Observations of stratospheric water vapour show a large positive long-term trend, which can not be explained by change in tropopause temperatures. Trends in the partitioning between vapour and ice of water entering the stratosphere have been suggested to resolve this conundrum. We present measurements of stratospheric H2O, HDO, CH4 and CH3D in the period 1991-2007 to evaluate this hypothesis. Because of fractionation processes during phase changes, the hydrogen isotopic composition of H2O is a sensitive indicator of changes in the partitioning of vapour and ice. We find that the seasonal variations of H2O are mirrored in the variation of the ratio of HDO to H2O with a slope of the correlation consistent with water entering the stratosphere mainly as vapour. The variability in the fractionation over the entire observation period is well explained by variations in H2O. The isotopic data allow to conclude that the trend in ice arising from particulate water is no more than 0.01±0.13 ppmv/decade in the observation period. Our observations suggest that between 1991 and 2007 the contribution from changes in particulate water transported through the tropopause plays only a minor role in altering in the amount of water entering the stratosphere. [ABSTRACT FROM AUTHOR]

Within the European project UFTIR (Time series of Upper Free Troposphere observations from an European ground-based FTIR network), six ground-based stations in Western Europe, from 79° N to 28° N, all equipped with Fourier Transform infrared (FTIR) instruments and part of the Network for the Detection of Atmospheric Composition Change (NDACC), have joined their efforts to evaluate the trends of several direct and indirect greenhouse gases over the period 1995-2004. The retrievals of CO, CH4, C2H6, N2O, CHClF2, and O3 have been optimized. Using the optimal estimation method, some vertical information can be obtained in addition to total column amounts. A bootstrap resampling method has been implemented to determine annual partial and total column trends for the target gases. The present work focuses on the ozone results. The retrieved time series of partial and total ozone columns are validated with ground-based correlative data (Brewer, Dobson, UV-Vis, ozonesondes, and Lidar). The observed total column ozone trends are in agreement with previous studies: 1) no total column ozone trend is seen at the lowest latitude station Izaña (28° N); 2) slightly positive total column trends are seen at the two mid-latitude stations Zugspitze and Jungfraujoch (47° N), only one of them being significant; 3) the highest latitude stations Harestua (60° N), Kiruna (68° N) and Ny-Ålesund (79° N) show significant positive total column trends. Following the vertical information contained in the ozone FTIR retrievals, we provide partial columns trends for the layers: ground-10 km, 10-18 km, 18-27 km, and 27-42 km, which helps to distinguish the contributions from dynamical and chemical changes on the total column ozone trends. We obtain no statistically significant trends in the ground-10 km layer for five out of the six ground-based stations. We find significant positive trends for the lowermost stratosphere at the two mid-latitude stations, and at Ny- Ålesund. We find smaller, but significant trends for the 18- 27 km layer at Kiruna, Harestua, Jungfraujoch, and Izaña. The results for the upper layer are quite contrasted: we find significant positive trends at Kiruna, Harestua, and Jungfraujoch, and significant negative trends at Zugspitze and Izaña. These ozone partial columns trends are discussed and compared with previous studies. [ABSTRACT FROM AUTHOR]

This paper describes the statistical analysis of annual trends in long term datasets of greenhouse gas measurements taken over ten or more years. The analysis technique employs a bootstrap resampling method to determine both the long-term and intra-annual variability of the datasets, together with the uncertainties on the trend values. The method has been applied to data from a European network of ground-based solar FTIR instruments to determine the trends in the tropospheric, stratospheric and total columns of ozone, nitrous oxide, carbon monoxide, methane, ethane and HCFC-22. The suitability of the method has been demonstrated through statistical validation of the technique, and comparison with ground-based in-situ measurements and 3-D atmospheric models. [ABSTRACT FROM AUTHOR]

This paper describes the statistical analysis of annual trends in long term datasets of greenhouse gas measurements taken over ten or more years. The analysis technique employs a bootstrap resampling method to determine both the long-term and intra-annual variability of the datasets, together with the uncertainties on the trend values. The method has been applied to data from a European network of ground-based solar FTIR instruments to determine the trends in the tropospheric, stratospheric and total columns of ozone, nitrous oxide, carbon monoxide, methane, ethane and HCFC-22. The suitability of the method has been demonstrated through statistical validation of the technique, and comparison with ground-based in-situ measurements and 3-D atmospheric models. [ABSTRACT FROM AUTHOR]

We present long-term time-series of strato-mesospheric CO vertical columns measured from stations located in Antarctica, mid-latitudes and the Arctic, covering the period from 1997-2005. The instrument and the measurement technique allows the separation of tropospheric and strato-mesospheric contributions to the CO column, therefore providing information on the chemistry and dynamics both at low and high altitudes. Data from polar stations show a similar annual variability of strato-mesospheric CO with a strong maximum in late winter and spring. A small enhancement in late summer for some stations, which we call the "summer bulge", can be seen occasionally. Generally, the mid-latitude stations show no significant annual variability of strato-mesospheric CO columns. Measurements were compared with a two-dimensional chemistry-transport model of the middle atmosphere. The annual and latitudinal variations of CO are reproduced well by a model run including thermospheric CO. Comparison with two model scenarios show that the polar winter maximum is due solely to downward transport of thermospheric CO, while CHOx chemistry in the stratosphere could probably contribute to the summer maximum. [ABSTRACT FROM AUTHOR]

We present long-term time-series of strato-mesospheric CO vertical columns measured from stations located in Antarctica, mid-latitudes and the Arctic, covering the period from 1997-2005. The instrument and the measurement technique allows the separation of tropospheric and strato-mesospheric contributions to the CO column, therefore providing information on the chemistry and dynamics both at low and high altitudes. Data from polar stations show a similar annual variability of strato-mesospheric CO with a strong maximum in late winter and spring and a small enhancement in late summer for some stations, which we call the "summer bulge". Generally, the mid-latitude stations show no significant annual variability of strato-mesospheric CO columns. Measurements were compared with a two-dimensional chemistry-transport model of the middle atmosphere. The annual and latitudinal variations of CO are reproduced very well by a model run including thermospheric CO. Comparison with different model scenarios show that the polar winter maximum is due solely to downward transport of thermospheric CO, while the summer maximum is due to CHOx chemistry in the stratosphere. [ABSTRACT FROM AUTHOR]

Ozone profiles retrieved from limb scattering measurements of the SCIAMACHY instrument based on the satellite ENVISAT are compared to ground based low altitude resolution remote sensors. All profiles are retrieved using optimal estimation. Following the work of Rodgers and Connor (2003) the retrievals of the ground based instruments are simulated using the SCIAMACHY retrieval. The SCIAMACHY results and the results of the ground based microwave radiometer in Bremen and Ny Alesund agree within the expected covariance of the intercomparison. There are not enough coincident measurements of the FTIR instrument in order to allow for a conlusive statistical treatment. However, preliminary intercomparison results are presented. [ABSTRACT FROM AUTHOR]

CO, CH4, N2O and CO2 were retrieved from high resolution solar absorption spectra obtained during a ship cruise from Capetown to Bremerhaven in January/February 2003 by Fourier Transform Infrared (FTIR) spectroscopy. Precisions of better than 0.5% for the column averaged volume mixing ratios (VMR) of CH4 and CO2 are achieved using of O2 as a reference gas. Shipborne FTIR-measurements of CO and data from SCIAMACHY/ENVISAT retrieved by the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm show qualitatively the same latitudinal variations. WFM-DOAS data of CH4, N2O and CO2 measured over sea exhibit a great spread. The spread is significantly reduced for satellite measurements over land and a reasonable agreement can be obtained if the shipborne data is compared with the closest SCIAMACHY measurements over land. The number of comparisons is too small to draw conclusions. However, by including only WFM-DOAS data with small errors the shipborne and WFM-DOAS data compare within 5% for CH4 and CO2 and within 30% for N2O. [ABSTRACT FROM AUTHOR]

Ozone profiles retrieved from limb scattering measurements of the SCIAMACHY instrument based on the satellite ENVISAT are compared to ground-based low altitude resolution remote sensors. All profiles are retrieved using optimal estimation. Following the work of Rodgers and Connor (2003) the retrievals of the ground-based instruments are simulated using the SCIAMACHY retrieval. The SCIAMACHY results and the results of the ground-based microwave radiometer in Bremen and Ny Ålesund agree within the expected covariance of the intercomparison. [ABSTRACT FROM AUTHOR]

Carbon monoxide total column amounts in the atmosphere have been measured in the High Northern Hemisphere (30°-90° N, HNH) between January 2002 and December 2003 using infrared spectrometers of high and moderate resolution and the Sun as a light source. They were compared to ground-level CO mixing ratios and to total column amounts measured from space by the Terra/MOPITT instrument. All these data reveal increased CO abundances in 2002-2003 in comparison to the unperturbed 2000-2001 period. Maximum anomalies were observed in September 2002 and August 2003. Using a simple two-box model, the corresponding annual CO emission anomalies (referenced to 2000-2001 period) have been found equal to 95 Tg in 2002 and 130 Tg in 2003, thus close to those for 1996 and 1998. A good correlation with hot spots detected by a satellite radiometer allows one to assume strong boreal forest fires, occurred mainly in Russia, as a source of the increased CO burdens. [ABSTRACT FROM AUTHOR]